TRS-based doppler estimation

Abstract

A method, system, and apparatus for tracking reference signal (TRS)-based Doppler estimation are disclosed. According to some aspects, a method in a network node includes configuring a WD using an autocorrelation configuration that includes an indication of M different time delays, M being an integer. The method includes receiving, from the WD, a magnitude of an autocorrelation estimate for a channel between the WD and the network node for each of the M different time delays.

Description

[0001] Cross-reference to related applications

[0002] This application claims priority to U.S. Provisional Application No. 63 / 336,486, filed on April 29, 2022, which is incorporated herein by reference in its entirety. Technical Field

[0003] The present disclosure relates to wireless communications, and more particularly to Doppler estimation based on a Tracking Reference Signal (TRS). Background Art

[0004] The 3rd Generation Partnership Project (3GPP) has developed and is developing standards for fourth generation (4G) (or Long Term Evolution (LTE)) and fifth generation (5G) (or New Radio (NR)) wireless communication systems. Such systems provide, among other things, broadband communications between network nodes (e.g., base stations) and mobile wireless devices (WDs), as well as communications between network nodes and between WDs. Sixth generation (6G) wireless communication systems are also under development.

[0005] MU-MIMO

[0006] With Multi-User Multiple Input Multiple Output (MU-MIMO), two or more users in the same cell are co-scheduled on the same time-frequency resource(s). That is, two or more independent data streams are sent to different WDs simultaneously, and the spatial domain can usually be used to separate the corresponding streams. By sending multiple streams simultaneously, the capacity of the system can be increased. However, this comes at the expense of a reduced signal to interference plus noise ratio (SINR) for each stream, since power is shared between streams and the streams will cause mutual interference.

[0007] Channel State Information Reference Signal (CSI-RS)

[0008] For CSI measurement and feedback, CSI-RS is defined. CSI-RS is transmitted on each antenna port and is used by the WD to measure the downlink (DL) channel between each transmit antenna port and each of its receive antenna ports. The transmit antenna port is also called a CSI-RS port. The number of antenna ports supported in NR is {1,2,4,8,12,16,24,32}. By measuring the received CSI-RS, the WD can estimate the channel (including the radio propagation channel) and the antenna gain that the CSI-RS is traversing. The CSI-RS used for the above purpose is also called non-zero power (NZP) CSI-RS.

[0009] The CSI-RS may be configured to be transmitted in certain resource elements (REs) in time slots and certain time slots. FIG1 shows an example of CSI-RS REs for 12 antenna ports, where 1 RE per resource block (RB) per port is shown. See also FIG2, where an example diagram of a time-frequency distribution of symbols is shown.

[0010] TRS

[0011] Due to oscillator imperfections, transmission and reception may not be synchronized in time and / or frequency, which may cause inter-symbol and intra-symbol interference. In NR, a Tracking Reference Signal (TRS) is introduced to be used by the WD for synchronization. TRS can be periodic or aperiodic.

[0012] From the 3GPP specification perspective, TRS is specified as a specific type of NZP CSI-RS, where the corresponding NZP CSI-RS resource set contains a higher layer parameter "trs-info".

[0013] Periodic TRS is configured as one or more NZP CSI-RS resource sets, each resource set consisting of multiple periodic NZP CSI-RS resources. More specifically, TRS consists of four single-port, density 3 CSI-RS resources located in two consecutive time slots. The CSI-RS resources within each NZP CSI-RS resource set can be configured with a period of 10, 20, 40 or 80 milliseconds. Please note that the exact RE set used for TRS may vary. There is always a time domain interval of four symbols between two CSI-RS resources within a time slot. Figure 2 shows an example of a TRS burst of 2 TRS symbols per time slot in 2 adjacent time slots. NR also supports aperiodic TRS.

[0014] CSI framework in NR

[0015] In NR, a WD can be configured with multiple CSI report settings and multiple CSI-RS resource settings. Each resource setting can contain multiple resource sets, and each resource set can contain up to 8 CSI-RS resources. For each CSI report setting, the WD will feedback a CSI report.

[0016] Each CSI report setting contains one or more of the following information:

[0017] CSI-RS resource set for channel measurement;

[0018] The set of resources used for interference measurements;

[0019] Optional, CSI-RS resource set for interference measurement;

[0020] Temporal behavior, i.e., periodic, semi-persistent, or aperiodic reporting;

[0021] Frequency granularity, i.e. broadband or sub-band;

[0022] Report quantity, which indicates the CSI parameters to be reported, such as rank indicator (RI), precoder matrix indicator (PMI), channel quality indicator (CQI), and CSI-RS resource indicator (CRI) (in case there are multiple CSI-RS resources in a CSI-RS resource set);

[0023] Codebook type, i.e., Type I or Type II, and codebook subset restrictions;

[0024] Measurement limitations; and

[0025] CQI subband size.

[0026] Type 1 and Type 2 codebooks in NR

[0027] Type 1 codebook (CB) is usually used by WD to report CSI for single-user MIMO (SU-MIMO) scheduling in NR. Type 2 CB is usually used for more accurate CSI feedback for multi-user MIMO (MU-MIMO) scheduling.

