Method, apparatus, and system of information transmission
The method integrates spatial and RF characteristics using a unified reference signal, enhancing reliability and efficiency in communication systems by leveraging antenna array configurations and advanced data processing.
Patent Information
- Application Number
- PCT/CN2024/107907
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2024-04-30
- Filing Date
- 2024-07-26
- Publication Date
- 2025-11-06
AI Technical Summary
Conventional sensing and communication systems operate in separate frequency domains, inefficiently obtaining spatial and RF characteristics.
A method and apparatus that utilize a reference signal associated with multiple angles of departure to efficiently obtain spatial and RF characteristics by integrating them into a unified information transmission system, leveraging transmit antenna array configurations and advanced data processing techniques.
Enhances the reliability and efficiency of obtaining spatial and RF characteristics, allowing for dynamic adjustments and predictive analytics to improve communication performance under varying environmental conditions.
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Figure CN2024107907_06112025_PF_FP_ABST
Abstract
Description
METHOD, APPARATUS, AND SYSTEM OF INFORMATION TRANSMISSION
[0001] The present application claims priority to PCT patent application No. PCT / CN2024 / 090862, entitled "METHOD, APPARATUS AND SYSTEM OF 4D RF MAP RECONSTRUCTION BASED ON CSI IN ULTRA-MASSIVE MIMO SYSTEM" , filed on April 30, 2024, and hereby incorporated by reference in its entirety.TECHNICAL FIELD
[0002] Embodiments of the present application relate to the field of communications, and more specifically, to a method, apparatus, and system of information transmission.BACKGROUND
[0003] Sensing systems that collect sensing data have been introduced to obtain spatial characteristics of an area in various fields.
[0004] However, the conventional sensing system and communication system are separated in a frequency domain. Operational frequency for the sensing system or the communication system, is strongly related to radio frequency (RF) characteristics. That is, the spatial characteristics and the RF characteristics are obtained from different systems in an inefficient way.
[0005] Therefore, an urgent technical problem to be solved is how to obtain spatial characteristics and RF characteristics efficiently.SUMMARY
[0006] Embodiments of the present application provide a method, apparatus, and system of information transmission. Spatial characteristics and RF characteristics can be obtained efficiently.
[0007] According to a first aspect, a method is described. The method may be applied at a terminal side, for example, a terminal (e.g., an electronic device (ED) ) or a module in a terminal, a circuit or a chip (for example, a modem chip, also referred to as a baseband chip, or a system on chip (SoC) chip or a system in package (SIP) chip that includes a modem core that is responsible for a communication function in a terminal. For example, the method is applied to a terminal. In this method, the terminal receives a reference signal, where the reference signal is associated with multiple angles of departure, denoted as P; and the terminal transmits first information based on the reference signal, where the first information indicates a parameter set of path loss associated with a full set or a subset of the P, denoted as S.
[0008] According to a second aspect, a method may be applied to a network side, for example, a location server (e.g., a base station (BS) ) or a component (for example, a circuit, a chip, or a chip system) in a location server on a network side. For example, the method is applied to a location server. In the method, the location server transmits a reference signal, where the reference signal is associated with multiple angles of departure, denoted as P; and the location server receives first information, the first information is generated based on the reference signal, and the first information indicates a parameter set of path loss associated with a full set or a subset of the P, denoted as S.
[0009] According to the foregoing method, the first information indicates both angles of departure (as spatial characteristics) and associated path loss (as RF characteristics) . The spatial characteristics and the RF characteristics can be obtained based on the same reference signal in an efficient way.
[0010] According to the first aspect or the second aspect, in a possible design, the S includes one or more of: at least one angle where each angle corresponds to at least one line-of-sight (LOS) path, and at least one angle where each angle corresponds to at least one i-bounce non-line-of-sight (LOS) path, i=1, …, M, M is a positive integer.
[0011] According to the foregoing method, the terminal side may not feedback on the spatial characteristics and the RF characteristics of entire paths. The resource consumption of the first information can be reduced.
[0012] According to the first aspect or the second aspect, in a possible design, the first information is generated based on a configuration of transmit antenna array associated with the reference signal.
[0013] According to the foregoing method, the terminal side may generate the first information based on the configuration of transmit antenna array. The configuration of the transmit antenna array is related to angles of departure, which can represent the spatial characteristics.
[0014] According to the first aspect or the second aspect, in a possible design, the configuration of transmit antenna array indicates one or more of: a type of the transmit antenna array, a quantity of transmit antennas of the transmit antenna array, spacing between adjacent transmit antennas of the transmit antenna array, parameters related to reference locations corresponding to the transmit antenna array, where the reference locations are used for generating the first information.
[0015] According to the foregoing method, the configuration of the transmit antenna array may be used for determining the generating method of the first information. For example, the terminal side may determine a proper method to generate the first information. The configuration of the transmit antenna array may be used for generating the first information. For example, the configuration may include parameters used for generating the first information. This can improve the reliability of obtaining spatial characteristics and RF characteristics.
[0016] According to the first aspect, in a possible design, the method further includes: the terminal receives the second information, where the second information indicates part or all of the configuration of transmit antenna array.
[0017] According to the second aspect, in a possible design, the method further includes: the location server transmits the second information, where the second information indicates part or all of the configuration of transmit antenna array.
[0018] According to the foregoing method, the second information indicates the part or all of the configurations of transmit antenna array, so that the terminal can generate the first information based on the second information. The reliability of first information generation can be improved.
[0019] According to the first aspect or the second aspect, in a possible design, angles from the transmit antenna array to the reference locations relative to the transmit antenna array include the P.
[0020] According to the foregoing method, the reference locations can be designed to reflect the spatial characteristics of angles of departure (P) where the reference signal is transmitted. Thereby, the reference locations can facilitate the generation of the first information.
[0021] According to the first aspect or the second aspect, in a possible design, the parameters indicate a set of first thresholds corresponding to path loss associated with the P.
[0022] According to the foregoing method, the parameters related to the reference locations can be designed to reflect the path loss characteristics associated with the P. Thereby, the reference locations can facilitate the generation of the first information.
[0023] According to the first aspect or the second aspect, in a possible design, the second information is generated based on one or more of: a location of the ED, an orientation of the ED, and a capability of the ED.
[0024] According to the foregoing method, the second information may be generated based on information related to the ED. For example, the BS may determine parameters related to the ED to generate the second information, avoiding the second information carrying too much useless information.
[0025] According to the first aspect, in a possible design, the method includes: the terminal transmits third information, where the third information is used for determining the parameters.
[0026] According to the second aspect, in a possible design, the method includes: the location server receives third information, where the third information is used for determining the parameters.
[0027] According to the foregoing method, the terminal could transmit the third information to the BS, so that the BS may generate the second information based on the third information. This can improve the reliability of the second information generation.
[0028] According to the first aspect or the second aspect, in a possible design, the parameters are associated with one or more of factors related to the reception of the reference signal: frequency, weather conditions, an orientation of the ED, and a communication environment of the ED.
[0029] According to the foregoing method, the RF characteristics may be affected by a variety of factors. Therefore, the parameters can be associated with various factors. Thereby, the ED may use the parameters based on these factors, improving the reliability of the first information.
[0030] According to the first aspect or the second aspect, in a possible design, the second information indicates one or more of: transmit array response matrix At (φ) of the transmit antenna; a set of vectors corresponding to the angles from the transmit antenna array to the reference locations related to the transmit antenna array; and a set of first thresholds corresponding to the angles from the transmit antenna array to the reference locations relative to the transmit antenna array; where the set of vectors and the set of first thresholds are derived from channel estimation between the transmit antennas and the reference locations.
[0031] According to the foregoing method, the second information can indicate the parameters required for generating the first information, ensuring the reliable generation of the first information.
[0032] According to the first aspect or the second aspect, in a possible design, the S comprises at least one angle corresponding to at least one i-bounce NLOS path, the first information is further based on a second threshold, wherein the second threshold is related to a value of the M.
[0033] According to the foregoing method, a second threshold may be designed to control the number of bounces of the path indicated by the first information, improving the reliability of the first information.
[0034] According to the first aspect or the second aspect, in a possible design, the second information further comprises an indication of the second threshold.
[0035] According to the foregoing method, the second information can indicate the second threshold required for generating the first information, ensuring the reliable generation of the first information.
[0036] According to the first aspect or the second aspect, in a possible design, the parameter set of path loss includes one or more of: reference signal received quality (RSRP) , signal to interference plus noise ratio (SINR) , channel quality indicator (CQI) , and rank indicator (RI) .
[0037] According to the first aspect or the second aspect, in a possible design, the first information further indicates propagation delay (s) associated with the reference signal.
[0038] According to the foregoing method, the first information may further indicate time characteristics, improving the performance of the first information.
[0039] According to the first aspect or the second aspect, in a possible design, the first information comprises Npath set (s) of parameters corresponding to Npath sub-channel (s) , the Npath sub-channel (s) is selected from r sub-channel (s) , the r sub-channel (s) is obtained from channel estimation between the ED and a transmitter, Npath and r are positive integers and Npath is less than or equal to r.
[0040] According to the foregoing method, the first information may indicate related parameters of part or all of the r sub-channels.
[0041] According to the first aspect or the second aspect, in a possible design, a set of parameters corresponding to a subchannel comprises one or more of: index (es) information of part or all of the S associated with the sub-channel; path loss information associated with the sub-channel; and time delay information associated with the sub-channel.
[0042] According to the foregoing method, the first information may indicate parameters related to angular characteristics, path loss characteristics and / or time characteristics, so that the BS may construct a 4D RF map based on these characteristics.
[0043] According to the first aspect or the second aspect, in a possible design, the first information further indicates one or more of: a location of the ED, an orientation of the ED, and a configuration of receive antennas corresponding to the reference signal.
[0044] According to the foregoing method, the first information may indicate more parameters related to the ED, so that the BS may construct a 4D RF map with better performance.
[0045] According to the first aspect, in a possible design, the method further includes: the terminal adjusts operational parameters based on the first information.
[0046] According to the first aspect, in a possible design, the operational parameters include one or more of: parameter (s) related to power settings, parameter (s) related to antenna configurations, and parameter (s) related to processing capabilities.
[0047] According to the foregoing method, it allows the ED to modify its settings based on the information received, to optimize performance in variable dynamic environments (e.g., variable signal conditions) .
[0048] According to the first aspect, in a possible design, the method further includes: the location server adjusts operational parameters based on the first information.
[0049] According to the first aspect, in a possible design, the operational parameters include one or more of: parameter (s) related to power settings, parameter (s) related to antenna configurations, and parameter (s) related to processing capabilities.
[0050] According to the foregoing method, it allows the BS to modify its settings based on the information received, to optimize performance in variable dynamic environments (e.g., variable signal conditions) .
[0051] According to the first aspect or the second aspect, in a possible design, the first information is used to predict a channel state associated with part or all of the S.
[0052] For example, the first information may further include machine learning algorithms to predict path loss and angular characteristics based on historical data collected via the reference signal.
[0053] According to the foregoing method, this method incorporates advanced data processing techniques to enhance the predictive accuracy and efficiency of the system, aligning with cutting-edge technological practices.
[0054] According to the first aspect or the second aspect, in a possible design, a type of transmit antenna array is a uniform rectangular array (URA) , and the first information is derived using discrete Fourier transform (DFT) .
[0055] According to the foregoing method, the first information is derived using DFT when the BS employs a URA type of antennas.
[0056] According to the foregoing method, the first information is derived using DFT when the BS employs a URA type of antennas, and the distance between any two antenna elements of the BS is greater than or equal to a distance threshold (e.g., half the wavelength) .
[0057] According to the first aspect or the second aspect, in a possible design, the DFT is used to obtain projections of a set of vectors onto the transmit array response matrix At (φ) of the transmit antenna, where the set of vectors is obtained from channel estimation based on the reference signal.
[0058] The conditions under which DFT is applied, ensure that the antenna setup is suitable for such computations without mutual interference.
[0059] According to the first aspect or the second aspect, in a possible design, the distance between any two antenna elements of the BS is greater than or equal to a distance threshold (e.g., half the wavelength) , a quantity of transmit antennas is larger than or equal to a quantity threshold, and first information includes a set of vectors, wherein the set of vectors is obtained from channel estimation based on the reference signal.
[0060] According to the foregoing method, the first information may be obtained by substituting projections directly when the BS meets the foregoing criteria. This method may be used instead of matrix-based calculations, which simplifies the data processing underived certain configurations. A simplification in the computational process under physical and quantitative criteria, enhancing processing speed and reducing complexity
[0061] According to the first aspect or the second aspect, in a possible design, the first information is processed using a virtual planar screen to simplify the computational load by selecting specific sub-channel vectors based on their estimated significance in representing the channel state. A computational abstraction is used to reduce complexity by focusing on significant sub-channels (vectors) , enhancing the efficiency of information transmission. The use of a computational abstraction to reduce complexity by focusing on significant channel vectors is particularly useful in complex multi-path environments.
[0062] According to the first aspect or the second aspect, in a possible design, the Npath subchannel (s) is selected from the r subchannel (s) based on: parameters related to reference locations and transmit antennas, and an orientation of the ED.
[0063] According to the foregoing method, the selection of sub-channels (vectors) may be predefined criteria such as the strength of the signal path or its alignment with predicted user movement or device orientation. The criteria for selecting significant vectors link the processing to practical operational needs and expected conditions.
[0064] According to the first aspect or the second aspect, in a possible design, the virtual planar screen is configured dynamically based on real-time data regarding the operating environment, including factors such as obstacles present, prevailing weather conditions, and expected changes in the ED’s location.
[0065] According to the foregoing method, adaptability in the virtual planar screen setup, allows the base station to respond dynamically to changes in the network environment.
[0066] According to the foregoing method, the dynamic adjustment of the virtual planar screen settings is based on environmental data, which enhances the method’s adaptability and accuracy in real-world scenarios.
[0067] In some instances, the base station employs machine learning algorithms to dynamically adjust the transmission power and beamforming patterns based on the first information received from the ED.
[0068] In some instances, the base station utilizes a predictive modeling system to anticipate changes in channel conditions based on historical data and environmental sensors, adjusting transmission parameters proactively. Predictive analytics can enhance the performance and reliability of the communication system under varying environmental conditions.
[0069] In some instances, the reference signal is processed using a spatial filtering algorithm to isolate the reference signal from different angles of departure. This can enhance the accuracy of the path loss and angular characteristics.
[0070] In some instances, the transmit antennas of the base station are divided into one or more sectors, each sector corresponds to a subset of the multiple angles of departure and is managed based on the first information. That is, the base station may implement a sectorized antenna system, and the base station may manage each sector independently. The sectorized approach to managing transmissions allows for finer control over signal direction and strength.
[0071] In some instances, the operational parameters are determined based on the first information and real-time data. For example, the base station may conduct real-time environmental scanning using integrated sensors to adjust the reference signal’s parameters dynamically to counteract adverse propagation effects caused by weather by weather or physical obstructions, improving data accuracy and integrity. The capability of the BS to adapt its operations based on real-time environmental sensing enhances robustness against external disturbances.
[0072] In some instances, the method further includes: the base station transmits the first information to an adjacent base station; and / or receives the first information from an adjacent base station, where the first information indicates a path loss associated with angular information of the adjacent base station. For example, the base station coordinates with adjacent base stations to manage overlapping coverage areas, optimizing the angles of departure and power levels to reduce interference and improve coverage efficiency. The coordination between multiple base stations for optimal coverage and small interference in dense network environments.
[0073] In some instances, the method further includes: the base station transmits information that indicates part or all of the operational parameters to the ED. For example, the base station deploys a feedback mechanism to the ED that adjusts its operational parameters based on the quality of service metrics observed from the first information, ensuring optimal end-user experience. A feedback loop where the BS adjusts its operations based on the service quality experienced by end-users, fostering a user-centric approach.
[0074] According to a third aspect, a communication apparatus is described. The communication apparatus has a function of implementing the first aspect. For example, the communication apparatus includes a corresponding module, unit, or means for performing operations in the first aspect. The module, unit, or means may be specifically implemented by using software, may be implemented by using hardware, or may be implemented by using software in combination with hardware.
[0075] According to a fourth aspect, a communication apparatus is described. The communication apparatus has a function of implementing the second aspect. For example, the communication apparatus includes a corresponding module, unit, or means for performing operations in the second aspect. The module, unit, or means may be specifically implemented by using software, may be implemented by using hardware, or may be implemented by using software in combination with hardware.
[0076] According to a fifth aspect, another communication apparatus is described. The communication apparatus includes a memory and one or more processors. The memory is configured to store a part or all of a necessary computer program or instructions for implementing a function in the first aspect. One or more processors may execute the computer program or the instructions, and when the computer program or the instructions is / are executed, the communication apparatus is enabled to implement the method in any possible design or implementation of the first aspect.
[0077] In some implementations, the communication apparatus may further include an interface circuit, and the processor is configured to communicate with another apparatus or component through the interface circuit.
[0078] In some implementations, the communication apparatus may further include the memory.
[0079] The communication apparatus may be a terminal, a module in a terminal, or a chip responsible for a communication function in a terminal, for example, a modem chip (also referred to as a baseband chip) or an SoC chip, or an SIP chip that includes a modem module.
[0080] According to a sixth aspect, another communication apparatus is described. The communication apparatus includes a memory and one or more processors. The memory is configured to store a part or all of a necessary computer program or instructions for implementing a function in the second aspect. One or more processors may execute the computer program or the instructions, and when the computer program or the instructions is / are executed, the communication apparatus is enabled to implement the method in any possible design or implementation of the second aspect.
[0081] In some implementations, the communication apparatus may further include an interface circuit, and the processor is configured to communicate with another apparatus or component through the interface circuit.
[0082] In some implementations, the communication apparatus may further include the memory.
[0083] The communication apparatus may be a location server, a module in a location server, or a chip responsible for a communication function in a location server, for example, a modem chip (also referred to as a baseband chip) or an SoC chip or a SIP chip that includes a modem module.
[0084] According to a seventh aspect, a communication system is described. The communication system includes a first communication apparatus and / or a second communication apparatus, the first communication apparatus is configured to perform the method in any possible implementation of the first aspect, and the second communication apparatus is configured to perform the method in any possible implementation of the second aspect.
[0085] According to an eighth aspect, a computer-readable storage medium is described. The computer-readable storage medium stores computer-readable instructions, and when a computer reads and executes the computer-readable instructions, the computer is enabled to perform the method in any one of the possible designs of the first aspect to the second aspect.
[0086] According to a ninth aspect, this application provides a computer program product. When a computer reads and executes the computer program product, the computer is enabled to perform the method in any one of the possible designs of the first aspect to the second aspect.
[0087] According to a tenth aspect, this application provides a system comprising at least one of an apparatus in (or at) an ED of the present application, or an apparatus in (or at) a network device of the present application.
[0088] According to an eleventh aspect, this application provides a method performed by a system comprising at least one of an apparatus in (or at) an ED of the present application, and an apparatus in (or at) a base station of the present application.
[0089] This application encompasses various embodiments, including not only method embodiments, but also other embodiments such as apparatus embodiments and embodiments related to non-transitory computer readable storage media. Embodiments may incorporate, individually or in combinations, the features disclosed herein.DESCRIPTION OF DRAWINGS
[0090] FIG. 1 is a schematic diagram of an application scenario according to this application;
[0091] FIG. 2 illustrates an example communications system 100;
[0092] FIG. 3 illustrates another example of an ED and a base station;
[0093] FIG. 4A illustrates units or modules in a device;
[0094] FIG. 4B illustrates an example of an apparatus 410;
[0095] FIG. 5 illustrates an example of LOS and NLOS;
[0096] FIG. 6 is an example of a channel model of a 4-by-4 MIMO system;
[0097] FIG. 7 illustrates a generic of time-domain MIMO representation;
[0098] FIG. 8 illustrates a generic diagram of MIMO representation including in frequency domain;
[0099] FIG. 9 illustrates a generic diagram of MIMO representation including in angular domain;
[0100] FIG. 10 illustrates a schematic diagram of spatial signatures;
[0101] FIG. 11 illustrates angular resolution in terms of number of antennas;
[0102] FIG. 12 illustrates 3D angle with respect to thew. r. t antenna panel;
[0103] FIG. 13 is a schematic flowchart of a method according to an embodiment of this application;
[0104] FIG. 14 illustrate an example of the reference signal (e.g., CSI-RS) in time-frequency domain according to this application;
[0105] FIG. 15 illustrates an example of LOS and one-bounce NLOS according to this application;
[0106] FIG. 16 illustrates a visualization of the projections of < Vmeasure (fk) , ABS (φ) > and < AED (θ) , Umeasure (fk) >according to this application;
[0107] FIG. 17 illustrates an example of a projection on an antenna’s range φazimuth from -π / 6 to 5π / 6 and φelevation from 0 to π / 2 according this application;
[0108] FIG. 18 illustrates multiple kinds of virtual planar screens according this application;
[0109] FIG. 19 illustrates a virtual planar screen data associated with a certain frequency according to this application;
[0110] FIG. 20 illustrates an example of building two virtual planar screens for two distance subcarriers according to this application;
[0111] FIG. 21 illustrates an example of a selection process according to this application;
[0112] FIG. 22 illustrates an example of an optimization process according to this application;
[0113] FIG. 23 illustrates an example of a selection process and an optimization process according to this application;
[0114] FIG. 24 illustrates an example of a selection process and a delay process estimation according to this application;
[0115] FIG. 25 illustrates an example of the first information according to this application;
[0116] FIG. 26 illustrates an example of the virtual planar screen data according to this application;
[0117] FIG. 27 illustrates an example of transmitted virtual planar data based on the location of the ED according to this application;
[0118] FIG. 28 illustrates an example of BS transmitting the virtual planar screen data to an ED according to this application;
[0119] FIG. 29 illustrates an example of the transmission of the second information and the third information according to this application;
[0120] FIG. 30 illustrates an example that the BS and the ED reconstruct the 4D RF map according to this application;
[0121] FIG. 31 illustrates an example of simulation results on 4D RF map reconstruction by BS receiving a lot of CSIs according to this application; and
[0122] FIGs. 32-33 are schematic block diagrams of possible devices according to the embodiments of this application.DESCRIPTION OF EMBODIMENTS
[0123] The following describes the technical solutions of the present application with reference to the accompanying drawings.
[0124] The technical solutions in embodiments of this application may be applied to multiple-input multiple-output (MIMO) technology. And the technical solutions in embodiments of this application may be applied to various communication systems, such as a fifth generation (5G) wireless communication system, a new ratio (NR) wireless communication system, a Long Term Evolution (LTE) system, an LTE frequency division duplex (FDD) system, an LTE time division duplex (TDD) system, a wireless local area network (WLAN) , a satellite communication system, or other evolving communication systems, such as a future generation wireless communication system.
[0125] For ease of understanding of the embodiments of this application, a communication system is shown in FIG. 1-FIG. 4 is used as an example to describe in detail a communication system to which the embodiments of this application are applicable.
[0126] Referring to FIG. 1, as an illustrative example without limitation, a simplified schematic illustration of a communication system is provided. The communication system 100 comprises a radio access network 120. The radio access network 120 may be a future generation radio access network, or a legacy (such as 5th generation (5G) , 4th generation (4G) , 3rd generation (3G) or 2nd generation (2G) ) radio access network. The RAN 120 may be a network using another radio access technology. In some implementations, radio access refers to a future generation air interface of standards which may comprise both terrestrial networks (TNs) and non-terrestrial networks (NTNs) , and more details will be described below. One or more communication electronic devices (ED) 110a, 110b, 110c, 110d, 110e, 110f, 110g, 110h, 110i, 110j (generically referred to as 110) may be interconnected to one another or connected to one or more network nodes (170a, 170b, generically referred to as 170) in the radio access network 120. A core network (CN) 130 may be a part of the communication system and may be dependent or independent of the radio access technology used in the communication system 100. The communication system 100 comprises a public switched telephone network (PSTN) 140, the internet 150, and other networks 160.
[0127] In general, the communication system 100 enables communication of multiple wireless or wired elements. The communication system 100 may provide content, such as voice, data, video, and / or text, via broadcast, multicast, groupcast, unicast, etc. The communication system 100 may operate by sharing resources, such as carrier spectrum bandwidth, among its constituent elements.
[0128] The communication system 100 may provide a wide range of communication services and applications including enhanced Mobile Broadband (eMBB) services, ultra-reliable low-latency communication (URLLC) services, massive machine type communication (mMTC) services, integrated sensing and communication (ISAC) , immersive communication, massive communication, Hyper reliable and low-latency communication, ubiquitous connectivity, integrated AI and communication, and other services that can be provided by a future generation communication system. The communication system 100 may provide other services and applications such as earth monitoring, remote sensing, passive sensing and positioning, navigation and tracking, autonomous delivery and mobility, etc.
[0129] The communication system 100 may include a terrestrial communication system (or network) and / or a non-terrestrial communication system (or network) . The communication system 100 may provide a high degree of availability and robustness through a joint operation of a terrestrial communication system and a non-terrestrial communication system. For example, integrating a non-terrestrial communication system (or components thereof) into a terrestrial communication system can result in a heterogeneous network comprising multiple layers. The heterogeneous network may achieve better overall performance through efficient multi-link joint operation, more flexible functionality sharing, and faster physical layer link switching between terrestrial networks and non-terrestrial networks. The terrestrial communication system and the non-terrestrial communication system could be considered sub-systems of the communication system 100.
[0130] FIG. 2 illustrates an example communication system 100. In general, the communication system 100 enables multiple wireless or wired elements to communicate data and other content. The purpose of the communication system 100 may be to provide content, such as voice, data, video, and / or text, via broadcast, multicast, groupcast, unicast, etc. The communication system 100 may operate by sharing resources, such as carrier spectrum bandwidth, between its constituent elements. The communication system 100 may include a terrestrial communication system and / or a non-terrestrial communication system. The communication system 100 may provide a wide range of communication services and applications (such as earth monitoring, remote sensing, passive sensing and positioning, navigation and tracking, autonomous delivery, and mobility, etc. ) . The communication system 100 may provide a high degree of availability and robustness through a joint operation of a terrestrial communication system and a non-terrestrial communication system. For example, integrating a non-terrestrial communication system (or components thereof) into a terrestrial communication system can result in what may be considered a heterogeneous network comprising multiple layers. Compared to conventional communication networks, the heterogeneous network may achieve better overall performance through efficient multi-link joint operation, more flexible functionality sharing, and faster physical layer link switching between terrestrial networks and non-terrestrial networks.
[0131] The terrestrial communication system and the non-terrestrial communication system could be considered sub-systems of the communication system. In the example shown in FIG. 2, the communication system 100 includes electronic devices (ED) 110a, 110b, 110c, 110d (generically referred to as ED 110) , radio access networks (RANs) 120a, 120b, a non-terrestrial communication network 120c, a core network 130, a public switched telephone network (PSTN) 140, the Internet 150, and other networks 160. The RANs 120a, 120b include respective base stations (BSs) 170a, 170b, which may be generically referred to as terrestrial transmit and receive points (T-TRPs) 170a, 170b. The non-terrestrial communication network 120c includes an access node 172, which may be generically referred to as a non-terrestrial transmit and receive point (NT-TRP) 172.
[0132] Any ED 110 may be alternatively or additionally configured to interface, access, or communicate with any T-TRP 170a, 170b and NT-TRP 172, the Internet 150, the core network 130, the PSTN 140, the other networks 160, or any combination of the preceding. In some examples, ED 110a may communicate an uplink and / or downlink transmission over a terrestrial air interface 190a with T-TRP 170a. In some examples, the EDs 110a, 110b, 110c, and 110d may also communicate directly with one another via one or more sidelink air interfaces 190b. In some examples, ED 110d may communicate an uplink and / or downlink transmission over a non-terrestrial air interface 190c with NT-TRP 172.
[0133] The air interfaces 190a and 190b may use similar communication technology, such as any suitable radio access technology. For example, the communication system 100 may implement one or more channel access methods, such as code division multiple access (CDMA) , space division multiple access (SDMA) , time division multiple access (TDMA) , frequency division multiple access (FDMA) , orthogonal FDMA (OFDMA) , or single-carrier FDMA (SC-FDMA, also known as discrete Fourier transform spread OFDMA, DFT-s-OFDMA) in the air interfaces 190a and 190b. The air interfaces 190a and 190b may utilize other higher dimension signal spaces, which may involve a combination of orthogonal and / or non-orthogonal dimensions.
[0134] The non-terrestrial air interface 190c can enable communication between the ED 110d and one or multiple NT-TRPs 172 via a wireless link or simply a link. For some examples, the link is a dedicated connection for unicast transmission, a connection for broadcast transmission, or a connection between a group of EDs 110 and one or multiple NT-TRPs 172 for multicast transmission.
[0135] The RANs 120a and 120b are in communication with the core network 130 to provide the EDs 110a 110b, and 110c with various services such as voice, data, and other services. The RANs 120a and 120b and / or the core network 130 may be in direct or indirect communication with one or more other RANs (not shown) , which may or may not be directly served by core network 130, and may or may not employ the same radio access technology as RAN 120a, RAN 120b or both. The core network 130 may also serve as a gateway access between (i) the RANs 120a and 120b or EDs 110a 110b, and 110c or both, and (ii) other networks (such as the PSTN 140, the Internet 150, and the other networks 160) . In addition, some or all of the EDs 110a 110b, and 110c may include functionality for communicating with different wireless networks over different wireless links using different wireless technologies and / or protocols. Instead of wireless communication (or in addition thereto) , the EDs 110a 110b, and 110c may communicate via wired communication channels to a service provider or switch (not shown) , and to the Internet 150. PSTN 140 may include circuit switched telephone networks for providing plain old telephone service (POTS) . Internet 150 may include a network of computers and subnets (intranets) or both, and incorporate protocols, such as Internet Protocol (IP) , Transmission Control Protocol (TCP) , User Datagram Protocol (UDP) . EDs 110a 110b, and 110c may be multimode devices capable of operation according to multiple radio access technologies, and incorporate multiple transceivers necessary to support such.
[0136] Any base station may be a single element, as shown, or multiple elements, distributed in the corresponding RAN, or otherwise. In some implementations, a plurality of RAN nodes coordinate to assist the ED 110 in implementing radio access, and different RAN nodes separately implement different functions of the base station. For example, the RAN node may be a central unit (CU) , a distributed unit (DU) , a CU-control plane (CP) , a CU-user plane (UP) , or a radio unit (RU) , etc. The CU and the DU may be separately deployed, or may be included in a same element (i.e., a baseband unit (BBU) ) . The RU may be included in a radio frequency device or a radio frequency unit (i.e., a remote radio unit (RRU) , an active antenna unit (AAU) , or a remote radio head (RRH) ) . In different systems, the CU (or the CU-CP and the CU-UP) , the DU, or the RU may also have different names, but a person skilled in the art may understand meanings thereof. For example, in an open radio access network (ORAN) system, a CU may also be referred to as an open CU (O-CU) , a DU may also be referred to as an open DU (O-DU) , and a CU-CP may also be referred to as an open CU-CP (O-CU-CP) . The CU-UP may also be referred to as an open CU-UP (O-CU-UP) , and the RU may also be referred to as an open RU (O-RU) . Any one of the CU (or the CU-CP, the CU-UP) , the DU, and the RU may be implemented by using a software module, a hardware module, or a combination of a software module and a hardware module.
[0137] Further, communication (s) between different devices / apparatuses in various embodiments of this application may refer to direct communication between different devices / apparatuses (that is, no forwarding is required by another device / apparatuses) , or may refer to communication (s) between different devices / apparatuses via another device / apparatus (that is, forwarding is required by another device / apparatus) . Alternatively, such communication (s) may refer to that a functional unit inside the device / apparatus uses another functional unit in the device / apparatus to communicate with another device / apparatus. In other words, "sending (or transmitting) information to... (an ED or a base station) " in this application may be understood as that a destination endpoint of the information is an ED or a base station. It may include sending / transmitting information directly or indirectly to an ED or a base station. Similarly, "receiving information from... (an ED or a base station) " may be understood as that a source endpoint of the information is an ED or a base station, and may include directly or indirectly receiving information from an ED or a base station. Necessary processing such as format conversion, digital-to-analog conversion, amplification, and filtering may be performed on the information between the source endpoint that sends the information and the destination endpoint. However, the destination endpoint may understand valid information from the source endpoint. Similar descriptions in this application may be understood similarly. Details are not described herein again. In the present disclosure, the terms "send" and "transmit" may be used interchangeably in embodiments of this application.
[0138] FIG. 3 illustrates another example of an ED 110 and a base station 170a, 170b and / or 170c. The ED 110 is used to connect persons, objects, machines, etc. The ED 110 may be widely used in various scenarios including, for example, cellular communications, device-to-device (D2D) , vehicle to everything (V2X) , peer-to-peer (P2P) , machine-to-machine (M2M) , machine-type communications (MTC) , internet of things (IoT) , virtual reality (VR) , augmented reality (AR) , mixed reality (MR) , metaverse, digital twin, industrial control, self-driving, remote medical, smart grid, smart furniture, smart office, smart wearable, smart transportation, smart city, drones, robots, remote sensing, passive sensing, positioning, navigation and tracking, autonomous delivery and mobility, etc.
[0139] Each ED 110 represents any suitable end user device for wireless operation and may include such devices (or may be referred to) as a user equipment / device (UE) , a wireless transmit / receive unit (WTRU) , a mobile station, a fixed or mobile subscriber unit, a cellular telephone, a station (STA) , a machine type communication (MTC) device, a personal digital assistant (PDA) , a smartphone, a laptop, a computer, a tablet, a wireless sensor, a consumer electronics device, a smart book, a vehicle, a car, a truck, a bus, a train, or an IoT device, wearable devices (such as a watch, a pair of glasses, head mounted equipment, etc. ) , an industrial device, or an apparatus in (e.g. communication module, modem, or chip) or comprising the forgoing devices, among other possibilities. Future generation EDs 110 may be referred to using other terms. The base station 170a and 170b is a T-TRP and will hereafter be referred to as T-TRP 170. Also shown in FIG. 3, a NT-TRP will hereafter be referred to as NT-TRP 172. Each ED 110 connected to T-TRP 170 and / or NT-TRP 172 can be dynamically or semi-statically turned-on (i.e., established, activated, or enabled) , turned-off (i.e., released, deactivated, or disabled) and / or configured in response to one of more of: connection availability and connection necessity.
[0140] The ED 110 includes a transmitter 201 and a receiver 203 coupled to one or more antennas 204. Only one antenna 204 is illustrated to avoid congestion in the drawing. One, some, or all of the antennas 204 may alternatively be panels. The transmitter 201 and the receiver 203 may be integrated, e.g. as a transceiver. The transceiver is configured to modulate data or other content for transmission by at least one antenna 204 or network interface controller (NIC) . The transceiver is also configured to demodulate data or other content received by the at least one antenna 204. Each transceiver includes any suitable structure for generating signals for wireless or wired transmission and / or processing signals received wirelessly or by wire. Each antenna 204 includes any suitable structure for transmitting and / or receiving wireless or wired signals.
[0141] The ED 110 includes at least one memory 208. The memory 208 stores instructions and data used, generated, or collected by the ED 110. For example, the memory 208 could store software instructions or modules configured to implement some or all of the functionality and / or embodiments described herein and that are executed by one or more processing unit (s) (e.g., a processor 210) . Each memory 208 includes any suitable volatile and / or non-volatile storage and retrieval device (s) . Any suitable type of memory may be used, such as random access memory (RAM) , read only memory (ROM) , hard disk, optical disc, subscriber identity module (SIM) card, memory stick, secure digital (SD) memory card, on-processor cache, and the like.
[0142] The ED 110 may further include one or more input / output devices (not shown) or interfaces (such as a wired interface to the Internet 150 in FIG. 1) . The input / output devices or interfaces permit interaction with a user or other devices in the network. Each input / output device or interface includes any suitable structure for providing information to or receiving information from a user, and / or for network interface communications. Suitable structures include, for example, a speaker, microphone, keypad, keyboard, display, touch screen, etc.
[0143] The ED 110 includes the processor 210 for performing operations including those operations related to preparing a transmission for uplink transmission to the NT-TRP 172 and / or the T-TRP 170; those operations related to processing downlink transmissions received from the NT-TRP 172 and / or the T-TRP 170; and those operations related to processing sidelink transmission to and from another ED 110. Processing operations related to preparing a transmission for uplink transmission may include operations such as encoding, modulating, transmit beamforming, and generating symbols for transmission. Processing operations related to processing downlink transmissions may include operations such as receive beamforming, demodulating and decoding received symbols. Depending upon the embodiment, a downlink transmission may be received by the receiver 203, possibly using receive beamforming, and the processor 210 may extract signaling from the downlink transmission (e.g. by detecting and / or decoding the signaling) . An example of signaling may be a reference signal transmitted by the NT-TRP 172 and / or by the T-TRP 170. In some embodiments, the processor 210 implements the transmit beamforming and / or the receive beamforming based on the indication of beam direction, e.g. beam angle information (BAI) , received from the T-TRP 170. In some embodiments, the processor 210 may perform operations relating to network access (e.g. initial access) and / or downlink synchronization, such as operations relating to detecting a synchronization sequence, decoding and obtaining the system information, etc. In some embodiments, the processor 210 may perform channel estimation, e.g. using a reference signal received from the NT-TRP 172 and / or from the T-TRP 170.
[0144] Although not illustrated, the processor 210 may form part of the transmitter 201 and / or part of the receiver 203. Although not illustrated, the memory 208 may form part of the processor 210.
[0145] The processor 210, the processing components of the transmitter 201, and the processing components of the receiver 203 may each be implemented by the same or different one or more processors that are configured to execute instructions stored in a memory (e.g. in the memory 208) . Alternatively, some or all of the processor 210, the processing components of the transmitter 201, and the processing components of the receiver 203 may each be implemented using dedicated circuitry, such as a programmed field-programmable gate array (FPGA) , an application-specific integrated circuit (ASIC) , or a hardware accelerator such as a graphics processing unit (GPU) or an artificial intelligence (AI) accelerator.
[0146] The T-TRP 170 may be known by other names in some implementations, such as a base station, a base transceiver station (BTS) , a radio base station, a network node, a network device, a device on the network side, a transmit / receive node, a Node B, an evolved NodeB (eNodeB or eNB) , a Home eNodeB, a next Generation NodeB (gNB) , a transmission point (TP) , a site controller, an access point (AP) , a wireless router, a relay station, a terrestrial node, a terrestrial network device, a terrestrial base station, a base band unit (BBU) , a remote radio unit (RRU) , an active antenna unit (AAU) , a remote radio head (RRH) , a central unit (CU) , a distributed unit (DU) , a positioning node, among other possibilities. The T-TRP 170 may be a macro BS, a pico BS, a relay node, a donor node, or the like, or combinations thereof. The T-TRP 170 may refer to the forgoing devices or refer to apparatus (e.g. a communication module, a modem, or a chip) in the forgoing devices.
[0147] In some embodiments, the parts of the T-TRP 170 may be distributed. For example, some of the modules of the T-TRP 170 may be located remote from the equipment that houses the antennas 256 for the T-TRP 170, and may be coupled to the equipment that houses the antennas 256 over a communication link (not shown) sometimes known as front haul, such as common public radio interface (CPRI) . Therefore, in some embodiments, the term T-TRP 170 may also refer to modules on the network side that perform processing operations, such as determining the location of the ED 110, resource allocation (scheduling) , message generation, and encoding / decoding, and that are not necessarily part of the equipment that houses the antennas 256 of the T-TRP 170. The modules may also be coupled to other T-TRPs. In some embodiments, the T-TRP 170 may actually be a plurality of T-TRPs that are operating together to serve the ED 110, e.g. through the use of coordinated multipoint transmissions.
[0148] The T-TRP 170 includes at least one transmitter 252 and at least one receiver 254 coupled to one or more antennas 256. Only one antenna 256 is illustrated to avoid congestion in the drawing. One, some, or all of the antennas 256 may alternatively be panels. The transmitter 252 and the receiver 254 may be integrated as a transceiver. The T-TRP 170 further includes a processor 260 for performing operations including those related to: preparing a transmission for downlink transmission to the ED 110, processing an uplink transmission received from the ED 110, preparing a transmission for backhaul transmission to the NT-TRP 172, and processing a transmission received over backhaul from the NT-TRP 172. Processing operations related to preparing a transmission for downlink or backhaul transmission may include operations such as encoding, modulating, precoding (e.g. multiple input multiple output (MIMO) precoding) , transmit beamforming, and generating symbols for transmission. Processing operations related to processing received transmissions in the uplink or over backhaul may include operations such as receive beamforming, demodulating received symbols, and decoding received symbols. The processor 260 may also perform operations relating to network access (e.g. initial access) and / or downlink synchronization, such as generating the content of synchronization signal blocks (SSBs) , generating the system information, etc. In some embodiments, the processor 260 also generates an indication of beam direction, e.g. BAI, which may be scheduled for transmission by a scheduler 253. The processor 260 performs other network-side processing operations described herein, such as determining the location of the ED 110, determining where to deploy the NT-TRP 172, etc. In some embodiments, the processor 260 may generate signaling, e.g. to configure one or more parameters of the ED 110 and / or one or more parameters of the NT-TRP 172. Any signaling generated by the processor 260 is sent by the transmitter 252. Note that “signaling” , as used herein, may alternatively be called control signaling. Signaling may be transmitted in a physical layer control channel, e.g. a physical downlink control channel (PDCCH) , in which case the signaling may be known as dynamic signaling. Signaling transmitted in a downlink physical layer control channel may be known as Downlink Control Information (DCI) . Siganling transmitted in an uplink physical layer control channel may be known as Uplink Control Information (UCI) . Signaling transmitted in a sidelink physical layer control channel may be known as Sidelink Control Information (SCI) . Signaling may be included in a higher-layer (e.g., higher than physical layer) packet transmitted in a physical layer data channel, e.g. in a physical downlink shared channel (PDSCH) , in which case the signaling may be known as higher-layer signaling, static signaling, or semi-static signaling. Higher-layer signaling may also refer to Radio Resource Control (RRC) protocol signaling or Media Access Control –Control Element (MAC-CE) signaling.
[0149] The scheduler 253 may be coupled to the processor 260. The scheduler 253 may be included within or operated separately from the T-TRP 170. The scheduler 253 may schedule uplink, downlink, sidelink, and / or backhaul transmissions, including issuing scheduling grants and / or configuring scheduling-free (e.g., “configured grant” ) resources. The T-TRP 170 further includes a memory 258 for storing information and data. The memory 258 stores instructions and data used, generated, or collected by the T-TRP 170. For example, the memory 258 could store software instructions or modules configured to implement some or all of the functionality and / or embodiments described herein and that are executed by the processor 260.
[0150] Although not illustrated, the processor 260 may form part of the transmitter 252 and / or part of the receiver 254. Also, although not illustrated, the processor 260 may implement the scheduler 253. Although not illustrated, the memory 258 may form part of the processor 260.
[0151] The processor 260, the scheduler 253, the processing components of the transmitter 252, and the processing components of the receiver 254 may each be implemented by the same or different one or more processors that are configured to execute instructions stored in a memory, e.g. in the memory 258. Alternatively, some or all of the processor 260, the scheduler 253, the processing components of the transmitter 252, and the processing components of the receiver 254 may be implemented using dedicated circuitry, such as a programmed FPGA, a hardware accelerator (e.g., a GPU or AI accelerator) , or an ASIC.
[0152] Although the NT-TRP 172 is illustrated as a drone only as an example, the NT-TRP 172 may be implemented in any suitable non-terrestrial form, such as satellites and high altitude platforms, including international mobile telecommunication base stations and unmanned aerial vehicles, for example. Also, the NT-TRP 172 may be known by other names in some implementations, such as a non-terrestrial node, a non-terrestrial network device, or a non-terrestrial base station. The NT-TRP 172 includes a transmitter 272 and a receiver 274 coupled to one or more antennas 280. Only one antenna 280 is illustrated to avoid congestion in the drawing. One, some, or all of the antennas may alternatively be panels. The transmitter 272 and the receiver 274 may be integrated as a transceiver. The NT-TRP 172 further includes a processor 276 for performing operations including those related to: preparing a transmission for downlink transmission to the ED 110, processing an uplink transmission received from the ED 110, preparing a transmission for backhaul transmission to T-TRP 170, and processing a transmission received over backhaul from the T-TRP 170. Processing operations related to preparing a transmission for downlink or backhaul transmission may include operations such as encoding, modulating, precoding (e.g. MIMO precoding) , transmit beamforming, and generating symbols for transmission. Processing operations related to processing received transmissions in the uplink or over backhaul may include operations such as receive beamforming, demodulating received symbols, and decoding received symbols. In some embodiments, the processor 276 implements the transmit beamforming and / or receive beamforming based on beam direction information (e.g. BAI) received from the T-TRP 170. In some embodiments, the processor 276 may generate signaling, e.g. to configure one or more parameters of the ED 110. In some embodiments, the NT-TRP 172 implements physical layer processing, but does not implement higher layer functions such as functions at the medium access control (MAC) or radio link control (RLC) layer. As this is only an example, more generally, the NT-TRP 172 may implement higher layer functions in addition to physical layer processing.