[0028] In the case of Type 1 CB, the precoding vector for each MIMO layer is associated with a single DFT beam, whereas for Type 2 CB, the precoding vector for each layer is a linear combination of multiple DFT beams.

[0029] Enhanced Type 2 Codebook in NR

[0030] In NR3GPP Technical Release 16 (3GPP Rel-16), Type 2 CB is enhanced by applying a frequency domain (FD) DFT basis across all subbands to reduce CSI feedback overhead and / or improve CSI accuracy.

[0031] QCL

[0032] Multiple signals can be sent from different antenna ports of the same base station. These signals can have the same large-scale characteristics, such as Doppler shift / spread, average delay spread, or average delay. These antenna ports are called quasi-co-located (QCL).

[0033] If the WD knows that two antenna ports are QCL with respect to some parameter (such as Doppler spread), the WD can estimate the parameter based on one of the antenna ports and apply the estimate to receive the signal on the other antenna port. Typically, the first antenna port is represented by a measurement reference signal (such as a TRS or synchronization signal block (SSB)) (called the source RS), while the second antenna port is a demodulation reference signal (DMRS) (called the target RS).

[0034] For example, if antenna ports A and B are QCL with respect to an average delay, the WD can estimate the average delay from the signal received from antenna port A and assume that the signal received from antenna port B has the same average delay. This is useful for demodulation because the WD can know the characteristics of the channel in advance, which helps the WD select an appropriate channel estimation filter, for example.

[0035] Information about what assumptions can be made about the QCL is sent from the network to the WD. In NR, four QCL relationships between the source RS and the target RS are defined:

[0036] Type A: {Doppler shift, Doppler spread, average delay, delay spread};

[0037] Type B: {Doppler shift, Doppler spread};

[0038] Type C: {average delay, Doppler shift}; and

[0039] Type D: {Spatial Rx Parameters}.

[0040] Multi-TRP transmission

[0041] Reliable physical downlink shared channel (PDSCH) and physical downlink control channel (PDCCH) transmission with multiple transmission points (TRPs) has been introduced in NR 3GPP Rel-16 and 3GPP Rel-17, respectively, where PDSCH or PDCCH can be sent through multiple TRPs to improve reliability. An example is shown in Figure 3, where TRP-specific TRS and CSI-RS are sent from each TRP, while PDSCH and PDCCH can be repeated on different TRPs.

[0042] It has been observed through measurements in actual deployments that downlink MU-MIMO precoding performance degrades when one or more of the co-scheduled WDs start moving faster than several kilometers per hour. The reason is that when this happens, the channel information used to calculate the precoding quickly becomes outdated.

[0043] Therefore, making downlink MU-MIMO precoding robust at higher WD speeds is a problem. Extending Type-IICSI feedback using time domain / Doppler information has been considered in the 3GPP Rel-18 scoping. The problem with this approach is that in the current 3GPP release, Type-IICSI calculations are already very complex, including measurements of up to 32 CSI-RS ports. Adding time domain information extraction on top of this makes the WD complexity even higher.

[0044] Another problem is that Type II feedback cannot be extended to multiple transmit and receive point (TRP) operations and L1 / L2 mobility because it was introduced with single TRP-based operations in mind. How to make MU-MIMO precoding across multiple TRPs more robust to WD speed while keeping WD complexity low is also a problem. Summary of the invention

[0045] Some embodiments advantageously provide methods, network nodes, and wireless devices for TRS-based Doppler estimation.

[0046] In some embodiments, the WD is configured to perform, execute and report Doppler related measurements based on TRS (also known as CSI-RS for tracking). In some embodiments, the network node uses these measurements to switch between different operating modes, for example:

[0047] Reciprocal mode based on sounding reference signal (SRS) and mode based on CSI feedback;

[0048] No additional DMRS symbol vs. one additional DMRS symbol; and / or

[0049] Two extra DMRS symbols versus three extra DMRS symbols.

[0050] Some embodiments may include:

[0051] Doppler related measurement definition;

[0052] The method used to measure the configuration;

[0053] Estimation methods;

[0054] The method used for measurement reporting; and / or

[0055] • Methods for utilizing measurements of Doppler correlation for a network node to decide to perform certain actions, such as switching between two modes.

[0056] Some embodiments may include WD measurements of autocorrelations for multiple delays, along with corresponding measurement configuration and measurement reporting details.

[0057] Some embodiments include WD measurements of autocorrelation across TRS bursts (ie, for delays corresponding to a TRS period or multiple TRS periods), and methods for compensating for phase incoherence and / or OFDM window adjustment, and corresponding measurement configuration and measurement reporting details.

[0058] Some embodiments include WD measurements of relative frequency offset and power for each identified peak in the channel impulse response, along with corresponding measurement configuration and measurement reporting details.

[0059] Some embodiments include methods of estimating Doppler spread based on autocorrelations for multiple delays.