[0153] The NT-TRP 172 further includes a memory 278 for storing information and data. Although not illustrated, the processor 276 may form part of the transmitter 272 and / or part of the receiver 274. Although not illustrated, the memory 278 may form part of the processor 276.
[0154] The processor 276, the processing components of the transmitter 272, and the processing components of the receiver 274 may each be implemented by the same or different one or more processors that are configured to execute instructions stored in a memory, e.g. in the memory 278. Alternatively, some or all of the processor 276, the processing components of the transmitter 272, and the processing components of the receiver 274 may be implemented using dedicated circuitry, such as a programmed FPGA, a hardware accelerator (e.g., a GPU or AI accelerator) , or an ASIC. In some embodiments, the NT-TRP 172 may actually be a plurality of NT-TRPs that are operating together to serve the ED 110, e.g. through coordinated multipoint transmissions.
[0155] The T-TRP 170, the NT-TRP 172, and / or the ED 110 may include other components, but these have been omitted for the sake of clarity.
[0156] One or more steps of the embodiment methods provided herein may be performed by corresponding units or modules, according to FIG. 4A. FIG. 4A illustrates units or modules in a device, such as in the ED 110, in the T-TRP 170, or in the NT-TRP 172. For example, a signal may be transmitted by a transmitting unit or by a transmitting module. A signal may be received by a receiving unit or by a receiving module. A signal may be processed by a processing unit or a processing module. Other steps may be performed by an artificial intelligence (AI) or machine learning (ML) module. The respective units or modules may be implemented using hardware, one or more components or devices that execute software, or a combination thereof. For instance, one or more of the units or modules may be a circuit such as an integrated circuit. Examples of an integrated circuit include a programmed FPGA, a GPU, or an ASIC. For instance, one or more of the units or modules may be logical such as a logical function performed by a circuit, by a portion of an integrated circuit, or by software instructions executed by a processor. It will be appreciated that where the modules are implemented using software for execution by a processor for example, the modules may be retrieved by a processor, in whole or part as needed, individually or together for processing, in single or multiple instances, and that the modules themselves may include instructions for further deployment and instantiation.
[0157] One or more steps of the embodiment methods provided herein may be performed by corresponding apparatus, according to FIG. 4B.
[0158] The apparatus 410 may be a communication device or an apparatus implemented in a communication device such as ED 110 or TRPs 170a-170b, 172. For example, the apparatus implemented in a communication device may be an integrated circuit, which in some contexts may be known by other colloquial names, such as chip, modem, modem chip, baseband chip, or baseband processor. In some implementations, one or more integrated circuits can be packaged into a system-on-chip, a system-in-package, or a multi-chip module. The apparatus may comprise one or more integrated circuits or comprise one or more integrated circuits and other discrete components. In some implementations, the apparatus 410 may be a module in ED 110. In some implementations, the apparatus 410 may be a module in one of TRPs 170a-170b, 172.
[0159] In an example, the apparatus 410 may include one or more processors / processor cores 411, and an interface circuit 412. The apparatus 410 may further include a memory 413. The one or more processors / processor cores 411 are configured to process signals and execute one or more communication protocols. The memory 413 is configured to store at least a part of corresponding computer program instructions and / or data. In an example, the one or more processors (or processor cores) 411 execute the computer program instructions stored in the memory 413 to implement related operations (for example, inputting, outputting, receiving, and transmitting) in the method embodiments disclosed herein. In some implementations, the memory 413 being configured to store the corresponding computer program instructions and / or data may mean that the memory 413 is configured to store all of the corresponding computer program instructions and / or data for execution by the one or more processors / processor cores 411. In some implementations, the memory 413 being configured to store the corresponding computer program instructions and / or data may mean that the memory 413 is configured to store a part of the corresponding computer program instructions and / or data. For example, the part of the corresponding computer program instructions and / or data may include computer program instructions and / or data that need to be currently executed by the one or more processors / processor cores 411. Thus, the memory 413 may store different parts of computer program instructions and / or data for a plurality times for the one or more processors (or processor cores) 411 to perform related operations in the method embodiments disclosed herein. As a communication interface, the interface circuit 412 is configured to implement communication with another component. For example, the interface circuit 412 may communicate a signal with other apparatus / system such as a radio frequency processing apparatus, or processor system. Optionally, to reduce a load of the one or more processors (or processor cores) , a baseband signal processing circuit 414 may be also disposed to implement processing of at least a part of baseband signals, including signal demodulation, modulation, encoding, decoding, or the like.
[0160] Apparatus 410 may be processor 210 (or 260) in ED 110 (or T-TRP 170, NT-TRP 172) , in some scenarios, or included in processor 210 (or 260) in ED 110 (or T-TRP 170, NT-TRP 172) in some scenarios. Apparatus 410 may be or include a baseband chip. In some implementations, the apparatus 410 may be independently packaged into a chip. In some implementations, the ED 110 (or T-TRP 170, NT-TRP 172) includes different types of chips. The apparatus 410 may be packaged into a processor chip (for example, an SoC chip or an SIP chip) with the different types of chips. In some implementations, the apparatus 410 may be packaged into a chip with some or all of circuits of a radio frequency processing system that may further included in the ED 110 (or T-TRP 170, NT-TRP 172) .
[0161] Additional details regarding the EDs 110, the T-TRP 170, and the NT-TRP 172 are known to those of skill in the art. As such, these details are omitted here.
[0162] Before introducing the communication method provided by this application, additional concepts and terms are defined to ensure a clearer understanding.
[0163] 1) radio frequency (RF) map: An RF map in this context is a detailed representation of the radio environment, for example, showing signal strengths, interference, and other pertinent information over an area.
[0164] A 4-dimension (4D) RF map comprises a traditional 3-dimension (3D) environment reconstruction combined with radio path loss information mapped onto the surfaces of buildings or other reflective objects within the environment. The 3D environment is a 3D space constructed from the three dimensions of length, width and height. The 4D RF map, which contains the RF characteristics, can be used for various parameter setting (e.g., beamforming, power parameter setting, and etc. ) .
[0165] 2) line-of-sight (LOS) and non-line-of-sight (NLOS) :
[0166] FIG. 5 illustrates an example of LOS and NLOS. LOS and NLOS are two kinds of communication scenarios. For example, a transmitter transmits a wireless signal, if the wireless signal arrives at a receiver without an obstacle, the path (e.g., path “a” ) can be referred to as the LOS path. If the wireless signal arrives at the receiver through one or more reflections of obstacle (s) (e.g., the ground, buildings, etc. ) , the path (e.g., path “b” and “c” ) can be referred to as NLOS path. In addition, M-times reflections can be referred to as M-bounces NLOS, where M is a positive integer. As shown in FIG. 5, path “b” is a one-bounce NLOS path, which passes 1-time reflection of obstacle#1. Path “c” is a 2-bounce NLOS path, which passes 2 times reflections of obstacle#1 and obstacle#2.
[0167] 3) MIMO
[0168] FIG. 6 is an example of a channel model of a 4-by-4 MIMO system. A transmitter is connected to four TX antennas, x1 to x4, a receiver is connected to four RX antennas, y1 to y4, and a transmission channel may be formed between each TX antenna and each RX antenna. For example, an RF signal transmitted through x1 may be received by y2 through channel h21. The RF signal transmitted through x3 may be received by y1 through channel h13.
[0169] Multiple-input multiple-output (MIMO) is a wireless communication technique that uses multiple antennas at both the transmitter and receiver ends to improve communication performance.
[0170] MIMO technology has been widely adopted in modern wireless standards like IEEE 802.11n (Wi-Fi) , 3G, 4G LTE, and 5G NR cellular networks.
[0171] In conventional MIMO systems, multiple antennas are used at the transmitter and receiver to increase the capacity and performance of a radio link through spatial multiplexing and diversity techniques. Spatial multiplexing allows multiple parallel data streams to be transmitted over the same time / frequency resources, effectively increasing the data throughput. Diversity techniques like transmit / receive diversity combine signals from multiple antennas to improve the overall signal quality and reliability.
[0172] As the number of antennas increases, the MIMO system is able to further enhance capacity and performance through the creation of highly directional beams. This beamforming capability allows the transmitted signals to be focused toward the intended receivers while minimizing interference in other directions. Reciprocally, it enables receivers to combine signals arriving from the direction of intended transmitters while suppressing interference from other directions.
[0173] Massive MIMO, involving operation with a few hundred antennas or more at the base station (BS) , is a key technology for 5G networks. By scaling up conventional MIMO, massive MIMO can coherently combine a large number of antennas to focus signals into ever-sharper beams towards each user. This provides major gains in capacity, radiated energy efficiency, and resilience against interference and jamming.
[0174] Ultra-massive MIMO systems take this scaling even further, with base stations deploying thousands or tens of thousands of antennas. The extremely high spatial resolution enabled allows ultra-massive MIMO to deliver highly directive signal transmission / reception and precise 3D beamforming. This makes ultra-massive MIMO a promising technology for beyond 5G and future (or advanced) wireless networks.
[0175] 3.1) MIMO represented in the time domain
[0176] FIG. 7 illustrates a generic of time-domain MIMO representation.
[0177] For a MIMO channel with NTx antennas and NRx antennas in the time domain, the input-output relationship can be represented using a convolution operation between the transmitted signal vector and the time-varying channel impulse response: y (t) = x (t) *h (t) , where: y (t) is the NRx × 1 vector of received signals at the receive antennas, x (t) is the NTx × 1 vector of transmitted signals from the transmit antennas, h (t) is the NRx × NTx matrix channel impulse response, and *denotes the convolution operation. The detailed time-domain model allows for precise simulation and analysis of signal behavior, used for optimizing system performance and enhancing predictive modeling capabilities. The time-domain channel impulse response h(t) captures how the transmitted signal vector x (t) propagates through the multipath environment and arrives at the receive antennas with different delays, attenuations, and phase shifts, which are represented by the time-varying matrix coefficients in h(t) .
[0178] 3.2) MIMO represented in the frequency domain
[0179] FIG. 8 illustrates a generic diagram of MIMO representation including in frequency domain.
[0180] By taking the Fourier transform of both sides, we can express the input-output relationship in the frequency domain as a matrix multiplication: Y (f) = X (f) H (f) , where Y (f) and X (f) are the frequency domain representations of the received and transmitted signal vectors respectively, and H (f) is the frequency response of the MIMO channel. It's crucial to note that H (f) is a frequency-dependent function. This matrix multiplication framework is critical for designing filters and equalizers in digital communication systems, allowing for tailored adjustments in response to varying channel conditions. The frequency-domain MIMO channel matrix H (f) varies across different frequency points or subcarriers. In orthogonal frequency division multiplexing (OFDM) systems, the wideband channel is divided into multiple narrowband subcarriers, and each subcarrier experiences a different frequency-flat MIMO channel characterized by its own H (f) matrix at that subcarrier frequency.
[0181] 3.3) MIMO represented in the spatial domain
[0182] FIG. 9 illustrates a generic diagram of MIMO representation in the angular domain.
[0183] This ability to characterize the frequency-selective nature of wideband MIMO channels as parallel frequency-flat spatial MIMO channels, one per subcarrier, is a key advantage of OFDM that makes it well-suited for MIMO communications. In MIMO-OFDM systems, the complete frequency-domain MIMO channel for a single OFDM symbol, [H (f1) , H (f2) , H (f3) , …. H (fNsc) ] , can be represented as a three-dimensional tensor of size NTx × NRx × Nsc, where NTx is the number of transmit antennas, NRx is the number of receive antennas, and Nsc is the number of subcarriers. This tensorial representation greatly enhances the analysis and processing capabilities, allowing for more efficient implementation of advanced communication techniques. Each slice of this tensor corresponds to the H (fk) matrix for a given subcarrier frequency. In MIMO-OFDM systems, the frequency-domain MIMO channel representation is particularly beneficial for techniques like precoding, beamforming, and equalization, optimizing the use of the spectrum and improving system reliability and throughput.
[0184] MIMO systems exploit the spatial dimension by utilizing multiple antennas at the transmitter and receiver. While the time-domain representation captures the multipath propagation characteristics of the channel, the angular domain provides valuable insights into the spatial properties of the MIMO channel. In the angular domain, the MIMO channel is characterized by the angles of arrival (AoAs) and angles of departure (AoDs) of the multipath components. This angular information is used for advanced beamforming and spatial filtering techniques, which aim to optimize signal clarity and reduce interference. Each multipath component corresponds to a specific AoA and AoD, representing the direction from which the signal arrives at the receiver and the direction from which it departs the transmitter, respectively. An angular domain channel matrix, denoted as H (θ, φ) , captures the complex gain of each multipath component as a function of the AoA θ and AoD φ, by effectively mapping the spatial signatures of the signal paths.
[0185] To convert the frequency-domain MIMO channel representation to the angular domain, we can apply a spatial Fourier transform to the channel matrices at each subcarrier frequency. For each subcarrier frequency fk, we apply a spatial Fourier transform to the corresponding MIMO channel matrix H (fk) to obtain the angular domain representation H (θ, φ, fk) , where θ represents the angles of arrival (AoAs) and φ represents the angles of departure (AoDs) . The spatial Fourier transform can be expressed as: H (θ, φ, fk) = Ar (θ) H H (fk) At (φ) where: Ar (θ) is the NRx × L receive array response matrix, with L being the number of angles of arrival, At (φ) is the NTx × P transmit array response matrix, with P being the number of angles of departure, (. ) H denotes the Hermitian (conjugate transpose) operation. The array response matrices Ar (θ) and At (φ) are designed based on the geometry and characteristics of the receive and transmit antenna arrays, respectively, allowing precise spatial characterization of signal paths.
[0186] When performing singular value decomposition (SVD) on the frequency-domain MIMO channel matrix H (fk) for a given subcarrier frequency fk, we obtain H (fk) = U (fk) Σ (fk) V (fk) H, where U (fk) and V (fk) are the left and right singular matrices, respectively, and Σ (fk) is the diagonal singular value matrix. The right singular vectors in V (fk) are commonly used as the precoding matrix for beamforming in the downlink. This precoding matrix can be projected to the angular domain representation to gain insights into its spatial properties Substituting the SVD of H (fk) , we get: H (θ, φ, fk) = Ar (θ) H U (fk) Σ (fk) V (fk) H At (φ) .
[0187] FIG. 10 illustrates a schematic diagram of spatial signatures.
[0188] To project the precoding matrix V (fk) to the angular domain, we can calculate the (inner) product V (fk) H At (φ) = < V (fk) , At (φ) >, which represents the precoding vectors projected onto the transmit array response vectors corresponding to different angles of departure φ.
[0189] The orthogonality of the columns (V (fk) = [v1 (fk) v2 (fk) …vr (fk) ] and (vi) Hvj=0, for all i≠j) in V (fk) ensures that the precoding spatial streams are orthogonal to each other in the spatial domain. This orthogonality is used for effective spatial multiplexing, as it minimizes interference between the spatial streams at the receiver, enhancing the overall efficiency and reliability of the communication system.
[0190] As illustrated in FIG. 10, v1 (fk) , v2 (fk) and v3 (fk) are orthogonal in the spatial domain. < v2 (fk) , At (φ1) > represents the precoding vector v2 (fk) projected onto the transmit array response vector At (φ1) corresponding to the angle of departure φ1. < v2 (fk) , At (φ2) > represents the precoding vector v2 (fk) projected onto the transmit array response vector At (φ2) corresponding to the angle of departure φ2.
[0191] The columns [<v1 (fk) , At (φ) > <v2 (fk) , At (φ) > …<vr (fk) , At (φ) >] represent the r spatial signatures or beamforming patterns of the precoding spatial streams in the angular domain. These spatial signatures can be analyzed to understand how the transmit weight (power) is distributed across different angles of departure, enabling efficient spatial processing techniques. But, it's important to note that the accuracy of this analysis depends on the accuracy of the array response matrix At (φ) .
[0192] As aforementioned, angular resolution is related to the number of antennas. For illustrative purposes, a beamforming pattern when the number of antennas is equal to 16, and a beamforming pattern when the number of antennas is equal to 256 are given in FIG. 11.
[0193] FIG. 11 illustrates angular resolution in terms of number of antennas, emphasizing how increasing antenna counts improves the system's capability to distinguish between signals from closely spaced angles.
[0194] In the downlink of a future (advanced) ultra-massive MIMO system operating in the centimeter-wave (cmWave) band, the BS can be equipped with up to 1024 antenna elements, while an ED might have 16. Given the significant distance between the ED and the BS relative to the wavelength (λ) , incoming signals are effectively from nearly distinct points in space. Due to the large distance between the ED and the BS compared to the wavelength (λ) , incoming signals can be considered to originate from nearly distinct points in space. To further enhance orthogonality between received signals, modern MIMO systems often utilize Uniform Rectangular Arrays (URA) . This substantial number of antenna ports at the BS not only enhances signal clarity but also significantly increases the spatial resolution for angles of departure (AoD) φ in the downlink (DL) , crucial for precise directional control and interference management. This large number of antenna ports at the BS translates to a higher spatial resolution for angles of departure (AoD) φ in the downlink (DL) .
[0195] In the following discussion, as we will focus on the downlink, we denote NBS as NTx and NED as NRx.
[0196] Notably, the expression of AoD (or AoA) is related to the choice of reference coordinates system. For example, the AoD (or AoA) may be expressed by a reference coordinates system with respect to the transmit antenna panel (or receive antenna panel) (referred to as a local coordinates system hereinafter) and / or a reference coordinates system with respect to the ground plane (referred to as a global coordinates system hereinafter) . For ease of understanding implementations of this application, an AoD represented by the local coordinates system and the global coordinates system is illustrated in FIG. 12.
[0197] FIG. 12 illustrates the 3D angle with respect to the antenna panel, the 3D angle of the antenna panel with respect to the ground plane, and the 3D angle with respect to the ground plane.
[0198] The transmit (BS) array response matrix ABS (φ) models the response of the transmit antenna array (BS) to signals departing from different 3D angles, denoted by φ. The angle φ is defined as a pair of azimuth and elevation angles, φ: = (φazimuth, φelevation) . BS antenna panels may be well-designed URAs, and the pair (φazimuth, φelevation) represents the 3D angle of departure with respect to the 2D plane of the antenna panel.
[0199] It is essential to distinguish this angle φ from the orientation angle of the antenna panel itself. The BS orientation angle, denoted as Θ, is a fixed 3D angle determined during the BS deployment and installation process. It is expressed as Θ: = (Θazimuth, Θelevation) and represents the orientation of the antenna panel with respect to the ground plane.
[0200] The true 3D angle of a radio ray propagation path with respect to the ground plane is a combination of the antenna panel's orientation angle Θ and the angle of departure φ from the antenna panel. By estimating φ and combining it with the known Θ, the real-world 3D angle of the propagation path can be determined.
[0201] In most scenarios, the BS installation reference plane (typically the ground plane) and the orientation angle Θare known or can be accurately measured and fixed. Therefore, estimating the angle φ from the transmit (BS) array response matrix ABS (φ) is sufficient to calculate the true 3D angle of the propagation path with respect to the ground plane.
[0202] Although not illustrated, an AoA could be represented in a similar way to the representation of the AoD, and details are omitted.
[0203] Notably, this application does not exclude other possible implementations of expressing the AoD and AoA.
[0204] 4) channel state information (CSI)
[0205] To facilitate understanding of the embodiments of this application, the CSI-RS is described in detail by example below. The CSI-RS is mainly used for downlink channel estimation corresponding to a physical antenna port. For example, a receiving apparatus (i.e. a terminal device) may perform channel estimation on each physical antenna port based on a CSI-RS sent by a transmitting apparatus ( (i.e. a network device) , to feedback channel state information (CSI) based on a channel estimation result. The CSI may include related information such as a channel quality indicator (channel quality indicator, CQI) , a precoding matrix indicator (precoding matrix indicator, PMI) , a layer indicator (layer indicator, LI) , and a rank indicator (rank indicator, RI) . The CSI is used to reconstruct or precode the downlink channel. In some embodiments, a process in which the base station obtains CSI may include: the base station sends a reference signal to the ED; the ED obtains an estimated CSI value according to the received reference signal, selects a precoding vector from a codebook according to the estimated CSI value, and feedback related to the index of the precoding vector to the base station; and the base station determines a CSI reconstruction value with reference to the index of the precoding vector. The CSI reconstruction value can be the CSI closest to the true value of the CSI that can be obtained by the base station.
[0206] Notably, the above presents a simplified description of some related technologies to provide a basic understanding. The various concepts presented throughout this disclosure may be implemented across a broad variety of telecommunication systems, network architectures, and communication standards. The actual telecommunication standard, network architecture, and / or communication standard used will depend on the specific application and the overall design constraints imposed on the system.
[0207] Notably, in some implementations, the term “ED” and the term “UE” may be used interchangeably.
[0208] Regarding the RF map, millimeter wave (mmWave) -sensing technology, and machine learning (ML) and artificial intelligence (AI) technology may be used to construct the RF map.
[0209] (1) mmWave-sensing
[0210] Some techniques on environment mapping and reconstruction for wireless systems has explored millimeter wave (mmWave) sensing approaches. Millimeter wave frequencies, typically in the range of 30-300 GHz, have gained significant interest in both communication and sensing applications in recent years. MmWave sensing leverages the quasi-optical properties of mmWave signals to enable highly directional beam transmission and reception, enhancing spatial resolution.
[0211] In wireless communication, mmWave is a key enabling technology for 5G and beyond networks. The large available bandwidth at mmWave frequencies can support multi-Gbps data rates. However, mmWave signals also experience high isotropic path loss and are vulnerable to blockages. Beamforming using large antenna arrays is therefore critical to overcome these issues.
[0212] This same beamforming capability has opened up opportunities for mmWave sensing and mapping in wireless systems. By measuring angles of arrival / departure or the time delays of reflected mmWave signals, it is possible to accurately locate objects and reconstruct environmental maps. Several mmWave sensing techniques have been explored:
[0213] Monostatic Radar Sensing: The communications array is used in a radar mode by transmitting special sensing waveforms and processing the reflections.
[0214] Bistatic Sensing: Sensing signals transmitted from a base station's antenna array are measured at user equipment (UE) receiving arrays, and the UE provides feedback to the base station, enabling multi-perspective views.
[0215] mmWave sensing has shown potential for applications like vehicular environment mapping, indoor localization / tracking, gesture recognition, and high-resolution imaging. However, its range is fundamentally limited by high atmospheric attenuation at mmWave frequencies.
[0216] Additionally, mmWave sensing is optimized for the mmWave frequency bands which do not align well with sub-6 GHz or 10 GHz-to-14 GHz cellular bands where environment mapping would be more beneficial. In other words, although mmWave sensing may reconstruct 3D environments, it cannot capture radio path loss information, as the 4-th dimension enable a RF-Map.
[0217] Furthermore, for both monostatic and bistatic mmWave sensing paradigms, these techniques involve designing special waveforms to be transmitted for environment sensing. The reflected signals are then measured and processed to extract mapping information. However, this approach requires allocating some of the wireless system's resources specifically for sensing purposes rather than data communication. It also needs specialized waveform design which increases system complexity.
[0218] Moreover, having a base station employ both mmWave sensing and sub-6GHz (or 10GHz-to-14GHz) communication is suboptimal from a system design perspective. The differing requirements for mmWave sensing and sub-6GHz / 10-14GHz communications introduce significant complexity in terms of RF front-end design, antenna integration, signal processing, and other system aspects, making it impractical to integrate these two frequency ranges into the same base station platform efficiently. The mmWave sensing would be tuned for the specific mmWave frequencies used, while the sub-6GHz / 10-14GHz bands are where the main communications take place to reach ubiquitous coverage. Note that mmWAVE sensing coverage is much shorter than communication coverage. Trying to integrate these two very different frequency ranges into the same base station platform introduces significant complexity in terms of RF front-end design, antenna integration, signal processing, and other aspects. It would be much more efficient and practical to instead have the environment mapping capabilities natively operated in the same frequency bands as the main communications system, rather than relying on a separate mmWave sensing module. This avoids having to support the vastly different propagation characteristics of mmWave versus sub-6GHz / 10-14GHz signals all within the same base station.
[0219] The monostatic sensing mechanism also suffers from some key drawbacks. Since the sensing and communications are occurring from the same antenna array, there can be significant interference between the two operations. This self-interference needs to be carefully mitigated (managed) through techniques like (antenna space) isolation, interference cancellation (needs special circuits) , or avoidance. Avoidance mechanisms, where sensing is scheduled to avoid overlapping with communication time slots or bands, lead to inefficient resource utilization and reduce spectral efficiency. For example, for mono-static sensing, the base station may need to intermittently go silent on communications to enable listening for reflections in a radar-like mode. This "silence period avoidance mechanism" to separate sensing from communication results in the wastage of valuable time-frequency resources that could have otherwise been used for data transmission. Moreover, mono-static sensing only provides a single perspective view of the environment from the base station location, resulting in limited coverage and mapping resolution.
[0220] While bistatic sensing can provide multi-perspective mapping views compared to mono-static approaches, it also has its own limitations. For accurate bi-static sensing, there needs to be more precise time / frequency synchronization between the transmitting base station and all the receiving ED nodes than communication requests. Any synchronization errors can degrade the sensing performance. Achieving tight synchronization adds complexity. ED side like measuring angles / delays of reflected paths and processing the sensing feedback consumes non-trivial power and processing on the mobile devices. This can accelerate battery drain on ED devices. The sensing information measured at the user equipment (UE) receivers needs to be fed back to the base station over uplink radio resources. This uplink feedback consumes precious bandwidth and adds significant overhead, especially as the number of EDs increases in the network.
[0221] A major drawback of bistatic sensing, particularly at mmWave frequencies, is that the ED receivers essentially only measure the direct line-of-sight (LOS) path from the transmitting base station. The quasi-optical mmWave signals do not effectively penetrate and scatter off environmental objects and surfaces. As a result, the sensing information available at the EDs consists primarily of just the LOS path with very little multipath information carrying environmental mapping details.
[0222] This lack of rich multipath components means the bi-static mmWave sensing has limited ability to reconstruct and map the actual 3D geometry of the surroundings based on reflected paths. While the LOS path can provide basic positioning, expressions (details) from objects like angles / delays of strong reflections off buildings and surfaces are mostly unavailable at the EDs. This prevents high-fidelity mapping of the environment's radio characteristics and 3D structure.
[0223] The mmWave-sensing, due to its own characteristics, is limited in capturing path loss information, which restricts its capability in constructing a comprehensive 4D map.
[0224] (2) AI / ML-Based RF map reconstruction-data requirement and challenge
[0225] With the recent advances in ML and AI, there has been growing research interest in applying these techniques for radio environment mapping and RF map reconstruction.
[0226] AI / ML-based approaches try to learn and generalize the complex mapping from sensory data (e.g. monosonic or bisonic sensory data aforementioned) to spatial environments in a data-driven manner. Several techniques have been explored:
[0227] Fingerprinting with Deep Learning: RF fingerprint datasets mapping received signal signatures to locations are collected and used to train deep neural networks (DNNs) or other ML models. These can then predict locations or environment maps from new signal measurements, significantly improving the accuracy and utility of RF maps.
[0228] GANs for 3D Environment Generation: Generative adversarial networks (GANs) have been applied to generate plausible 3D scene reconstructions from partial sensory inputs like channel state information. This technique provides a powerful tool for creating detailed and realistic environmental visuals crucial for various applications.
[0229] End-to-End Learning: Rather than separate intermediary steps, end-to-end deep learning models directly map raw measurements like channel responses to 3D maps.
[0230] Hybrid Physics-ML Approaches: Domain knowledge from physics-based models is embedded into the ML architecture to constrain the learning problem better.
[0231] Some key benefits of the AI / ML approaches include: learning complex mappings that are hard to model analytically, generalization ability through training on diverse datasets, and incorporating sensor data fusion from different modalities.
[0232] However, there are also several challenges with AI-based RF mapping. First of all, it consumes a lot of data. Very large and diverse training datasets are required to achieve effective generalization across different environments. Secondly, the methodology lacks interpretability. The learned models are typically opaque black-boxes lacking physical intuition and interpretability. Thirdly, AI methodology is usually not real-time and complexity with a large-q of neurons. Efficient deployment of large deep neural networks on resource-constrained devices is challenging for real-time operation. At last, models trained in one environment may not generalize well when deployed in significantly different environments due to distribution shifts. In conclusion, these data, interpretability, complexity, and generalization issues continue to be active areas of research as AI / ML plays an increasing role in wireless sensing and mapping applications.
[0233] Another major non-technical challenge for AI / ML-based RF mapping techniques is the potential privacy issues that arise from relying on user equipment (UE) (ED) position data as part of the training process. This reliance often complicates data collection and may limit the deployment of such technologies due to privacy concerns. Many of these approaches use simultaneous localization and mapping principles, where RF data measurements are associated with ground truth ED location labels to learn the mapping between signals and spatial environments.
[0234] This impediment limits the AI / ML approaches in two key ways: first, it becomes extremely difficult to collect large, diverse datasets spanning different locations and scenarios for effective training. Second, even if trained models are developed, their applicability is constrained to static environments where real-time ED position tracking is not required during the mapping operation itself.
[0235] Privacy-preserving ML techniques like federated learning could potentially help, but even with these approaches, challenges remain in sufficiently privatizing the modeling process, particularly for highly sensitive location data. For highly sensitive location data, there are still open challenges around sufficiently privatizing the modeling process. Overall, negotiating this tension between learning from ED position ground truth and maintaining user privacy remains a critical issue for the widespread deployment of AI / ML RF mapping solutions.
[0236] User Equipment (UE) position information is often used in cellular communication networks to improve various network performance metrics for the network. Such performance metrics may, for example, include capacity, agility, and efficiency. The improvement may be achieved when elements of the network exploit the position, the behavior, the mobility pattern, etc., of the UE in the context of a priori information describing a wireless environment in which the UE is operating.
[0237] A sensing system may be used to help gather UE pose information, including its location in a global coordinate system, its velocity and direction of movement in the global coordinate system, orientation information, and information about the wireless environment. While traditionally separate, integrating this sensing system with the communication system could provide advantages in terms of reduced hardware requirements and resource utilization, although it introduces significant challenges in achieving accurate and comprehensive environmental sensing using communication system hardware. “Location” is also known as “position” and these two terms may be used interchangeably herein. Examples of well-known sensing systems include radar (Radio Detection and Ranging) and lidar (Light Detection and Ranging) . While the sensing system can be separate from the communication system, it could be advantageous to gather the information using an integrated system, which reduces the hardware (and cost) in the system as well as the time, frequency, or spatial resources needed to achieve both functionalities. However, using the communication system hardware to perform sensing of UE pose and environment information is a highly challenging and open problem. The difficulty of the problem relates to factors such as the limited resolution of the communication system, the dynamicity of the environment, and the huge number of objects whose electromagnetic properties and position are to be estimated.
[0238] Accordingly, integrated sensing and communication (also known as integrated communication and sensing, joint sensing and communication, and other similar names) is a desirable feature in existing and future communication systems. This integration aims to enhance system efficiency by combining two critical functionalities into a single framework, although achieving this integration effectively remains a complex and unresolved challenge.
[0239] Therefore, this application provides a method that terminal side and network side can obtain the spatial characteristics and the RF characteristics based on the same reference signal in an efficient way.
[0240] Notably, for ease of description, the terminal side is exemplified as an ED, and the network side is exemplified as a BS hereinafter. This is not limited to this application.
[0241] FIG. 13 is a schematic flowchart of a method according to this application.
[0242] At step 1310, a BS transmits a reference signal to an ED. Correspondingly, the ED receives the reference signal from the BS.
[0243] At step 1320, the ED transmits first information to the BS. Correspondingly, the BS receives the reference signal from the ED.
[0244] The reference signal is associated with multiple angles of departure, denoted as P (or set P) (i.e., the symbol “P (or set P) ” represents the multiple first angles of arrival) . The reference signal is used to generate the first information. The first information indicates a parameter set of path loss (as RF characteristics) associated with a full set or a subset of the P (as spatial characteristics) , denoted as S (or set S) (i.e., the symbol “S (or set S) ” represents the multiple first angles of arrival) . The spatial characteristics and the RF characteristics can be obtained based on the same reference signal in an efficient way.
[0245] The term “angle of departure” refers to a direction of propagation of a radio frequency wave transmitted from an antenna array (i.e., BS antenna array) relative to orientation of the antenna array.
[0246] Path loss may be referred to as a reduction in power density (or attenuation) of an electromagnetic wave as it propagates through space. In some implementations, the parameter set of path loss, which may reflect the path loss, may include one or more of: a channel gain, reference signal received quality (RSRP) , signal to interference noise ratio (SINR) , channel quality indicator (CQI) , rank indicator (RI) , and other parameters related to the path loss. This is not limited to this application.
[0247] Notably, an angle of departure could correspond to a path between the BS and the ED. In other words, the reference signal transmitted by the BS at a certain angle of departure would arrive at the ED through the corresponding path.
[0248] The first information may indicate path loss of all or part of multiple paths corresponding to the multiple angles of departure (i.e., P) . For example, the reference signal may be transmitted at p (which is a positive integer) angles of departure. The first information indicates the path loss of s (which is a positive integer, s≤p) paths respectively corresponding to s angles of departure among the p angles of departure. That is, the association between the path loss and the S may be reflected as each angle of departure (which could correspond to a path) is associated with one or more parameters indicating path loss of the corresponding path.
[0249] Notably, the first information can be used for constructing a 4D RF map, because spatial characteristics (or angular characteristics) and path loss characteristics can be obtained from the first information. The BS can know the path loss of the paths corresponding to the angle (s) emitted by the BS, and construct the 4D RF map.
[0250] The “4D RF map” in implementations of this application may be represented in various forms. For example, the BS may draw a 4D RF map of an area based on the first information; or the 4D RF map may be illustrated as one or more tables; or the 4D RF map may represent channel data and / or geographic data derived from the first information; or the first information may be referred to as a kind of form of the 4D RF map. This is not limited to this application.
[0251] Notably, the first information can be used to construct / reconstruct a 4D RF map, where the 4D RF map incorporates RF characteristics into spatial characteristics. In some implementations, the term RF characteristics and the term channel characteristics are used interchangeably. In some implementations, the term spatial characteristics and the term angular characteristics are used interchangeably. In some implementations, the term “path” and term “channel” are used interchangeably herein.
[0252] Notably, in some implementations of this application, the spatial characteristics are exemplary by angles of departure. However, this application does not exclude other possible spatial parameters in the physical environment for a sensing purpose, for example, the location of the ED, the existence of obstacles, terrain, etc. The above spatial parameters may be also obtained based on the reference signal. Similarly, in some implementations of this application, the RF characteristics are exemplary by path loss. However, this application does not exclude other RF parameters (e.g., channel state information) in the physic environment, for example, scattering, fading, power decay, etc.
[0253] The reference signal can be various types of downlink signal. For example, the reference signal may be a channel state information reference signal (CSI-RS) , or any other possible signal defined in a future network.
[0254] Notably, the CSI-RS herein may be designed to obtain the RF characteristics and the spatial characteristics. The CSI-RS may be referred to as sensing CSI-RS. The first information may be referred to as CSI feedback in this case.
[0255] The configuration of the reference signal (e.g., resource configuration) can be designed in a variety of ways. In some implementations, the reference signal resource in the frequency domain may be designed by the operation band of the ED.
[0256] In the 5G NR TDD system, the partial-bandwidth CSI-RS is indeed the most prevalent configuration mode. The CSI-RS is transmitted only on a part of the bandwidth (BWP) instead of the entire system bandwidth. This approach may avoid potential interference and collisions with uplink transmissions that share the same carrier frequency in TDD systems.
[0257] In some implementations, the reference signal may be configured to occupy an entire system band.
[0258] For example, in a multi-BWP system, the network side can configure separate reference signal (e.g., CSI-RS) resources on different BWPs, with each BWP obtaining the CSI for its respective part of the bandwidth. By leveraging the BWP switching mechanism, the terminal side can effectively cover the entire bandwidth by transitioning between the configured BWPs and aggregating the CSI obtained from each BWP.
[0259] In some implementations, the reference signal may be configured to occupy part of the system band. For example, for the specific purpose of 4D-RF-Map reconstruction, the BS may specify a subset of subcarriers within the CSI-RS bandwidth for the ED to perform sensing-purpose channel measurements. By focusing on these designated subcarriers, the ED can measure the frequency-domain channel response H (fk) k=1, 2, 3…at those specific frequency points fk, k=1, 2, 3…. This targeted measurement approach not only reduces the computational complexity but also allows for more efficient resource utilization during the reconstruction process.
[0260] With the aid of the BWP switching mechanism, the ED can systematically measure the channel response across the full or quasi-full system bandwidth by transitioning between the configured BWPs and repeating the channel measurement process on the specified subcarriers within each BWP. This comprehensive measurement enables the ED to obtain a complete representation of the channel characteristics across the entire frequency range, facilitating accurate 4D-RF-Map reconstruction.
[0261] However, for the sake of simplicity and clarity in the following description, we will consider an example scenario where the ED operates on a single subcarrier, denoted as fk. This focused description allows us to illustrate the underlying principles and algorithms involved in the 4D-RF-Map reconstruction process without the added complexity of BWP switching and multi-subcarrier measurements.
[0262] The ED may perform a channel estimation on the reference signal, where the channel matrix of this can be represented by Hmeasure (fk) for the certain frequency fk. The ED may perform SVD on the channel matrix Hmeasure (fk) (as described in FIG. 9) , to get the right singular matrix Vmeasure = [vmeasure_1 (fk) , vmeasure_2 (fk) , …, vmeasure_r (fk) ] and scalar values σmeasure_1 (fk) , σmeasure_2 (fk) , …, σmeasure_r (fk) , where “r” is the rank of the channel matrix. Where each column (vector) in Vmeasure can be referred to as a sub-channel.
[0263] In some implementations, the BS transmits the reference signal to multiple EDs. For example, the BS may broadcast the reference signal at the multiple angles of departure. The reference signal at an angle of departure may pass through multiple paths and arrive at multiple EDs. Similarly, for the sake of simplicity and clarity in the following description, the path (s) will be referred to as the path (s) between the BS and the single ED hereinafter, unless otherwise stated.
[0264] The multiple angles of departure are related to the configuration and structure of transmit antenna array (i.e., BS’s antenna array) .
[0265] The first information indicates path loss associated with a full set or a subset of the P, denoted as S.
[0266] Notably, as aforementioned, the BS may transmit the reference signal to multiple EDs. Each ED may transmit the first information. The BS may construct the 4D RF map based on the first information from the multiple EDs. In other words, the 4D RF map may include path loss characteristics and angular characteristics of paths between the BS and multiple locations of the EDs.
[0267] In some implementations, the S includes one or more of: at least one angle corresponding to at least one LOS path, and at least one angle corresponding to at least one i-bounce NLOS, where i=1, …, M, M is a positive integer. In other words, the first information may indicate the path loss of the LOS path (s) (if exists) and i-bounce NLOS path (s) (if exists) and their associated angle (s) of departure, rather than the path loss of all paths corresponding to the P. This could reduce transmission consumption of the first information.
[0268] For example, M may be equal to 1, the ED may report path loss of LOS path (s) and one-bounce NLOS path (s) . For another example, M may be equal to 2, the ED may report path loss of LOS path (s) , one-bounce NLOS path (s) , and two-bounce NLOS path (s) . The ED may discard information of multi-bounce (larger than M-bounce) NLOS path.
[0269] Notably, multi-bounce (larger than M-bounce) NLOS path may involve multiple reflections or diffracted components, which may be considered as inaccurate data for a 4D RF map or less likely to be chosen for communication. Therefore, the value of M is related to the resource consumption of the first information and the accuracy of the 4D RF map.
[0270] The ED can generate the first information in a variety of ways. For example, the first information indicates path loss associated with the angle (s) of departure, where the angle (s) of departure is related to the transmit antenna array. The generation implementations of the first information can be related to the configuration of the transmit antenna array. That is, in some implementations, the first information may be generated based on a configuration of transmit antenna array (or configuration of transmit antennas) associated with the reference signal.
[0271] For example, as aforementioned (e.g., in FIG. 9) , the channel matrix in the spatial domain can be represented as: Hmeasure (θ, φ, fk) = Ar (θ) H Umeasure (fk) Σmeasure (fk) Vmeasure (fk) H At (φ) , where the Vmeasure (fk) H At (φ) includes path loss component and angles of departure component. That is, the first information may be obtained from the Vmeasure (fk) H At (φ) . At (φ) is designed based on the configuration of the transmit antenna array, where the configuration may be related to geometry characteristics or parameters related to the transmit antennas. Notably, the transmit antennas here may be considered as the BS’s antennas, where the “At (φ) ” and “ABS (φ) ” can be used interchangeably.
[0272] For example, the configuration of transmit antenna array indicates one or more of:
[0273] a type of transmit antenna array, for example, the type of transmit antenna array may be divided based on the geometric characteristics of the transmit antenna array, e.g., uniform rectangular array (URA) , cylindrical array, spherical array, irregularly spaced array, or another possible array;
[0274] a quantity of transmit antennas;
[0275] spacing between adjacent transmit antennas (or distance between any two antenna elements) ; and
[0276] parameters related to reference locations corresponding to the transmit antenna array, where the reference locations are used for generating the first information, for example, the parameters may be obtained from an estimation between the transmit antennas and the reference locations.
[0277] At least part of the configuration of the transmit antenna array may affect the mathematical representation of the reference signal. For example, the type of the transmit antenna array, the quantity of the transmit antennas, and the spacing between adjacent transmit antennas may affect the amount of computation and accuracy for generating the first information. Therefore, the ED may determine an appropriate method to obtain the first information that indicates both path loss and angles based on the configuration of the transmit antennas. That is, the configuration of the transmit antennas may be used for determining the generating method of the first information. For example, the terminal side may determine a proper method to generate the first information. The configuration of the transmit antennas may be used for generating the first information. For example, the configuration may include parameters used for generating the first information. For ease of understanding embodiments of this application, three implementations of generating the first information are given below.
[0278] In a first implementation, the first information is derived using discrete Fourier transform (DFT) . The DFT can be used to obtain projections of a set of vectors (e.g., vectors in Vmeasure (fk) ) onto the transmit array response matrix ABS (φ) , denoted as < Vmeasure (fk) , ABS (φ) >. The set of vectors can also be referred to as spatial signature vectors.
[0279] For example, the transmit array response matrix ABS (φ) may be represented as ABS (φ) = [1, e (-j2πdsinφ / λ) , e (-j2π2dsinφ / λ) , ... e (-j2π (Ntx-1) dsinφ / λ) ] H. Thereby, the calculation of Vmeasure (fk) H ABS (φ) may be included (directly or after a simple process) in the first information. The BS can obtain the path loss characteristics and angular characteristics from the calculation of Vmeasure (fk) H ABS (φ) .
[0280] In some instances of this first implementation, the configuration of the transmit antennas may meet a condition#1, so that the transmit antenna array can be expressed approximately by DFT. For example, the condition#1 may include one or more of: the transmit antenna array is URA, the spacing between adjacent transmit antennas is equal to or greater than a distance threshold (e.g., half the wavelength (λ / 2) ) , the number of the transmit antennas is larger than a threshold.
[0281] Under these assumptions for future (advanced) ultra-massive MIMO DL and URA antenna array, we can equate the number of angles of departure (P) to the number of transmit antennas (NBS) . Furthermore, the NED × NBS transmit array response matrix, ABS (φ) = [1, e (-j2πdsinφ / λ) , e (-j2π2dsinφ / λ) , ... e (-j2π (Ntx-1) dsinφ / λ) ] H. When NBS is a big number (e, g., ≥256) , ABS (φ) approaches to DFT matrix of size NBS, enhancing the precision of spatial information derived from the array.
[0282] Notably, condition#1 makes the calculation using DFT feasible, this application does not exclude other possible conditions.
[0283] In some instances of the first implementation, the first information may further include a calculation of Ar (θ) H Umeasure (fk) . In other words, the first information may be further derived using the DFT to obtain projections of vectors in Ar (θ) H on to the U (fk) , denoted as < AED (θ) , Umeasure (fk) >. Thereby, the first information may further indicate the associated angle (s) of the arrival of the reference signal. In some instances, the configuration of receive antennas may meet condition#1, so that the DFT can be used. Details about the condition#1 are omitted here.
[0284] While the transmit (BS) array response matrix ABS (φ) can be a matrix of large values of NBS in the downlink of future (advanced) ultra-massive MIMO system, a similar approach for the receive (ED) array response matrix AED (θ) at the user equipment (ED) may not be as straightforward. In the downlink MIMO scenario, the number of receive (ED) antennas (NED) at the ED is typically much smaller than the number of transmit (BS) antennas (NBS) at the base station, thereby limiting the angular resolution for angles of arrival (AoA) θ at the ED side. Additionally, there can be different types of EDs with varying numbers of antennas and even different antenna panel configurations, resulting in inconsistencies in the spatial projection for various EDs. Consequently, the angular domain representation at the ED side may not be as accurate or consistent across different EDs. In contrast, the transmission side at the BS remains consistent even for different downlink transmissions to different EDs, making the angular domain analysis at the BS more reliable and valuable for spatial processing techniques in the downlink MIMO configuration.
[0285] As aforementioned in FIG. 12, to obtain the true 3D angle with respect to the ground plane, the known orientation angle of the antenna panel, denoted as (Θazimuth, Θelevation) , is added to the relative angle (φazimuth, φelevation) . This combination of Θ and φ provides the 3D angle of the path vi (fk) with respect to the ground plane.
[0286] However, the direct computation of the (φ'azimuth, φ'elevation) pair corresponding to each spatial signature vmeasure _i (fk) H ABS (φ) at the ED side faces several practical challenges. Firstly, the transmit (BS) array response matrix ABS (φ) is intrinsically tied to the specific antenna array panel design employed at the BS. This implies that for accurate angle estimation, the BS needs to convey the exact ABS (φ) matrix to the EDs prior to communication. However, as different BSs may adopt various kinds of antenna panel configurations, there is no standardized formation for ABS (φ) , introducing potential compatibility issues and additional signaling overhead.
[0287] Secondly, while ABS (φ) can be well approximated by a bijective DFT matrix under certain idealized conditions (e.g., condition#1 described above) , such as a URA antenna array panel at the BS, practical deployment scenarios often deviate from these assumptions. Many modern base stations employ more advanced antenna panel designs, such as cylindrical, spherical, or irregularly spaced arrays, which cannot be approximated by a DFT matrix. In such cases, computing the projection vmeasure_i (fk) H ABS (φ) becomes computationally intensive, especially as it cannot leverage efficient algorithms like the Fast Fourier Transform (FFT) .
[0288] In such cases, a second implementation (when condition#2 is met, the projection Vmeasure (fk) H ABS (φ) may be approximately substituted by the Vmeasure (fk) ) , a third implementation (the first information may be derived using the parameters related to reference locations) are introduced below.
[0289] In a second implementation, the first information includes a set of vectors, where the set of vectors is obtained from a channel estimation based on the reference signal. For example, the set of vectors may be vectors in Vmeasure (fk) (i.e., the spatial signature vectors) . That is, the projection Vmeasure (fk) H ABS (φ) may be approximately substituted by the Vmeasure (fk) .
[0290] In some instances of this second implementation, the transmit antennas may meet condition#2, so that the ED may report the Vmeasure (fk) to imply the path loss and associated angles of departure. For example, condition#2 may include: the spacing between adjacent transmit antennas is equal to or greater than a spacing threshold (e.g., half the wavelength (λ / 2) ) (referred to as the first criterion hereinafter) , the number of the transmit antennas is larger than a fourth threshold (referred to as second criterion hereinafter) . The BS can obtain approximate path loss characteristics and angular characteristics based on the Vmeasure (fk) .
[0291] For example, when an antenna panel configuration meets two criteria, directly computing the spatial signature vmeasure_i (fk) H At (φ) may not be the most practical approach for angle estimation at the ED side.
[0292] The first criterion is that the distance between any two antenna elements in the panel is greater than or equal to half the wavelength (λ / 2) . This condition ensures that the transmit (BS) array response matrix ABS (φ) can accurately capture the spatial characteristics of the propagation paths without introducing undesirable effects such as mutual coupling or grating lobes.
[0293] The second criterion is that the number of transmit (BS) antennas (NBS) is sufficiently large to ensure the quasi-bijectivity (one-to-one mapping between vmeasure_i (fk) and v measure_i (fk) H ABS (φ) ) . In other words, ABS (φ) should be a well-conditioned matrix, capable of representing distinct spatial signatures for different angles of departure without ambiguity. This condition helps in high-resolution angle estimation and scenarios with closely spaced propagation paths.
[0294] When these two criteria are met, the vmeasure_i (fk) itself can serve as an alternative spatial signature of the propagation path. Instead of relying on the projection vmeasure_i (fk) H ABS (φ) , the ED can directly utilize vmeasure_i (fk) for spatial detection purposes.
[0295] In a third implementation, the first information is derived using the parameters related to reference locations. For example, angles from the transmit antenna array to the reference locations related to the transmit antenna array include the P. The reference locations can be designed to reflect the spatial characteristics of angles of departure (P) where the reference signal is transmitted.
[0296] The reference locations can be designed in a variety of ways. In some instances, the reference locations may be designed based on angles of departure supported by the BS. For example, the BS may support emitting signals within a certain range of directions (e.g., φazimuth from -π / 6 to 5π / 6 and φelevation from 0 to π / 2) . The angles between the antennas of the BS and the reference locations may be within a certain range. The distance between the reference locations and the transmit antennas is not limited to this application. For example, the distance may be 20 meters.
[0297] For ease of description, the reference locations may be considered as locations on a virtual planar screen. Determining the reference locations can be described as building (generating) the virtual planar screen.
[0298] The BS can generate an adapted virtual planar screen based on a predefined specification, configuration, or design of the antenna panel. This adaptation can incorporate factors such as the physical dimensions of the antenna array, the radiation patterns of individual antenna elements, the operating frequency band, and the intended coverage area of the BS, allowing the virtual planar screen could reflect the practical constraints and capabilities of the antenna system.
[0299] The parameters related to a reference location may include at least one spatial parameter (e.g., angular parameter) and associated path loss parameter. For ease of description, these parameters may be generically referred to as virtual planar screen data. The virtual planar data can reflect spatial characteristics and associated path loss characteristics, so that the parameters can be used for generating the first information.
[0300] In some instances, the parameters indicate a set of first thresholds corresponding to path loss associated with the P. For example, the paths between the antennas of the BS and the reference locations could be assumed as LOS paths. Path loss of the LOS paths can be calculated (based on the reference locations) and together with actual measured path loss (obtained in step 1310) to generate the first information. For example, the ED may use the virtual planar data to filter out the LOS path (s) and the i-bounce (e.g., i=1) NLOS path (s) among the multipath propagation of the reference signal.
[0301] It's worth noting that the construction of the spatial map can be implemented by the assumption of a LOS propagation environment, free from obstacles and reflections. In practical scenarios, where multipath propagation and NLOS conditions are prevalent, additional signal processing techniques and channel modeling approaches may be used to account for these effects accurately.
[0302] The parameters may be derived from a channel estimation between the transmit antennas and the reference locations. For example, the parameters may be obtained from a LOS channel matrix H (φazimuth, φelevation) between the transmit antennas and the virtual planar screen. The BS may perform SVD on the LOS channel matrix to extract the matrix of right singular matrix V (φazimuth, φelevation) , where each column in the matrix may be referred to as a spatial signature vector. The spatial signal vector indicates spatial characteristics (e.g., represented by the φazimuth, φelevation) and associated path loss characteristics (e.g., represented by a scalar of the spatial signature vectors σ1 (φazimuth, φelevation) ) of the LOS channel.
[0303] Notably, when the channels between the transmit antennas and the reference locations are assumed as LOS channels, the right singular matrix V (φazimuth, φelevation) for each reference location may have a single column v1 (φazimuth, φelevation) . Therefore, the virtual planar data may include a set of vectors v1 (φazimuth, φelevation) for each reference locations. The corresponding scalar values σ1 (φazimuth, φelevation) can be included in the virtual planar data or derived from the vectors.
[0304] The first thresholds may be determined based on the set of vectors or the corresponding scalar values. For example, a first threshold associated with an angle of departure may be equal to the corresponding scalar value. For another example, the first threshold may be equal to the corresponding scalar value adding an offset. For another example, the first threshold may be replaced with a range, so that the ED could determine whether measured path loss is within this range. This is not limited to this application.
[0305] The parameters can be derived in a variety of ways, for example, simulation, artificial intelligence / machine learning (AI / ML) technology, etc. Some exemplary methods are given below:
[0306] To obtain the corresponding LOS channel matrix H (φazimuth, φelevation) at every virtual planar screen angle φ, several alternative methods can be employed:
[0307] 1) Electromagnetic simulation: Virtual signals can be generated using electromagnetic simulation software based on the antenna design, operating frequency band, and intended coverage area of the BS. These simulations can provide the LOS channel response for each angle on the virtual planar screen, accounting for the specific antenna characteristics and propagation conditions.
[0308] 2) Pre-deployment measurements: Before deploying the BS in the field, measurements can be conducted in a controlled environment, such as an anechoic chamber or an open-area test site, to capture the LOS channel response from various angles. Since the same antenna design can be shared across multiple BSs operating in similar frequency bands and coverage areas, a common virtual planar screen can be utilized.
[0309] 3) On-site measurements and post-processing: By measuring the actual channel data from multiple deployed BSs, it may be possible to identify and isolate the LOS path using advanced signal processing techniques, such as high-resolution parameter estimation or SVD-based approaches. The identified LOS paths can then be averaged across multiple BSs to obtain a more accurate and robust LOS channel representation for the virtual planar screen.
[0310] 4) Hybrid approach: A combination of the above methods can be employed, where simulations or pre-deployment measurements provide an initial estimate of the LOS channel, which is then refined and calibrated using on-site measurements from deployed BSs. This hybrid approach can leverage the advantages of both simulation and measurement- based techniques, potentially improving the accuracy and applicability of the spatial map.
[0311] Regardless of the method chosen, other methods that the obtained LOS channel matrices can represent the true propagation conditions experienced by the BS, are not excluded in this application.
[0312] In some instances, the parameters are associated with one or more factors related to the reception of the reference signal: frequency, whether conditions, an orientation of the ED, and a communication environment of the ED. These factors may affect the path loss characteristics. For example, the weather conditions may include temperature, humidity, the presence of micro-particles in the air, etc. The orientation of the ED may represent changes in ED’s location. The communication environment may represent present of obstacles, etc. The virtual planar screen data may be associated with the factors. The ED may use proper parameters based on the factor (s) , improving the reliability of the first information.
[0313] The virtual planar screen representation of the spatial channel may be affected by various environmental factors, such as temperature, humidity, and the presence of micro-particles in the air. These factors generally do not influence the angles of arrival / departure, but they can impact the path loss and signal attenuation, which is reflected in the singular values (e.g., σ1) . Consequently, the BS may need to maintain multiple virtual planar screens corresponding to different environmental conditions, such as different temperature and humidity ranges, to accurately capture the channel characteristics.
[0314] For example, the BS may build a virtual planar screen and generate virtual planar data based on the one or more factors. Exemplarily, the BS may build a virtual planar screen and generate virtual planar data based on a certain frequency fk. Thus, the virtual planar screen data associated with the frequency fk may be represented by a set of vectors v1 (φazimuth, φelevation, fk) and corresponding scalar values σ1 (φazimuth, φelevation, fk) .
[0315] Notably, the certain frequency fk can be replaced by any one or more of the factors (e.g., whether conditions, a combination of frequency and whether conditions, etc. ) . For ease of description, the virtual planar screen data associated with frequency is mainly described as an example.
[0316] Another factor that affects the angular representation of the virtual planar screen is the wavelength λk or, more specifically, the subcarrier frequency fk at which the channel matrix H (φazimuth, φelevation, fk) is generated. In the context of MIMO systems, where the operational bandwidth may extend to 400 MHz or beyond, the wavelength corresponding to the lowest subcarrier can differ significantly from that of the highest subcarrier. This frequency-dependent variation in wavelength is actually advantageous, as it provides more information about the broad spectrum of reflective surface materials and their scattering properties at different frequencies.
[0317] For example, the BS may build may build a virtual planar screen for every one or more frequency units. That is, every one or more frequency units may share the same virtual planar screen. The number of the one or more frequency units can be designed in a variety of ways. For example, it can be designed based of calculation power of the BS, the range of the subcarriers, etc. This is not limited to this application.
[0318] Still referring to the third implementation, the parameters used for generating the first information are introduced above, and the method of generating the first information is described below.
[0319] In some instances, the ED may perform a selection process to generate the first information. The selection process may be used to select the S among the P.
[0320] Notably, the ED has two sets of data, one set of data is obtained from measuring the reference signal (referred to as step 1310) , and another set of data is virtual planar screen data. The virtual planar data may include a set of vectors v1 (fk) and a set of scalar values σmeasure_1 (fk) associated with reference locations (i.e., angles of departure) . In order to distinguish the two sets of data, the channel matrix based on the reference signal is represented by Hmeasure (fk) for a certain frequency fk. The ED may perform SVD on the channel matrix Hmeasure (fk) , to get the right singular matrix Vmeasure = [vmeasure_1 (fk) , vmeasure_2 (fk) , …, vmeasure_r (fk) ] and scalar values σmeasure_1 (fk) , σmeasure_2 (fk) , …, σmeasure_r (fk) , where “r” is the rank of the channel matrix. Where, each column (vector) in Vmeasure can be referred to as a sub-channel.
[0321] As aforementioned in step 1310, the S (angles of departure indicated by the first information) may include angle (s) corresponding angle (s) corresponding to LOS path (s) and angle (s) corresponding to i-bounce NLOS path (s) (i=1, …, M) (M=1 is taken as an example hereinafter) . The scalar values of the virtual planar screen data may represent path loss of the LOS component. The ED may select the LOS and one-bounce NLOS sub-channels by comparing the measured scalar values with the LOS components.
[0322] In some instances, the first information may be further based on a second threshold. The second threshold (also referred to as a proportion threshold) is related to the value of M. The second threshold may be designed to control the number of bounces of the path indicated by the first information, improving the reliability of the first information. For example, for each MIMO sub-channel i∈ {1, 2, …} , if the ratio between the σmeasure_i (fk) and the corresponding LOS component σ1 (fk) is smaller than the proportion threshold, the corresponding sub-channel may be considered as not the LOS or the one-bounce NLOS and the ED may discard the corresponding sub-channel; if not, the corresponding sub-channel may be considered as the LOS or the one-bounce NLOS, the sub-channel can be used to generate first information.
[0323] The ED may perform rank-reduced SVD on Hmeasure (fk) to obtain a right singular matrix Vmeasure (fk) and a singular value matrix Σ (fk) . The right singular matrix Vmeasure (fk) contains all the spatial path information from the BS to the ED at the subcarrier fk, accounting for both LOS and NLOS propagation scenarios.
[0324] As we have mentioned, unlike traditional CSI feedback aimed at optimizing transmission quality, CSI feedback for 4D RF Map reconstruction primarily focuses on paths with less reflections (e.g., the LOS and one-bounce NLOS components) . After separating the MIMO sub-channels using SVD, we need to select and retain only the MIMO sub-channels formed by the potential LOS and one-bounce NLOS components. The selection process may be as follows:
[0325] The ED first compares the singular value corresponding to a MIMO sub-channel with the singular value pre-stored in the virtual planar screen data (e.g., tables or vectors) . If the singular value corresponding to vmeasure_i (fk) is too small, it implies that the path loss on the ray or cluster of rays corresponding to vmeasure_i (fk) is substantial and cannot be reliably utilized for 4D RF Map reconstruction. This step allows the ED to remove many low-quality MIMO sub-channels that are unsuitable for environment reconstruction.
[0326] Thereafter, the ED may measure the relative differences between the singular values of the remaining MIMO sub-channels. Since SVD decomposition is typically used for MIMO channel separation, the first MIMO sub-channel is usually the strongest, the second is the second strongest, and so on. The ED can calculate the ratio of the singular values of the remaining sub-channels after the second sub-channel to the singular value of the first MIMO sub-channel. If this ratio is greater than the proportion threshold, the MIMO sub-channel may be retained; otherwise, it may be removed from the candidate group. After these two selection steps, it is highly likely that the remaining MIMO sub-channels correspond to the LOS or one-bounce NLOS components.
[0327] The proportion threshold can be used for balancing the trade-off between the accuracy of the 4D RF Map reconstruction and the associated overhead and computational complexity at the ED. Unlike conventional channel measurement and feedback mechanisms designed for transmission purposes, where the ED typically needs to provide the complete channel state information (CSI) , the reconstruction task does not necessitate the ED to compress and feed back all channel information. Instead, the ED can selectively provide only a portion of the channel information, thereby reducing the overhead and computational complexity involved in the feedback process.
[0328] The proportion threshold determines the fraction or percentage of the most significant channel components or spatial signatures that the ED needs to feedback to the BS for the reconstruction process. By setting an appropriate proportion threshold, the BS can strike a balance between the reconstruction accuracy and the feedback overhead.
[0329] Therefore, the proportional threshold is a parameter that governs the extraction of high-quality LOS and strong single-bounce reflected paths from the overall channel response.
[0330] Notably, this application does not exclude other possible selection processes.
[0331] In some instances, the ED may perform an optimization process to generate the first information. The optimization process may be used to compact the first information.
[0332] For the sake of description simplicity and efficiency, the virtual planar screen can be represented using a matrix Ψ (fk) , where each column corresponds to a spatial signature vector v (fk) , with a height equal to the number of antennas at the BS (NBS) . Furthermore, each column in this matrix represents a distinct transmit angle φ from the BS's perspective. There are numerous candidates, Nφ, angles φ, resulting in the matrix Ψ (fk) being a "short and fat" NBS× Nφ matrix.
[0333] In theory, each selected column vector, v measure_m (fk) , =1, 2, …, of V (fk) can be expressed as a linear combination of all the columns in the matrix Ψ (fk) . However, considering that the spatial propagation path is sparse when the number of transmit antennas (NBS) is very large, the objective is to linearly fit v measure_m (fk) with as few columns of matrix Ψ (fk) as possible: v measure_i (fk) ≈Ψ (fk) s (fk) , where s (fk) is Nφ × 1 vector indicating which columns are used for the linear fitting.
[0334] This calculation is formulated as an optimization problem. The primary objective of the linear combination fitting is to minimize the Mean Squared Error (MMSE) , equivalent to minimizing the L-2 norm. Additionally, to achieve sparsity and utilize as few spatial signatures as possible, the optimization is performed under the constraint of minimizing the L-1 norm.
[0335] Find a vector s such that:
[0336] α min (|| vmeasure_i (fk) -Ψ (fk) s (fk) ||2) +β min (| s (fk) |)
[0337] where α and β are optimization parameters.
[0338] It can be solved by the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm or matching pursuing (MP) algorithm, message-passing algorithm (MPA) , or even deep neural network.
[0339] The result of the optimization is a highly sparse vector s', which indicates the transmission angles of the rays from the BS side within the cluster of rays corresponding to the spatial signature v measure i. Generally, these rays converge to form a cluster, producing effective MIMO sub-channels. Therefore, we can remove any outlier angle results that do not converge with the dominant cluster.
[0340] In some instances, the ED may perform a selection process and an optimization process to generate the first information. For example, the ED may perform the selection process (as described above first) , and perform an optimization process on the selected sub-channel (s) .
[0341] For the remaining MIMO sub-channels v measure_i (fk) (including the LOS and single-bounce NLOS sub-channels) , sparse optimization is performed as shown above (optimized α min (|| v measure_i (fk) -Ψ (fk) s (fk) ||2) +β min (| s (fk) |) ) .
[0342] The optimization result corresponding to each sub-channel is a sparse s' (fk) vector containing the angles of the rays emitted from the BS that formed the sub-channel, along with the channel loss or channel gain at each angle. Sometimes, there may be multiple rays contributing to a sub-channel. To reduce the overhead of CSI feedback, the ED may identify the ray with the strongest channel gain in s' (fk) and use this ray to approximate the transmission angle from the BS that formed the sub-channel.
[0343] This approximation essentially enhances the relative importance of the β min (| s (fk) |) term compared to the αmin (|| v measure_i (fk) -Ψ (fk) s (fk) ||2) term in the optimization objective. If only the strongest ray is retained, the entire "optimized α min (|| v measure_i (fk) -Ψ (fk) s (fk) ||2) +β min (| s (fk) |) " problem becomes a simpler task of "finding the column of the matrix Ψ (fk) whose inner product with v measure_i (fk) is the largest. " In this way, the computational burden on the ED becomes significantly reduced.
[0344] In a communication system, the above three implementations can be implemented separately or in a combination. This is not limited to this application. For example, the network may determine the implementation to generate the first information based on the application scenario or the configuration of the base stations.
[0345] In some implementations, the first information further indicates propagation delay (s) associated with the reference signal. That is, the ED may further feedback time characteristics to the BS, improving the performance of the first information used for reconstructing the 4D RF map.
[0346] Notably, the ED can perform a delay estimation process on the sub-channels. In some implementations, when the ED performs a selection process to obtain the selected sub-channels (e.g., a sub-channel corresponding to the LOS component and a sub-channel corresponding to one-bounce NLOS) , the ED may perform a delay estimation process on the two sub-channels. The process complexity on the ED side can be further reduced.
[0347] For example, in an OFDM-MIMO system, the ED can perform an Inverse Discrete Fourier Transform (IDFT) operation on these frequency-domain representations to convert them into their corresponding time-domain channel impulse responses, e.g., h1 (t) and h2 (t) , respectively.
[0348] By analyzing the time-domain channel impulse responses, the ED can estimate the relative delays τ1 and τ2 associated with the two MIMO sub-channels. These relative delays represent the propagation times of the LOS and single-bounce NLOS components subtracting the LOS propagation time, respectively, and are directly related to the distances traveled by these components relative to the LOS path.
[0349] As aforementioned, although the above examples describe the channel characteristics at the certain frequency fk, the reference signal may occupy multiple frequencies (e.g., as illustrated in FIG. 14) . In some instances, the ED may perform delay estimation by combining the sub-channels separated from multiple frequencies.
[0350] The delay estimation process can be further enhanced by combining the time-domain channel impulse responses obtained from multiple subcarriers, as mentioned earlier. This approach leverages the frequency diversity present in the channel, providing a more robust and accurate delay estimation, which is crucial for identifying the corresponding angles on the virtual planar screen.
[0351] The distance traveled by the LOS component can be estimated by comparing the singular value σ1 (fk) of MIMO channel H (fk) with the corresponding singular value recorded on the virtual screen, given they experience free-space pathloss. With the estimated relative delays and the knowledge of the propagation speed (typically the speed of light) , the approximate distances traveled by the single-bounce NLOS components can be subsequently calculated. These distance estimates, along with the angle information obtained from the virtual planar screen, enable the ED to reconstruct the 3D spatial geometry of the propagation paths, which is a key component of the 4D RF Map reconstruction process.
[0352] The first information may indicate the path loss associated with the S explicitly or implicitly. The interpretation of the first information is related to the generation method of the first information.
[0353] In some instances, the first information may indicate (or include) calculation of the Vmeasure (fk) H ABS (φ) , when the first information is derived using DFT (i.e., the first implementation that generates the first information) .
[0354] In some instances, the first information may indicate (or include) Vmeasure (fk) , when the projection Vmeasure (fk) H ABS (φ) can be approximately substituted by the Vmeasure (fk) (i.e., the second implementation that generates the first information) .
[0355] In some instances, the first information may include part or all of the parameters corresponding to r sub-channel (s) (i.e., vmeasure_1, vmeasure_2, …, vmeasure_r in the right singular matrix Vmeasure) .
[0356] For example, the first information may include Npath set (s) of parameters corresponding to Npath sub-channel (s) , the Npath sub-channel (s) is selected from r sub-channel (s) , Npath and r are positive integers and Npath is less than or equal to r.
[0357] Where, the Npath sub-channel (s) can be selected from r sub-channel (s) by a selection process above.
[0358] Notably, as aforementioned, when the ED selects the LOS and one-bounce NLOS sub-channels by the selection process, the Npath may be equal to 2, where “r” is the rank of the channel matrix.
[0359] In some instances, a set of parameters corresponding to a sub-channel may include one or more of:
[0360] index information of part or all of the S associated with the sub-channel;
[0361] path loss information associated with the sub-channel; and
[0362] time delay information associated with the sub-channel.
[0363] Where, the index information of part or all of the S associated with the sub-channel may indicate the angle of departure of the sub-channel. For example, this is the index of the angle φ corresponding to the non-zero element in the sparse vector s' (fk) associated with the spatial signature vmeasure (fk) in the virtual planar screen.
[0364] The path loss information associated with the sub-channel may indicate path loss of the sub-channel. For example, this is the singular value σmeasure_i (fk) obtained from the SVD decomposition, representing the path loss or gain of the sub-channel.
[0365] The time delay information associated with the sub-channel may indicate the propagation delay of the sub-channel. For example, this is the estimated relative delay τi of the sub-channel, which is calculated from the time-domain channel impulse response.
[0366] In some implementations, the first information further indicates one or more of: a location of the ED, an orientation of the ED, and a configuration of receive antennas corresponding to the reference signal. These parameters can help the BS to construct an RF 4D map with better performance.
[0367] In some implementations, the first information is used to predict the channel state associated with the part or all of the S. For example, the ED and / or the BS may utilize a machine learning algorithm to predict path loss and angular information based on historical data collected via reference signal. This may incorporate advanced data processing techniques to enhance the predictive accuracy and efficiency of the system, aligning with cutting-edge technological practices.
[0368] The ED can obtain the parameter (s) that used for generating the first information in a variety of ways. In some implementations, the parameter (s) may be signaled by a network device (e.g. base station) dynamically, e.g. in physical layer control signaling such as DCI, or semi-statically, e.g. in radio resource control (RRC) signaling or in the medium access control (MAC) layer; or be predefined based on the application scenario; or be determined by the ED as a function of other parameters that are known by the ED; or may be fixed, e.g. by a standard; or a combination thereof. This is not limited to this application. If the part or all of the parameter (s) are signaled by the BS, the ED and the BS may further perform the step 1330 before step 1320.
[0369] Optionally, at step 1330, the BS transmits second information to the ED. Correspondingly, the ED receives the second information from the BS.
[0370] The second information indicates part or all of the configuration of transmit antennas. As aforementioned in step 1320, the part or all of the configuration of the transmit antennas can be used to generate the first information. The parameters included in the second information are related to the implementation that generate the first information.
[0371] In some instances, the second information indicates the transmit array response matrix At (φ) of the transmit antenna. For example, the BS may determine that the first information is derived using DFT. The second information may indicate the transmit array response matrix At (φ) , so that the ED may calculate Vmeasure (fk) H At (φ) to generate the first information.
[0372] In some instances, the second information indicates parameters related to the reference locations (i.e., the virtual planar screen data described in step 1320) . For example, the BS may determine that the first information is generated based on the virtual planar screen data. The second information may indicate the virtual planar screen data, so that the ED can generate the first information based on the virtual planar screen data.
[0373] As aforementioned, the virtual planar screen data may include a set of vectors corresponding to the angle (s) from the transmit antenna to the reference locations (e.g., a set of vectors v1 (φazimuth, φelevation) ) and / or a set of first thresholds (e.g., corresponding scalar values σ1 (φazimuth, φelevation) ) . A detailed of description the above parameters can be found in step 1320.
[0374] Virtual planar screens are conceptual representations used in wireless communication systems. These virtual planar screen data may be structured or standardized as tabular or vector forms, where each entry or item corresponds to a specific combination of parameters or conditions.
[0375] For example, consider a virtual planar screen associated with a particular frequency (fk) , temperature, and humidity. In this case, the azimuth angle (φazimuth, ) represents the x-direction of the table, while the elevation angle (φelevation) constitutes the y-direction. Each table entry is a vector of size (NBS × 1) , containing a complex-valued spatial signature (v) and a scalar value (σ) representing the corresponding path loss or channel gain.
[0376] For another example, this table can be extended into a vector, where each element contains a complex-valued spatial signature vector (v) and a scalar value (σ) associated with a specific angle (φ) or a combination of azimuth and elevation angles.
[0377] The virtual planar screen data indicated by the second information may be represented in a variety of forms. For example, the virtual planar screen may be represented by a matrix, a table, a set of parameters or a combination thereof.
[0378] The second information may indicate part or all of the virtual planar screen data. The BS may determine the parameters indicated by the second information in a variety of ways.
[0379] In certain scenarios, the BS may not need to transmit the entire set of virtual planar screen tables to the ED. This flexibility can be leveraged to optimize resource utilization and reduce overhead, particularly when the ED has limited capabilities or when only coarse location information about the ED is available.
[0380] In some instances, the parameters indicated by the second information may be related to one or more of: a location of the ED, a capability of the ED and an orientation of the ED.
[0381] For example, the BS may select part of the virtual planar screen data based on the location of the ED. Based on the location of the ED, the BS may determine some candidate angles of departure that may correspond to the LOS path or one-bounce path between the BS and the ED. Therefore, the BS may indicate the part of the virtual planar screen data associated with the candidate angles of departure. The transmission consumption of the second information can be reduced. Notably, this part of virtual planar screen data may be referred to as selected virtual planar screen data hereinafter.
[0382] Notably, the BS can have multiple virtual planar screen tables, each tailored to different environmental conditions, frequency bands, or other relevant factors.
[0383] When an ED participating in 4D RF Map reconstruction enters the coverage area of a BS, the BS explores the current environment based on factors such as temperature, humidity, and available spectrum points (subcarriers) . The corresponding virtual planar screen tables, which encapsulate the channel information for the specific conditions, are then transmitted to the ED through a downlink channel.
[0384] For example, the orientation of the ED may be used to determine the trajectory of the ED, and the BS may select the virtual planar screen data based on the trajectory.
[0385] For example, the capability of the ED may include processing power, memory (storage capability) , bandwidth constraints, etc. The BS may determine the part of the virtual planar screen data indicated by the second information. Exemplary, the BS may determine the size of the part of the virtual planar screen data based on the capability of the ED (e.g., storage capability) . This is not limited to this application.
[0386] Additionally, if the BS has access to coarse location information about the ED, such as its approximate position or sector within the cell, it can further optimize the transmission of virtual planar screen tables. In this case, the BS may transmit only the table information corresponding to the ED's approximate location, omitting tables that are less likely to be relevant or useful for the ED's current context.
[0387] Moreover, in some instances, the BS can employ sampling techniques to reduce the amount of data transmitted for each virtual planar screen data (e.g., table) . Instead of sending the complete table, the BS can transmit table information sampled at regular intervals or based on specific criteria, such as angle ranges or spatial signatures with higher significance. This approach can effectively reduce the overhead while still providing the ED with sufficient information to reconstruct the 4D RF Map accurately.
[0388] In some cases, the BS may also choose to omit certain components of the virtual planar screen tables, such as the scalar path loss or channel gain values (σ) . This further reduction in transmitted data can help optimize the downlink resource utilization.
[0389] In addition to selectively transmitting virtual planar screen tables or sampling their information, the BS can leverage various compression technologies to further reduce the downlink overhead associated with transmitting these tables or vectors. The inherent structure and spatial correlation present in the virtual planar screen tables make them amenable to efficient compression techniques.
[0390] One approach the BS can employ is Principal Component Analysis (PCA) , a dimensionality reduction technique that identifies the most significant principal components or eigenvectors of the virtual planar screen data. By transmitting the coefficients corresponding to the dominant principal components, the BS can achieve substantial compression while retaining the main characteristics of the virtual planar screen tables.
[0391] Another compression technique that the BS can utilize is low-bit quantization. Since the virtual planar screen tables typically consist of complex-valued spatial signatures and scalar path loss or channel gain values, the BS can quantize these values using a lower number of bits while still maintaining a sufficient level of accuracy. This quantization process can significantly reduce the bit rate required for transmitting the virtual planar screen tables, thereby optimizing the downlink resource usage.
[0392] Furthermore, the BS can explore advanced compression algorithms specifically designed for the virtual planar screen data structure. These algorithms can leverage the spatial and angular correlations present in the tables, as well as any sparsity or redundancy in the data, to achieve even higher compression ratios.
[0393] If there are multiple subcarriers, implying the presence of multiple virtual planar screen tables, it is important to consider the gradual but persistent changes that occur from one subcarrier to another. In such scenarios, compression techniques that jointly encode the tables or vectors across multiple subcarriers are recommended. By exploiting the inter-subcarrier correlations and redundancies, these compression methods can further improve the overall compression efficiency, leading to even greater reductions in downlink overhead.
[0394] However, it is important to note that the effective utilization of these compression technologies may require the pre-definition of standard protocols or formats for representing and transmitting the compressed virtual planar screen data. Standardization efforts would ensure interoperability between different BS and ED implementations, enabling seamless communication and reconstruction of the 4D RF Map.
[0395] The compression technologies described above are only for illustrative purposes. This application does not exclude other possible compression technologies. Notably, these compression technologies may be applied to any information transmitted by the BS or the ED (e.g., first information) . This is not limited to this application.
[0396] The BS can transmit the second information in a variety of ways. For example, the second information may be carried in PDSCH (s) , PDCCH (s) , physical broadcast channel (PBCH) , or a combination thereof. Exemplary, the selected virtual planar screen data may be carried in the PDSCH (s) or PDCCH (s) , and the proportion threshold may be carried in PBCH. This is not limited to this application.
[0397] In some implementations, the BS transmits the second information based on the selected virtual planar screen data. For example, the BS may determine whether the size of the selected virtual planar screen data is larger than or equal to a size threshold. When the size of the selected virtual planar screen data is larger than or equal to the size threshold, the BS may determine to transmit the selected virtual planar screen data via one or more PDSCHs; When not, the BS may determine to transmit the selected virtual planar screen data via one or more PDCCHs.
[0398] In some implementations, as aforementioned in step 1320, a second threshold may be used to perform a selection process. In this case, the second information may further include an indication of the second threshold (i.e., the proportion threshold) .
[0399] In addition to transmitting the virtual planar screen table (s) or vector (s) , the related control signaling from the BS to the ED further includes information for 4D RF Map reconstruction. This information encompasses the specific subcarrier (s) at which the BS requires the ED to complete channel measurement and feedback, as well as a preset proportion threshold.
[0400] The preset proportion threshold, which is a parameter used for the 4D RF map reconstruction process, can be transmitted by the BS to multiple EDs in a broadcast manner. This broadcast approach ensures that all EDs within the cell or coverage area receive the same proportion threshold value, enabling a consistent and coordinated reconstruction process.
[0401] One way to broadcast the proportion threshold is through system information blocks (SIBs) or other broadcast control channels, such as the physical broadcast channel (PBCH) or the physical downlink control channel (PDCCH) . The BS can include the proportion threshold value as part of the system information or control signaling, which is periodically broadcast to all EDs within the cell.
[0402] As aforementioned, the BS can determine the parameter (s) that are used for generating the first information in a variety of ways. In some implementations, the ED may report related information that can be used to determine the parameter (s) . That is, the ED and the BS may further perform step 1340 before step 1330.
[0403] Optionally, at step 1340, the ED transmits third information to the BS. Correspondingly, the BS receives the third information from the ED.
[0404] The third information may be used to determine the parameters. For example, the third information may indicate the location of the ED, the capability of the ED and the orientation of the ED. Thus, the BS can generate the second information based on the third information.
[0405] For instance, based on the ED's reported capabilities, such as processing power, memory, or bandwidth constraints, the BS can strategically transmit only a subset of the virtual planar screen tables that are most relevant or crucial for the ED's operations. This selective transmission can help conserve downlink resources while still providing the ED with the required channel information for 4D RF Map reconstruction.
[0406] According to the above technical solution, the ED and the BS may obtain the path loss characteristics and spatial characteristics based on the first information. In some implementations, the ED and / or the BS may adjust their operational parameters based on the first information. That is, the ED and the BS may further perform step 1350 and step 1360.
[0407] Optionally, at step 1350, the ED adjusts operational parameters#1 based on the first information.
[0408] The operational parameters#1 may be used for communication between the ED and the BS. This may optimize performance in variable signal conditions.
[0409] In some implementations, the operational parameters include one or more of: parameter (s) related to power settings, parameter (s) related to antenna configurations, and parameter (s) related to processing capabilities.
[0410] For example, the ED could be allowed to modify its settings based on the data received, which can maintain optimal performance in dynamic environments.
[0411] Optionally, at step 1360, the BS adjusts operational parameters#2 based on the first information.
[0412] The operational parameters#2 may be used for communication between the ED and the BS.
[0413] Notably, the BS may reconstruct the 4D RF map based on the first information from multiple EDs, so that the BS can adjust parameters#2 based on the 4D RF map.
[0414] In some implementations, the BS and the ED can loop the process of reconstructing a 4D RF map, so that the 4D RF map can follow the changes in the physical environment in real-time.
[0415] Notably, the virtual planar screen may be configured dynamically based on real-time data regarding the operating environment, including factors such as obstacles present, prevailing weather conditions, and expected changes in the ED’s location.
[0416] According to the foregoing method, the dynamic adjustment of the virtual planar screen settings is based on environmental data, which enhances the method’s adaptability and accuracy in real-world scenarios.
[0417] According to the above technical solution, the first information indicates angles of departure (as spatial characteristics) and associated path loss (as RF characteristics) . The spatial characteristics and the RF characteristics can be obtained based on the same reference signal in an efficient way.
[0418] The aim of this disclosure is to generate a 4D RF map from the first information (e.g., CSI feedback reports) sent from at least one ED to a base station (BS) .
[0419] The process may begin with the BS broadcasting a pre-built codebook to its associated at least one ED. Following this, the BS then transmits a set of reference signals (e.g. CSI reference signals) in the downlink. Upon receiving these signals, each ED estimates its downlink MIMO channel based on the received reference signals. One or more EDs may transform their estimated MIMO channels into another domain (e.g. angular domain) and then compare against the codebook entries to generate sensing CSI reports. The sensing CSI reports may include detailed part of ray-tracing information from the BS to the one or more EDs. The sensing CSI may be then fed back from the one or more EDs to the BS. After accumulating a sufficient number of sensing CSI reports, the BS may reconstruct the 4D RF map of the coverage area.
[0420] For ease of understanding implementations, some detailed examples are given in conjunction with FIGs. 14-31 for illustrative purposes.
[0421] As aforementioned in step 1310, the sensing CSI-RS may be configured to occupy an entire BWP in frequency domain. For ease of understanding embodiments of this application, an example of sensing CSI-RS configured in time-frequency domain is illustrated in FIG. 14.
[0422] FIG. 14 illustrates an example of the reference signal (e.g., CSI-RS) in the time-frequency domain according to this application.
[0423] As shown in FIG. 14, an example of Multi-BWP CSI-RS, 5 OFDM symbols (t1, t2, …, t5) are illustrated on the horizontal coordinate (i.e., time coordinate) , and 8 subcarriers (f1, f2, …, f8) are illustrated on the vertical coordinate (i.e., frequency coordinate) . The multi-BWP CSI-RS across multiple OFDM symbols covers the entire bandwidth.
[0424] The measurement subcarriers fk, k=1, 2, …are determined by the BS, which also transmits the virtual planar screen tables or vectors corresponding to these subcarriers. The ED measures the downlink frequency-domain channel H (fk) based on reference signals of a CSI-RS broadcast in a downlink channel.
[0425] As aforementioned in step 1320, the first information may indicate path loss and angles of departure of LOS path (s) and i-bounce NLOS path (s) (e.g., i=1) . For ease of understanding embodiments of this application, a schematic diagram of the LOS path (s) and 1-bounce NLOS are illustrated in FIG. 15.
[0426] FIG. 15 illustrates an example of LOS and one-bounce NLOS according to this application.
[0427] As shown in FIG. 15, the first information may indicate path loss and angles of departure LOS path, 1-bounce NLOS (1) path and 1-bounce NLOS (2) . Related information of 2-bounce NLOS (3) may be discarded for the first information.
[0428] The 4D environment reconstruction process primarily relies on capturing and leveraging the reflected propagation paths in the wireless channel. Among these reflected paths, the most valuable and accurate information is obtained from single-bounce reflections. These single-bounce reflections, where the signal undergoes only one reflection before reaching the ED, provide a clear and less distorted representation of the interactions between radio channel and environment characteristics.
[0429] In contrast, weaker propagation paths involving multiple reflections or diffracted components pose significant challenges for accurate reconstruction. Firstly, these multi-bounce reflected paths often experience substantial signal attenuation due to cumulative reflection losses, making it difficult to reliably estimate their contributions to the channel. Secondly, disentangling and reversing the effects of multiple reflections to reconstruct the environment becomes increasingly complex and prone to errors.
[0430] Consequently, it is advantageous to focus the RF-map-Reconstruction-purpose CSI feedback from the ED to the BS primarily on the direct LOS path and the high-quality single-bounce reflected paths. By concentrating the feedback on these dominant and more reliable components, the reconstruction process can accurately capture the key features of the propagation environment while reducing the impact of weaker, more challenging components.
[0431] As aforementioned in step 1320, the first information can be generated in a first implementation. For ease of understanding of embodiments of this application, a visualization of the projection of < Vmeasure (fk) , ABS (φ) > and < AED (θ) , Umeasure (fk) > is given in FIG. 16.
[0432] FIG. 16 illustrates a visualization of the projections of < Vmeasure (fk) , ABS (φ) > and < AED (θ) , Umeasure (fk) >according to this application.
[0433] The first information may include the calculation of Vmeasure (fk) H ABS (φ) , that is, the projections of < Vmeasure (fk) , ABS (φ) >. In some instances, the first information may further include the calculation of AED (θ) H Umeasure (fk) , that is, the projection of < AED (θ) , Umeasure (fk) >.
[0434] A visualization of the projection of <v1, ABS > and <AED, u1> is shown in the diagram on the left in FIG. 16. The “v1” represents the first column in Vmeasure (fk) , and the “u1” represents the first column in Umeasure (fk) . The received signal y=Hmeasurex+w, where Hmeasure represents channel matrix, x represents transmitted signal, w represents interference. The ED performs SVD decomposition on the Hmeasure, Hmeasure=Umeasure ∑measureVmeasure H, than pre-coder V (: , 1) (array of size M=m'n') , eigen-channel ∑measure (1, 1) , de-coder U (: , 1) (array of size N=mn) are obtained. The m, n, m', n' are positive integers herein.
[0435] Similarly, a visualization of the projection of <v2, ABS > and <AED, u2> is shown in the diagram on the middle in FIG. 16. The “v2” represents the second column in V (fk) , and the “u2” represents the second column in Umeasure (fk) . The ED performs the SVD decomposition on the Hmeasure, Hmeasure=Umeasure ∑Vmeasure H, than pre-coder Vmeasure (: , 2) , eigen-channel ∑ (2, 2) , de-coder Umeasure (: , 2) are obtained.
[0436] Similarly, a visualization of the projection of <v3, ABS > and <AED, u3> is shown in the diagram on the right in FIG. 16. The “v3” represents the third column in Vmeasure (fk) , and the “u3” represents the third column in Umeasure (fk) . The ED performs the SVD decomposition on the Hmeasure, Hmeasure=Umeasure ∑measureVmeasure H, than pre-coder Vmeasure (: , 3) , eigen-channel ∑measure (3, 3) , de-coder Umeasure (: , 3) are obtained.
[0437] As shown in FIG. 16, each column (eigen vectors) of Vmeasure (fk) projected on ABS (φ) [<vmeasure_1 (fk) , ABS (φ) ><v measure_2 (fk) , ABS (φ) > …<v measure_r (fk) , ABS (φ) >] and each column (eigen vectors) of U measure (fk) projected on AED (θ) [<AED (θ) , u measure_1 (fk) > <AED (θ) , u measure_2 (fk) > …<AED (θ) , u measure_2 (fk) >] in the case that the BS and the ED meet condition#1 (e.g., both ED and BS employs a typical URA antenna array panels) .
[0438] As aforementioned in step 1320, the first information can be generated in a first implementation. For ease of understanding of embodiments of this application, a visualization of the projection of an antenna’s range field of view (FOV) φazimuth from -π / 6 to 5π / 6 and φelevation from 0 to π / 2 is given in FIG. 17.
[0439] FIG. 17 illustrates an example of a projection on an antenna’s range φazimuth from -π / 6 to 5π / 6 and φelevation from 0 to π / 2.
[0440] In a MIMO system, an ED estimates the DL frequency-domain MIMO channel (H measure (fk) ) on a subcarrier fk. The ED then performs a rank-reduced SVD on H measure (fk) : H measure (fk) ≈ U measure (fk) Σmeasure (fk) V measure (fk) H.
[0441] In theory, the ED can project the right singular vectors V measure (fk) onto the transmit array response matrix ABS (φ) , where φ : = (φazimuth, φelevation) represents the 3D angle of departure with respect to the antenna panel plane.
[0442] For each column vmeasure_i (fk) , i=1, 2, ..., r, in Vmeasure (fk) , the projection vmeasure_i (fk) H At (φ) will exhibit a peak over the range φazimuth from -π / 6 to 5π / 6 and φelevation from 0 to π / 2, if for example the BS’s antenna panel is designed within this range. The (φ’azimuth, φ’ elevation) pair corresponding to this peak indicates the relative 3D angle of the path represented by vmeasure_i (fk) with respect to the antenna panel plane.
[0443] As aforementioned in step 1320, the first information can be generated in a third implementation. The first information may be derived using parameter related to a virtual planar screen. For ease of understanding embodiments of this application, an exemplary virtual planar screen is given in FIG. 18.
[0444] FIG. 18 illustrates multiple kinds of virtual planar screens according this application.
[0445] As shown in FIG. 18, the virtual planar screen can be flat, square, spherical, etc. Although not illustrated, this application does not exclude other possible shape of the virtual planar screen. Each small area (illustrated as black dot) may be considered as a reference location.
[0446] Notably, while the virtual screen is often referred to as a "planar screen, " it is not limited to a planar surface. Depending on the specific scenario and the desired level of accuracy, the virtual screen can be modeled as a spherical surface or other curved surfaces that better represent the propagation environment around the BS. This flexibility allows for more accurate characterization of the spatial channel properties, particularly in scenarios with significant elevation variations or three-dimensional propagation effects. However, regardless of the shape of the virtual screen, it is represented and processed in a manner similar to a virtual planar screen.
[0447] As aforementioned in step 1320, still referring to the third implementation, the virtual planar screen data may be associate with one or more factors. For ease of understanding embodiments of this application, an exemplary virtual planar screen data associated with a certain frequency is given in FIG. 19.
[0448] FIG. 19 illustrates virtual planar screen data associated with a certain frequency according to this application.
[0449] As aforementioned, the reference locations can be considered as locations (also referred to as small areas) on a virtual planar screen. The angle between the antennas of the BS and each small area can be represented by φ = (φazimuth, φelevation) .
[0450] To build a virtual planar screen, consider a completely open BS environment where the antennas of the base station emit signals within a fixed range of directions, for example, φazimuth from -π / 6 to 5π / 6 and φelevation from 0 to π / 2. Since the surroundings are free of obstacles, the emissions along all directions are LOS. At a certain distance from the BS, say 20 meters away, we can establish a virtual planar screen. On this screen, each small area corresponds to a specific BS transmission angle φ = (φazimuth, φelevation) that is geometrically mapped from the center of the antenna panel to that small area.
[0451] We can "virtually generate" the frequency-domain channel on the subcarrier fk at each small area, denoted as H (φazimuth, φelevation, fk) , and perform singular value decomposition (SVD) on it to extract the matrix of right singular vectors V (φazimuth, φelevation, fk) and the diagonal matrix of singular values Σ (φazimuth, φelevation, fk) . Since there are no reflections, there is only one radio ray path, and the V (φazimuth, φelevation, fk) matrix has only one column, namely v1 (φazimuth, φelevation, fk) . We store this v1 (φazimuth, φelevation, fk) and its corresponding singular value σ1 (φazimuth, φelevation, fk) in the corresponding small area associated with (φazimuth, φelevation, fk) .
[0452] By repeating this process for all small areas on the virtual planar screen, we can create a spatial map of the singular vectors v1 (φazimuth, φelevation, fk) and the singular values σ1 (φazimuth, φelevation, fk) for the entire range of angles covered by the BS antenna panel. This spatial map represents the spatial signatures and the corresponding singular values of the LOS paths from the base station to different locations on the virtual screen, effectively capturing the angle-dependent characteristics of the propagation channel.
[0453] The resolution of the virtual planar screen, or spatial map, represented by the angular resolution or granularity of φ = (φazimuth, φelevation) , depends on several factors related to the base station (BS) antenna array panel configuration. As mentioned earlier, a larger number of transmit antennas (NBS) at the BS translates to higher angular resolution, enabling a finer granularity of the virtual planar screen. This is because more antennas provide improved spatial sampling of the propagation channel, allowing for better differentiation between closely spaced angles of arrival / departure.
[0454] Additionally, the angular resolution is influenced by the wavelength (λ) of the carrier frequency. A shorter wavelength implies that the spacing between antenna elements, typically set to λ / 2 or greater, becomes smaller, resulting in higher angular resolution for the same number of antennas.
[0455] As aforementioned in step 1320, still referring to the third implementation, the BS may build may build a virtual planar screen for every one or more frequency units. For ease of understanding embodiments of this application, a schematic diagram of virtual planar data associated with multiple frequencies is given in FIG. 20.
[0456] FIG. 20 illustrates an example of building two virtual planar screens for two distance subcarriers according to this application.
[0457] As shown in FIG. 20, the operating frequency of the BS may include subcarriers f1, f2, …, fk, …The frequency is a main factor that affects the path loss, so that the BS may build multiple virtual planar screens corresponding to different frequencies. The BS may build a virtual planar screen for every few sub-carriers. For example, the BS may build a virtual planar screen#1 for subcarriers f1, and build a virtual planar screen#2 for subcarriers fk. The subcarriers f1, f2, …, fk-1 could share the virtual planar screen#1, and the subcarriers fk, fk+1, …, f2k-1 could share the virtual planar screen#2. The distance between the subcarriers f1 to subcarriers fk can be designed in a variety of ways. For example, it can be designed based of calculation power of the BS, the range of the subcarriers, etc. This is not limited to this application.
[0458] As aforementioned in step 1320, still referring to the third implementation, the ED may perform a selection process to generate the first information. For ease of understanding embodiments of this application, a schematic flow chart of a selection process is given in FIG. 21.
[0459] FIG. 21 illustrates an example of a selection process according to this application.
[0460] Now, let us assume that the BS specifies that the ED should perform channel measurements for sensing purposes on the subcarrier fk. Additionally, the ED has previously obtained a table or a vector representing the corresponding virtual planar screen at the subcarrier fk, which encapsulates the channel information for that specific subcarrier.
[0461] At step 1: The ED performs SVD on channel matrix Hmeasure (fk) to get right singular matrix Vmeasure= [v measure_1 (fk) , v measure_2 (fk) , …] and singular values∑= [σmeasure_1 (fk) , σmeasure_2 (fk) , ... ] .
[0462] At step 2: For each MIMO subchannel i∈ {1, 2, …} , the ED compares σmeasure_i (fk) with the range of σ (fk) prestored in planar screen data.
[0463] At step 3: The ED determines whether σmeasure_i (fk) is smaller than or equal to scalar values σ (fk) by multiple orders.
[0464] When the ED determines that σmeasure_i (fk) is smaller than or equal to scalar values σ (fk) by multiple orders in step 3, the ED performs the step 4.
[0465] At step 4: The ED discards this subchannel i as it is unreliable for 4D RF map reconstruction.
[0466] When the ED determines that σmeasure_i (fk) is not smaller than or equal to scalar values σ (fk) by multiple orders in step 3, the ED performs the step 5.
[0467] At step 5: The ED retains this subchannel i. After checking all MIMO subchannels in H measure (fk) and obtaining all retained subchannels j∈ {1, 2, …} , the ED calculates the ratio between singular value of each retained subchannel σmeasure_j (fk) and LOS component σ1.
[0468] At step 6: The ED determines whether the ratio of considered subchannel j is smaller than or equal to a given threshold λ.
[0469] When the ED determines that the ratio of considered subchannel j is smaller than or equal to the propagation threshold λ, the ED performs the step 7.
[0470] At step 7: The ED discards this subchannel j as it is likely to be higher order scattering component.
[0471] When the ED determines that the ratio of considered subchannel j is not smaller than or equal to the propagation threshold λ, the ED performs the step 8.
[0472] At step 8: The ED retains this subchannel j. After processing with all subchannels and obtaining retained channels m∈ {1, 2, …} , all v measure_m (fk) and σmeasure_m (fk) correspond to LOS and single-bounce NLOS components, which can be used to generate the first information.
[0473] As aforementioned in step 1320, still referring to the third implementation, the first information may be generated based on an optimization process. For ease of understanding embodiments of this application, a schematic diagram of the optimization process is given in FIG. 22.
[0474] FIG. 22 illustrates an example of an optimization process according to this application.
[0475] As shown in FIG. 22, an example of vi (fk) ≈Ψ (fk) s (fk) and sparse optimization. As aforementioned, the virtual planar screen data (e.g., the spatial signature matrix) can be represented using a matrix Ψ (fk) . The sensing ED may perform rank-reduced SVD on Hmeasure (fk) to obtain a right singular matrix Vmeasure (fk) . v measure_i (fk) ≈Ψ (fk) s (fk) , where s (fk) is Nφ × 1 vector indicating which columns are used for the linear fitting.
[0476] The ED may find a vector s such that: α min (|| vmeasure_i (fk) -Ψ (fk) s (fk) ||2) +β min (| s (fk) |) , where α and β are optimization parameters. The result of the optimization is a highly sparse vector s', which indicates the transmission angles of the rays from the BS side within the cluster of rays corresponding to the spatial signature v measure i.
[0477] Theoretically, the non-zero scalar values in s' (fk) represent the projections of vmeasure_i (fk) onto the column vectors of the matrix Ψ (fk) indicated by the non-zero elements of s' (fk) (inner products) . These scalar results represent the channel gain (or path loss) distribution of each ray within the MIMO sub-channel vmeasure_i (fk) across the cluster of rays. Strictly speaking, the ED needs to send the angles and the corresponding scalar values indicated by the non-zero elements of s' (fk) to the BS, enabling the BS to reconstruct the 4D RF Map accurately. However, considering that there may be several MIMO sub-channels, directly transmitting all this information would result in a large number of uplink CSI reports.
[0478] Another issue with the direct optimization of α min (|| vmeasure_i (fk) -Ψ (fk) s (fk) ||2) +β min (| s (fk) |) is the time-consuming and computationally complex nature of the process, which may be challenging for resource-constrained EDs.
[0479] Therefore, based on practical considerations, we recommend the following simplified algorithm. This is why the information about the virtual planar screen configured by the BS in advance contains the proportion threshold λ and a feature value σ.
[0480] As aforementioned in step 1320, still referring to the third implementation, the first information may be generated based on a selection process and an optimization process. For ease of understanding embodiments of this application, a schematic diagram of the optimization process is given in FIG. 23.
[0481] FIG. 23 illustrates an example of a selection process and an optimization process according to this application.
[0482] As shown in FIG. 23, an example of using inner product for maximum detection to replace sparse optimization for feasible complexity. The sensing ED may perform rank-reduced SVD on Hmeasure (fk) to obtain a right singular matrix Vmeasure (fk) . v measure_i (fk) ≈Ψ (fk) s (fk) , where s (fk) is Nφ × 1 vector indicating which columns are used for the linear fitting. Then, the ED may perform a selection process (represented by ) . For the remaining MIMO sub-channels v measure_i (fk) (including the LOS and single-bounce NLOS sub-channels) , the entire "optimized α min (||v measure_i (fk) -Ψ (fk) s (fk) ||2) +β min (| s (fk) |) " problem becomes a simpler task of "finding the column of the matrix Ψ (fk) whose inner product with v measure_i (fk) is the largest (represented by ) , and thus the correspondingv1 (Φmax, fk) , Φmax, σmax.
[0483] As aforementioned in step 1320, the first information may further indicate propagation delay (s) associated with the reference signal. For ease of understanding embodiments of this application, an example of obtaining the propagation delay (s) is illustrated with FIG. 24.
[0484] FIG. 24 illustrates an example of a selection process and a delay process estimation according to this application.
[0485] As shown in FIG. 24, an example of transforming on time-domain to detect the delays for MIMO subchannels respectively. For example, consider a MIMO channel H (fk) at a subcarrier fk, which is decomposed into r MIMO sub-channels: Hmeasure (fk) ≈Umeasure (fk) Σmeasure (fk) Vmeasure (fk) H. In this case, the ED can separate the frequency-domain representations of these independent MIMO sub-channels: Hmeasure_1 (fk) = umeasure_1 (fk) σmeasure_1 (fk) vmeasure_1 (fk) H, Hmeasure_2 (fk) = umeasure_2 (fk) σmeasure_2 (fk) vmeasure_2 (fk) H…
[0486] Similarly, the ED obtains Hmeasure_1 (fkk) = umeasure_1 (fkk) σmeasure_1 (fkk) vmeasure_1 (fkk) H, Hmeasure_2 (fkk) =u measure_2 (fkk) σmeasure_2 (fkk) vmeasure_2 (fkk) H…at a different subcarrier fkk. By repeating this process across multiple subcarriers, the ED can obtain a full-bandwidth frequency-domain representation of the two MIMO sub-channels: [H1 (fk) 0 …0 H1 (fkk) 0 …0 H1 (fkkk) ... ] , [H2 (fk) 0 …0 H2 (fkk) 0 …0 H2 (fkkk) ... ] … (not illustrated) .
[0487] The ED can perform IDFT operation on [H1 (fk) 0 …0 H1 (fkk) 0 …0 H1 (fkkk) ... ] , [H2 (fk) 0 …0 H2 (fkk) 0 …0 H2 (fkkk) ... ] …respectively, to obtain time domain channel impulse responses h1 (t) , h2 (t) …Where, a schematic diagram of h1 (t) is given in the FIG. 24. Then the ED may combine the h1 (t) , h2 (t) …to obtain h (t) as illustrated in FIG. 24.
[0488] When identifying the corresponding angles of the remaining MIMO sub-channels on the virtual planar screen, the ED needs to estimate the delay of each remaining MIMO sub-channel. This delay estimation is crucial because the ED completes the full-bandwidth measurement by utilizing a reference signal from the CSI-RS of the configured bandwidth part (BWP) . The ED can perform delay estimation more accurately by combining the MIMO sub-channels separated from different subcarriers. Although the path loss due to reflection may vary across different subcarriers, the angle of the ray path remains the same.
[0489] Notably, although not illustrated, the ED may perform a selection process before delay estimation. For example, the ED may select two sub-channels that reflect the LOS and the single-bounce NLOS components. Then the ED could perform IDFT on the two sub-channels respectively, reducing the process complicity on ED side.
[0490] As aforementioned in step 1320, a set of parameters included in the first information corresponding to a subchannel may include a variety of related parameters. For ease of understanding embodiments of this application, an exemplary first information is illustrated in FIG. 25.
[0491] FIG. 25 illustrates an example of the first information according to this application.
[0492] As shown in FIG. 25, an example of a sensing-purpose CSI feedback content data structure. As aforementioned, the ED may select Npath sub-channels from the r sub-channels by a selection process. Here, Npath=2 is taken as an example, where the ED selects the LOS and one-bounce NLOS sub-channels.
[0493] So far, the ED has prepared the required content for CSI feedback to support 4D RF Map reconstruction. According to the control commands from the BS, the ED could feedback CSI related to 4D RF Map reconstruction on a specified subcarrier fk, which includes the following information:
[0494] The number of valid paths (Npath) : This is the number of MIMO sub-channels remaining after the two selection steps, representing the LOS and single-bounce NLOS components.
[0495] Estimated transmitting angle of the first MIMO sub-channel on the BS side: This is the index of the angle φcorresponding to the non-zero element in the sparse vector s' (fk) associated with the spatial signature v (fk) in the virtual planar screen.
[0496] Estimated path loss on the first MIMO sub-channel: This is the singular value σ1 (fk) obtained from the SVD decomposition, representing the path loss or gain of the LOS or single-bounce NLOS component.
[0497] Estimated path delay of the first MIMO sub-channel: This is the estimated relative delay τ1 of the first MIMO sub-channel, calculated from the time-domain channel impulse response.
[0498] Estimated transmitting angle of the second MIMO sub-channel on the BS side: Similar to the first sub-channel, this is the index of the angle φ corresponding to the non-zero element in the sparse vector s' (fk) associated with the spatial signature v (fk) in the virtual planar screen.
[0499] Estimated path loss on the second MIMO sub-channel: This is the singular value σ2 (fk) obtained from the SVD decomposition, representing the path loss or gain of the second LOS or single-bounce NLOS component.
[0500] Estimated path delay of the second MIMO sub-channel: This is the estimated relative delay τ2 of the second MIMO sub-channel, calculated from the time-domain channel impulse response.
[0501] By analogy, the CSI feedback includes the relevant information for all Npath MIMO sub-channels retained after the selection process.
[0502] If available, ED configuration information (e.g., ED location, orientation, antenna configurations…) to enhance the reconstruction performance.
[0503] It's important to note that the BS may require the ED to feedback CSI for 4D RF Map reconstruction on additional subcarriers, such as fkk. In such cases, the ED can leverage the same path delay estimations for the corresponding MIMO sub-channels across different subcarriers. This is because, although the path loss may vary due to frequency-selective fading, the propagation delays of the LOS and single-bounce NLOS components remain consistent across the considered subcarriers.
[0504] As aforementioned in step 1330, the virtual planar screen data indicated by the second information may be represented in variety of forms. For ease of understanding embodiments of this application, the virtual planar screen data in a form is illustrated in FIG. 26.
[0505] FIG. 26 illustrates an example of the virtual planar screen data according to this application.
[0506] As shown in FIG. 26, an example of virtual planar screen in form a matrix.
[0507] The virtual planar screen data (i.e., the parameters related to the locations) may include a set of vectors and a set of first thresholds. The set of vectors are spatial signature vectors v1 (Φ [1] , fk) , v1 (Φ [2] , fk) , …, v1 (Φ [NΦ] , fk) corresponding to angles of departure Φ [1] , Φ [2] , …, Φ [NΦ] . The set of vectors could form a matrix Ψ [fk] with NΦ rows and NBS columns. The NΦ is a positive integer and represents the number of the angles, and the NBS is a positive integer and represents the number of antennas of the BS. Each angle of departure Φ [i] can be represented by azimuth and elevation Φ [m] azimuthΦ [n] elevation, where “m” is azimuth value and “n” is elevation value. The set of first thresholds are the scalars σ1 (Φ [1] , fk) , σ1 (Φ [2] , fk) , …, σ1 (Φ [NΦ] , fk) corresponding to angles of departure Φ [1] , Φ [2] , …, Φ [NΦ] .
[0508] As aforementioned in step 1330 and step 1340, the BS may transmit part of the virtual planar screen data to the ED. For ease of understanding embodiments of this application, the part of the virtual planar screen is illustrated in FIG. 27.
[0509] FIG. 27 illustrates an example of transmitted virtual planar data based on the location of the ED according to this application.
[0510] As shown in FIG. 27, if the BS knows a coarse location of the ED, it sends the appropriate portion of the virtual planar screen relevant to that location. The BS can determine the angles of departure of possible LOS paths and one-bounce NLOS paths based on a location of the ED. Thereby, the BS may transmit the part of virtual planar screen data corresponding to the angles of departure.
[0511] As aforementioned in step 1330, the BS may transmit the second information based on the size of the selected virtual planar screen data. For ease of understanding embodiments of this application, a schematic flow chart of the transmission mechanism is given in FIG. 28.
[0512] FIG. 28 illustrates an example of BS transmitting the virtual planar screen data to an ED according to this application.
[0513] When an ED enters considered cell or associates with the considered BS:
[0514] At step 1: the BS determines whether the ED participates 4D RF map reconstruction.
[0515] When the BS determines that the ED does not participate 4D RF map reconstruction in step 1, the BS will not transmit the virtual planar screen to the ED, this process is terminated.
[0516] When the BS determines that the ED participates 4D RF map reconstruction in step 1, the BS will perform the step 2.
[0517] At step 2: the BS determines that whether the size of selected planar screen data is larger than or equal to a size threshold.
[0518] When the BS determines that the size of selected planar screen data is larger than the size threshold in step 2, the BS will perform the step 3.
[0519] At step 3: the BS schedules dedicated downlink resources with the ED and transmit the selected planar scree as data payload through a PDSCH, and this process is terminated.
[0520] When the BS determines that the size of selected planar screen data is not larger than the size threshold in step 2, the BS will perform the step 4.
[0521] At step 4: the BS packs the selected virtual screen data into downlink control information and transmit via a PDCCH, and this process is terminated.
[0522] The virtual planar screen table (s) or vectors can be transmitted to the ED through various downlink control channels or dedicated data channels, depending on the specific wireless communication standard and system configuration.
[0523] One common approach is to use downlink control channels, such as the PDCCH and PDSCH in 5G NR, to convey the virtual planar screen table (s) to the ED.
[0524] In this approach, the BS can encode the virtual planar screen table (s) or vector (s) as control information and transmit it to the ED using the downlink control channels. Alternatively, if the virtual planar screen table (s) are large or require more bandwidth, the BS can transmit them using dedicated data channels, such as the PDSCH in 5G NR. In this case, the BS can schedule dedicated resources for the ED and transmit the virtual planar screen table (s) as part of the downlink data payload. The table information can be encapsulated in a predefined message format or protocol, ensuring that the ED can correctly interpret and reconstruct the virtual planar screen table (s) or vector (s) upon reception.
[0525] As aforementioned in step 1330 and step 1340, the ED may transmit third information that can be used to generate second information. For ease of understanding embodiments of this application, an exemplary flow chart (as an example of step 1340 and step 1330) is illustrated with FIG. 29.
[0526] FIG. 29 illustrates an example of the transmission of the second information and the third information according to this application.
[0527] As shown in FIG. 29, an example of an ED sending its capability to the BS, and the BS sending the ED the proper virtual planar screen (s) . The ED may construct a sensing report with its capability description, and send the report (as an example of the third information) to the BS. Based on the report, the BS may tailor the virtual planar screens with relevant frequencies, suitable parameters, and virtual screen resolution, etc. The BS can send the selected / processed subset of the planar screens (as an example of second information) via PDCCH / PDSCH.
[0528] As aforementioned in step 1350 and step 1360, the BS and the ED can loop the process of reconstructing 4D RF map, so that the 4D RF map can follow the changes in the physical environment in real time. For ease of understanding embodiments of this application, an exemplary flow chart (as an example performed after the 4D RF map constructed (step 1320) ) is illustrated with FIG. 30.
[0529] FIG. 30 illustrates an example that the BS and the ED reconstruct the 4D RF map according to this application.
[0530] When an ED enters considered cell or associates with the considered BS:
[0531] At step 1: the BS determines whether the ED participates 4D RF map reconstruction.
[0532] When the BS determines that the ED does not participate 4D RF map reconstruction in step 1, the BS will continue to proceed with regular operations, this process is terminated.
[0533] When the BS determines that the ED participates 4D RF map reconstruction in step 1, the BS will perform the step 2.
[0534] At step 2: BS includes related parameters for 4D RF map reconstruction, e.g., required subcarriers for sensing CSI feedback and preset proportion threshold in MIB / SIB and broadcasts to ED through PBCH / PDSCH.
[0535] At step 3: ED receives MIB / SIB on PBCH / PDSCH and records / updates the essential parameters for 4D RF map reconstruction.
[0536] At step 4: In subsequent operations, ED computes sensing CSI from complete CSI information using the received parameters and virtual screens. ED sends sensing CSI report to BS.
[0537] At step 5: the BS determines whether related parameters for reconstruction changed / updated.
[0538] When the BS determines that the related parameters for reconstruction changed / updated, the BS and ED reperform step 2. That is, the BS may transmit changed / updated related parameters to the ED, so that the ED generates sensing CSI report based on changed / updated related parameters.
[0539] When the BS determines that the related parameters for reconstruction do not change / update, the BS and ED reperform step 4. The ED keep generating sensing CSI report based on obtained related parameters.
[0540] As aforementioned in FIG. 13, the first information (e.g., sensing CSI feedback) can be used to construct a 4D RF map. For ease of understanding embodiments of this application, an example of 4D RF map is illustrated in FIG. 31.
[0541] FIG. 31 illustrates an example of simulation results on 4D RF map reconstruction by BS receiving a lot of CSIs according to this application.
[0542] When a large number of EDs or a single ED is located at multiple locations, the aforementioned CSI is fed back to the BS, enabling the BS to construct a comprehensive 4D RF Map. The specific algorithm used for constructing the 4D RF Map is not the primary focus of this patent, as there can be different implementations and techniques employed for this purpose.
[0543] It is important to note that in certain scenarios, the ED may not have suitable CSI available for feedback. For example, if the ED is experiencing poor channel quality, no MIMO sub-channel may pass the preliminary selection process. It is also possible that the CSI feedback from the ED contains only a single MIMO sub-channel. From the perspective of a single ED report, the lack of such information alone cannot complete the RF Map reconstruction process. However, from the BS's perspective, it obtains thousands of CSI feedback reports from multiple EDs.
[0544] In fact, the reconstruction process itself becomes an over-determined optimization problem, where the BS can leverage the collective information from various CSI feedback reports to reconstruct an accurate 4D RF Map. This redundancy and diversity of information from multiple EDs and locations provide robustness and reliability to the reconstruction process.
[0545] For each CSI feedback on the fk subcarriers, the BS will determine whether the paths of both the LOS and the one-bounce NLOS components exist simultaneously. If both components are present, the BS can estimate the following:
[0546] The distance between the transmission point (ED location) and the BS, based on the path delays of the LOS and one-bounce NLOS components.
[0547] The direction of the reflector responsible for the single-bounce NLOS component, based on the transmitting angles of the two paths from the BS and the delay difference between them.
[0548] The path loss introduced by the reflection point, estimated based on the relative loss of the single-bounce NLOS eigenvalue compared to the LOS eigenvalue.
[0549] From this information, the BS can obtain detailed RF information about the reflection point, including:
[0550] Its location in 3D space, derived from the distance and direction estimates;
[0551] Its orientation in 3D space, based on the angle of incidence and reflection; and
[0552] The path loss at the frequency fk, depending on the angle of incidence at the reflection point.
[0553] Furthermore, since the CSI feedback may include measurements on multiple subcarriers, the BS can construct a more comprehensive RF profile of the reflection point, encompassing:
[0554] Its location in 3D space;
[0555] Its orientation in 3D space; and
[0556] The distribution of path loss over a range of frequencies, depending on the angle of incidence.
[0557] The frequency-dependent path loss distribution effectively provides a spectral analysis of the reflection point, which can theoretically enable the inference of the surface material information at that location. This spectral information can be valuable for enhancing the accuracy and granularity of the reconstructed 4D RF Map.
[0558] The methods according to embodiments of this application are described above in detail with reference to FIGS. 13-31. The apparatuses provided in embodiments of this application are described below in detail with reference to FIGS. 13-31. The description of apparatus embodiments corresponds to the description of the method embodiments. Therefore, for content that is not described in detail, refer to the foregoing method embodiments. For brevity, details are not described herein again.
[0559] Referring to FIG. 32, a schematic block diagram of a communication apparatus according to an embodiment of this application is shown. The communication apparatus 10 includes a transceiver unit 11 and a processing unit 12. The transceiver unit 11 may implement a corresponding communication function, and the processing unit 11 is configured to perform data processing. The transceiver unit 11 may also be referred to as a communication interface or a communication unit.
[0560] In some embodiments, the communication apparatus 10 may further include a storage unit. The storage unit may be configured to store instructions and / or data. The processing unit 12 may read instructions and / or data in the storage unit, to enable the communication apparatus to implement the foregoing method embodiments.
[0561] The communication apparatus 10 may be configured to perform actions performed by the ED in the foregoing method embodiments. In this case, the communication apparatus 10 may be the ED or a component that can be configured in the ED. The transceiver unit 11 is configured to perform communicating-related (e.g., receiving / transmitting-related) operations on the ED side in the foregoing method embodiments. The processing unit 12 is configured to perform processing-related operations on the ED side in the foregoing method embodiments.
[0562] The communication apparatus 10 may implement steps or procedures performed by the ED in FIGS. 13-31 according to embodiments of this application. The communication apparatus 10 may include units configured to perform the method performed by the ED in FIGS. 13-31. In addition, the units in the communication apparatus 10 and the foregoing other operations and / or functions are separately used to implement corresponding procedures in FIGS. 13-31.
[0563] Alternatively, the communication apparatus 10 may be configured to perform actions performed by the base station in the foregoing method embodiments. In this case, the communication apparatus 10 may be the base station or a component that can be configured in the base station. The transceiver unit 11 is configured to perform communicating-related (e.g., receiving / transmitting-related) operations on the base station side in the foregoing method embodiments. The processing unit 12 is configured to perform processing-related operations on the base station side in the foregoing method embodiments.
[0564] The communication apparatus 10 may implement steps or procedures performed by the base station in FIGS. 13-31 according to embodiments of this application. The communication apparatus 10 may include units configured to perform the method performed by the base station in FIGS. 13-31. In addition, the units in the communication apparatus 10 and the foregoing other operations and / or functions are separately used to implement corresponding procedures in FIGS. 13-31.
[0565] A specific process in which the units perform the foregoing corresponding steps is described in detail in the foregoing method embodiments. For brevity, details are not described herein again.
[0566] Referring to FIG. 33, a schematic block diagram of another communication apparatus according to an embodiment of this application is shown. The communication apparatus 20 includes a processor 21. The processor 21 is coupled to a memory 22. The memory 22 is configured to store a computer program or instructions and / or data. The processor 21 is configured to execute the computer program or instructions and / or data stored in the memory 22, so that the methods in the foregoing method embodiments are executed.
[0567] In some embodiments, the communication apparatus 20 includes one or more processors 21.
[0568] In an example, as shown in FIG. 33, the communication apparatus 20 may further include the memory 22.
[0569] In some embodiments, the communication apparatus 20 may include one or more memories 22.
[0570] In an example, the memory 22 may be integrated with the processor 21, or disposed separately from the processor 21.
[0571] In an example, as shown in FIG. 33, the communication apparatus 20 may further include a transceiver 23, where the transceiver 23 is configured to receive and / or transmit a signal. For example, the processor 21 may be configured to control the transceiver 23 to receive and / or transmit a signal.
[0572] In some embodiments, the communication apparatus 20 may be an ED or a component (e.g., a chip, a circuit, or a processing system) that can be configured in the ED; or the communication apparatus 20 may be a base station or a component (e.g., a chip, a circuit, or a processing system) that can be configured in the base station.
[0573] In a solution, the communication apparatus 20 is configured to perform the operations performed by the ED in the foregoing method embodiments.
[0574] For example, the processor 21 may be configured to perform a processing-related operation performed by the ED in the foregoing method embodiments, and the transceiver 23 may be configured to perform a communicating-related (e.g., receiving / transmitting-related) operation performed by the ED in the foregoing method embodiments.
[0575] In another solution, the communication apparatus 20 is configured to perform the operations performed by the base station in the foregoing method embodiments.
[0576] For example, the processor 21 may be configured to perform a processing-related operation performed by the base station in the foregoing method embodiments, and the transceiver 23 may be configured to perform a communicating-related (e.g., receiving / transmitting-related) operation performed by the base station in the foregoing method embodiments.
[0577] An embodiment of this application further provides a computer-readable storage medium. The computer-readable storage medium stores computer instructions used to implement the method performed by the ED or the method performed by the base station in the foregoing method embodiments.
[0578] For example, when the computer program is executed by a computer, the computer may be enabled to implement the method performed by the ED or the method performed by the base station in the foregoing method embodiments.
[0579] An embodiment of this application further provides a computer program product including instructions. When the instructions are executed by a computer, the computer is enabled to implement the method performed by the ED or the method performed by the base station in the foregoing method embodiments.
[0580] An embodiment of this application further provides a communication system. The communication system includes the ED and the base station in the foregoing embodiments.
[0581] For explanations and beneficial effects of related content of any communication apparatus provided above, refer to a corresponding method embodiment provided above. Details are not described herein again.
[0582] The processor mentioned in embodiments of this application may be a central processing unit (CPU) . The processor may further be another general-purpose processor, a digital signal processor (DSP) , an application-specific integrated circuit (ASIC) , a field programmable gate array (FPGA) , or another programmable logic device, a discrete gate, a transistor logic device, a discrete hardware component, or the like. The general-purpose processor may be a microprocessor, or the processor may be any conventional processor or the like.
[0583] The memory mentioned in embodiments of this application may be a volatile memory or a non-volatile memory, or may include a volatile memory and a non-volatile memory. The non-volatile memory may be a read-only memory (ROM) , a programmable read-only memory (programmable ROM, PROM) , an erasable programmable read-only memory (erasable PROM, EPROM) , an electrically erasable programmable read-only memory (electrically EPROM, EEPROM) , or a flash memory. The volatile memory may be a random access memory (RAM) . For example, the RAM may be used as an external cache. By way of example but not limitation, the RAM may include a plurality of forms such as the following: a static random access memory (static RAM, SRAM) , a dynamic random access memory (dynamic RAM, DRAM) , a synchronous dynamic random access memory (synchronous DRAM, SDRAM) , a double data rate synchronous dynamic random access memory (double data rate SDRAM, DDR SDRAM) , an enhanced synchronous dynamic random access memory (enhanced SDRAM, ESDRAM) , a synchlink dynamic random access memory (synchlink DRAM, SLDRAM) , and a direct rambus random access memory (direct rambus RAM, DR RAM) .
[0584] It should be noted that when the processor is a general-purpose processor, a DSP, an ASIC, an FPGA, another programmable logic device, a discrete gate or a transistor logic device, or a discrete hardware component, the memory (storage module) may be integrated into the processor.
[0585] It should be further noted that the memory described in this specification is intended to include, but is not limited to, these memories and any other memory of a suitable type.
[0586] A person of ordinary skill in the art may be aware that, in combination with the examples described in embodiments disclosed in this specification, units and methods may be implemented by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are performed by hardware or software depends on particular applications and design constraints of the technical solutions. A person skilled in the art may use different methods to implement the described functions for each particular application, but it should not be considered that the implementation goes beyond the protection scope of this application.
[0587] It should be noted that the term “receive” or “receiving” used herein may refer to receiving or otherwise obtaining from an element / component in same apparatus or from another device separate from the apparatus. Similarly, the term “transmit” or “transmitting” may refer to outputting or sending to / for an element / component in same apparatus or to / for another device separate from the apparatus. For example, any of the methods / procedures described herein may be performed by a chipset, in which case any sending or receiving steps may occur between elements of the chipset.
[0588] It may be clearly understood by a person skilled in the art that, for the purpose of convenient and brief description, for a detailed working process of the foregoing apparatus and unit, refer to a corresponding process in the foregoing method embodiment. Details are not described herein again.
[0589] In the several embodiments provided in this application, the disclosed apparatuses and methods may be implemented in other manners. For example, the described apparatus embodiment is merely an example. For example, division into the units is merely logical function division and may be other division in an actual implementation. For example, a plurality of units or components may be combined or integrated into another system, or some features may be ignored or not performed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections may be implemented through some interfaces. The indirect couplings or communication connections between the apparatuses or units may be implemented in electronic forms, mechanical forms, or other forms.
[0590] The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or may be distributed on a plurality of network units. Some or all of the units may be selected based on an actual requirement to implement the solutions provided in this application.
[0591] In addition, function units in embodiments of this application may be integrated into one unit, or each of the units may exist alone physically, or two or more units may be integrated into one unit.
[0592] All or some of the foregoing embodiments may be implemented by using software, hardware, firmware, or any combination thereof. When the software is used to implement embodiments, all or a part of embodiments may be implemented in a form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the procedures or functions according to embodiments of this application are all or partially generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or another programmable apparatus. For example, the computer may be a personal computer, a server, a network device, or the like. The computer instructions may be stored in a computer-readable storage medium or may be transmitted from a computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website, computer, server, or data center to another website, computer, server, or data center in a wired (for example, a coaxial cable, an optical fiber, or a digital subscriber line (DSL) ) or wireless (for example, infrared, radio, and microwave, or the like) manner. The computer-readable storage medium may be any usable medium accessible by the computer, or a data storage device, for example, a server or a data center, integrating one or more usable media. The usable medium may be a magnetic medium (for example, a floppy disk, a hard disk, or a magnetic tape) , an optical medium (for example, a DVD) , a semiconductor medium (for example, an SSD) , or the like. For example, the usable medium may include but is not limited to any medium that can store program code, such as a USB flash drive, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disc.
[0593] The present disclosure encompasses various embodiments, including not only method embodiments, but also other embodiments such as apparatus embodiments and embodiments related to non-transitory computer readable storage media. Embodiments may incorporate, individually or in combinations, the features disclosed herein.
[0594] Although this disclosure refers to illustrative embodiments, this is not intended to be construed in a limiting sense. Various modifications and combinations of the illustrative embodiments, as well as other embodiments of the disclosure, will be apparent to persons skilled in the art upon reference to the description.
[0595] Features disclosed herein in the context of any particular embodiments may also or instead be implemented in other embodiments. Method embodiments, for example, may also or instead be implemented in apparatus, system, and / or computer program product embodiments. In addition, although embodiments are described primarily in the context of methods and apparatus, other implementations are also contemplated, as instructions stored on one or more non-transitory computer-readable media, for example. Such media could store programming or instructions to perform any of various methods consistent with the present disclosure.
Claims
1.A communication method, comprising:receiving a reference signal, wherein the reference signal is associated with multiple angles of departure, denoted as P; and;transmitting first information based on the reference signal, wherein the first information indicates a parameter set of path loss associated with a full set or a subset of the P, denoted as S.2.The method according to claim 1, wherein the S comprises one or more of:at least one angle, wherein each angle corresponds to at least one line-of-sight (LOS) path; andat least one angle, wherein each angle corresponds to at least one i-bounce non-line-of-sight (NLOS) path, i=1, …, M, M is a positive integer.3.The method according to claim 1 or 2, wherein the first information is based on a configuration of transmit antenna array associated with the reference signal.4.The method according to claim 3, wherein the configuration of transmit antenna array indicates one or more of:a type of the transmit antenna array;a quantity of transmit antennas of the transmit antenna array;spacing between adjacent transmit antennas of the transmit antenna array; andparameters related to reference locations corresponding to the transmit antenna array, wherein the reference locations are used for generating the first information.5.The method according to claim 3 or 4, wherein the method further comprises:receiving second information, wherein the second information indicates part or all of the configuration of transmit antenna array.6.The method according to claim 4 or 5, wherein angles from the transmit antenna array to the reference locations relative to the transmit antenna array comprise the P.7.The method according to any one of claims 4 to 6, wherein the parameters indicate a set of first thresholds corresponding to path loss associated with the P.8.The method according to any one of claims 5 to 7, wherein the second information is generated based on one or more of:a location of an electronic device (ED) , an orientation of the ED and a capability of the ED.9.The method according to any one of claims 4 to 8, wherein the method further comprises:transmitting third information, wherein the third information is used for determining the parameters.10.The method according to any one of claims 4 to 9, wherein the parameters are associated with one or more of factors related to the reception of the reference signal: frequency, weather conditions, an orientation of the ED, and a communication environment of the ED.11.The method according to any one of claims 6 to 10, wherein the second information indicates one or more of:transmit array response matrix At (φ) of the transmit antenna;a set of vectors corresponding to the angles from the transmit antenna array to the reference locations related to the transmit antenna array; anda set of first thresholds corresponding to the angles from the transmit antenna array to the reference locations related to the transmit antenna array;wherein, the set of vectors and the set of first thresholds are derived from channel estimation between the transmit antennas and the reference locations.12.The method according to any one of claims 2 to 11, wherein the S comprises at least one angle corresponding to at least one i-bounce NLOS path, the first information is further based on a second threshold, wherein the second threshold is related to a value of the M.13.The method according to claim 12, wherein the second information further indicates the second threshold.14.The method according to any one of claims 1 to 13, wherein the parameter set of path loss comprises one or more of:reference signal received quality (RSRP) , signal to interference plus noise ratio (SINR) , channel quality indicator (CQI) , and rank indicator (RI) .15.The method according to any one of claims 1 to 14, wherein the first information further indicates propagation delay (s) associated with the reference signal.16.The method according to any one of claims 1 to 15, wherein the first information comprises Npath set (s) of parameters corresponding to Npath sub-channel (s) , the Npath sub-channel (s) is selected from r sub-channel (s) , the r sub-channel (s) is obtained from channel estimation between the ED and a transmitter, Npath and r are positive integers and Npath is less than or equal to r.17.The method according to claim 16, wherein a set of parameters corresponding to a subchannel comprises one or more of:index (es) information of part or all of the S associated with the subchannel;path loss information associated with the subchannel; andtime delay information associated with the subchannel.18.The method according to any one of claims 1 to 17, wherein the first information further indicates one or more of: a location of the ED, an orientation of the ED, and a configuration of receive antennas corresponding to the reference signal.19.The method according to any one of claims 1 to 18, wherein the method further comprises:adjusting operational parameters based on the first information, wherein the operational parameters are used for communication of an ED and a base station.20.The method according to claim 19, wherein the operational parameters comprise one or more of: parameter (s) related to power settings, parameter (s) related to antenna configurations, and parameter (s) related to processing capabilities.21.A communication method, comprising:transmitting a reference signal, wherein the reference signal is associated with multiple angles of departure, denoted as P;andreceiving first information, wherein the first information is generated based on the reference signal, and the first information indicates a parameter set of path loss associated with a full set or a subset of the P, denoted as S.22.The method according to claim 21, wherein the S comprises one or more of:at least one angle, wherein each angle corresponds to at least one line-of-sight (LOS) path; andat least one angle, wherein each angle corresponds to at least one i-bounce non-line-of-sight (NLOS) path, i=1, …, M, M is a positive integer.23.The method according to claim 21 or 22, wherein the first information is generated based on a configuration of transmit antenna array associated with the reference signal.24.The method according to claim 23, wherein the configuration of transmit antenna array indicates one or more of:a type of the transmit antenna array;a quantity of transmit antennas of the transmit antenna array;spacing between adjacent transmit antennas of the transmit antenna array; andparameters related to reference locations corresponding to the transmit antenna array, wherein the reference locations are used for generating the first information.25.The method according to claim 23 or 24, the method further comprises:transmitting second information, wherein the second information indicates part or all of the configuration of transmit antenna array.26.The method according to claim 24 or 25, wherein angles from the transmit antenna array to the reference locations relative to the transmit antenna array comprise the P.27.The method according to any one of claims 24 to 26, wherein the parameters indicate a set of first thresholds corresponding to path loss associated with the P.28.The method according to any one of claims 24 to 27, wherein the second information is generated based on one or more of: a location of an electronic device (ED) , an orientation of the ED and a capability of the ED.29.The method according to any one of claims 24 to 28, wherein the method further comprises:receiving third information, wherein the third information is used for determining the parameters.30.The method according to any one of claims 24 to 29, wherein the parameters are associated with one or more of factors related to the reception of the reference signal: frequency, weather conditions, an orientation of the ED, and a communication environment of the ED.31.The method according to any one of claims 26 to 30, wherein the second information indicates one or more of:transmit array response matrix At (φ) of the transmit antenna;a set of vectors corresponding to the angles from the transmit antenna array to the reference locations related to the transmit antenna array; anda set of first thresholds corresponding to the angles from the transmit antenna array to the reference locations relative to the transmit antenna array;wherein, the set of vectors and the set of first thresholds are derived from channel estimation between the transmit antennas and the reference locations.32.The method according to any one of claims 22 to 31, wherein the S comprises at least one angle corresponding to at least one i-bounce NLOS path, the first information is further based on a second threshold, wherein the second threshold is related to a value of the M.33.The method according to claim 32, wherein the second information further indicates the second threshold.34.The method according to any one of claims 21 to 33, wherein the parameter set of path loss comprises one or more of:reference signal received quality (RSRP) , signal to interference plus noise ratio (SINR) , channel quality indicator (CQI) , and rank indicator (RI) .35.The method according to any one of claims 21 to 34, wherein the first information further indicates propagation delay (s) associated with the reference signal.36.The method according to any one of claims 21 to 35, wherein the first information comprises Npath set (s) of parameters corresponding to Npath sub-channel (s) , the Npath sub-channel (s) is selected from r sub-channel (s) , the r sub-channel (s) is obtained from channel estimation between the ED and a transmitter, Npath and r are positive integers and Npath is less than or equal to r.37.The method according to claim 36, wherein a set of parameters corresponding to a subchannel comprises one or more of:index (es) information of part or all of the S associated with the subchannel;path loss information associated with the subchannel; andtime delay information associated with the subchannel.38.The method according to any one of claims 21 to 37, wherein the first information further indicates one or more of: a location of the ED, an orientation of the ED, and a configuration of receive antennas corresponding to the reference signal.39.The method according to any one of claims 21 to 38, wherein the method further comprises:adjusting operational parameters based on the first information, wherein the operational parameters are used for communication of a base station and an ED.40.The method according to claim 39, wherein the operational parameters comprise one or more of: the parameter (s) related to power settings, parameter (s) related to antenna configurations, and parameter (s) related to processing capabilities.41.A communication apparatus, configured to perform the method according to any one of claims 1 to 20 or 21 to 40.42.The communication apparatus of claim 41, wherein comprising:receiving unit, configured to receive a reference signal, wherein the reference signal is associated with multiple angles of departure, denoted as P; and;transmitting unit, configured to transmit first information based on the reference signal, wherein the first information indicates a parameter set of path loss associated with a full set or a subset of the P, denoted as S.43.The communication apparatus of claim 41, comprising:transmitting unit, configured to transmit a reference signal, wherein the reference signal is associated with multiple angles of departure, denoted as P;receiving unit, configured to receive first information based on the reference signal, wherein the first information indicates a parameter set of path loss associated with a full set or a subset of the P, denoted as S.44.The communication apparatus of claim 41, comprising:one or more processors, configured to perform processing step according to any one of claims 1 to 20 or 21 to 40;an interface circuit, configure to perform transmitting or receiving step according to any one of claims 1 to 20 or 21 to 40.45.The communication apparatus of claim 44, the interface circuit comprises one or more transceivers.46.An apparatus comprising:one or more processors; anda memory storing instructions which, when executed by the one or more processors, cause the apparatus to: perform the method of any one of claims 1 to 20 or 21 to 40.47.A communication system, wherein the communication system comprises a first communication apparatus configured to perform the method of any one of claims 1 to 20 and a second communication apparatus configured to perform the method of any one of claims 21 to 40.48.A computer-readable storage medium having instructions stored thereon which, when executed by apparatus, cause the apparatus to perform the method of any one of 1 to 20 or 21 to 40.49.A computer program product having instructions which, when executed, cause an apparatus to perform the method of any one of claims 1 to 20 or 21 to 40.
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