[0060] Some embodiments include methods for estimating various Doppler quantities based on estimates of the relative frequency offset and power of each identified peak in the channel impulse response.

[0061] According to one aspect, a method in a wireless device WD configured to communicate with a network node is provided. The method comprises determining an autocorrelation estimate for a channel between the WD and the network node for each of M time delays, M being an integer. The method further comprises reporting to the network node an indication of a magnitude of each of the autocorrelation estimates for the M time delays.

[0062] According to another aspect, a WD includes processing circuitry and a radio interface that configure the WD to perform any of the methods described above.

[0063] According to another aspect, a method in a network node configured to communicate with a wireless device WD is provided. The method includes configuring the WD using an autocorrelation reporting configuration, the autocorrelation reporting configuration including an indication of M time delays, M being an integer. The method further includes receiving from the WD an autocorrelation estimate for a channel between the WD and the network node for each of the M time delays.

[0064] According to another aspect, a network comprises processing circuitry and a radio interface configuring a network node to perform any of the methods described above. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] The present embodiments and their attendant advantages and features will be more readily understood by reference to the following detailed description when considered in conjunction with the accompanying drawings, in which:

[0066] FIG1 shows an example of a resource element;

[0067] Figure 2 shows the TRS cycle;

[0068] FIG3 shows a plurality of TRPs;

[0069] 4 is a schematic diagram of an example network architecture according to the principles of the present disclosure, showing a communication system connected to a host computer via an intermediate network;

[0070] 5 is a block diagram of a host computer communicating with a wireless device via a network node over an at least partially wireless connection according to some embodiments of the present disclosure;

[0071] 6 is a flow chart illustrating an example method for executing a client application at a wireless device implemented in a communication system including a host computer, a network node, and a wireless device according to some embodiments of the present disclosure;

[0072] 7 is a flow chart illustrating an example method for receiving user data at a wireless device implemented in a communication system including a host computer, a network node, and a wireless device, according to certain embodiments of the present disclosure;

[0073] 8 is a flow chart illustrating an example method for receiving user data from a wireless device at a host computer implemented in a communication system including a host computer, a network node, and a wireless device, according to certain embodiments of the present disclosure;

[0074] 9 is a flow chart illustrating an example method for receiving user data at a host computer implemented in a communication system including a host computer, a network node, and a wireless device according to some embodiments of the present disclosure;

[0075] FIG10 is a flow chart of an example process in a network node for Doppler estimation based on a tracking reference signal (TRS);

[0076] Fig.11 is a flow chart of an example process for Doppler estimation based on a tracking reference signal (TRS) in a wireless device;

[0077] Fig.12 is a flow chart of an example process in a network node for Doppler estimation based on a Tracking Reference Signal (TRS);

[0078] Fig.13 is a flow chart of an example process for Doppler estimation based on a tracking reference signal (TRS) in a wireless device;

[0079] Fig.14 An example of TRS timing is shown;

[0080] Fig.15 An example of a TRS burst cycle is shown;

[0081] Fig.16 Another example of a TRS burst cycle is shown;

[0082] Fig.17The Bessel function is shown;

[0083] Fig.18 An example of a power spectral density function is shown;

[0084] Fig.19 is a flow chart of an example process in a WD according to the principles described herein; and

[0085] 20 is a flow diagram of an example process in a network node according to principles described herein. DETAILED DESCRIPTION

[0086] Before describing the example embodiments in detail, it should be noted that the embodiments reside primarily in a combination of device components and processing steps related to TRS-based Doppler estimation. Therefore, the components have been represented by conventional symbols in appropriate places in the drawings, and only those specific details relevant to understanding the embodiments are shown so as not to obscure the present disclosure with details that would be obvious to a person of ordinary skill in the art having the benefit of the description herein. Like numbers represent like elements throughout the description.

[0087] As used herein, relational terms, such as "first" and "second", "top" and "bottom", etc., may be used only to distinguish one entity or element from another entity or element, without necessarily requiring or implying any physical or logical relationship or order between these entities or elements. The terms used herein are only for the purpose of describing specific embodiments and are not intended to limit the concepts described herein. Unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" used herein are also intended to include the plural forms. It will be further understood that when used herein, the terms "include", "comprise", "cover", and / or "contain" specify the presence of the features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0088] In the embodiments described herein, connection terms such as "in communication with..." may be used to indicate electrical or data communication, which may be achieved, for example, by physical contact, induction, electromagnetic radiation, radio signals, infrared signals, or optical signals. Those skilled in the art will appreciate that multiple components may interoperate, and modifications and variations in achieving electrical and data communication are possible.

[0089] The term "network node" used herein may be any type of network node included in a radio network, and may also include a base station (BS), a radio base station, a base transceiver station (BTS), a base station controller (BSC), a radio network controller (RNC), a g-node B (gNB), an evolved NB (eNB), a NB, a multi-standard radio (MSR) radio node (e.g., MSRBS), a multi-cell / multicast coordination entity (MCE), an integrated access and backhaul (IAB) node, a relay node, a donor node controlling a relay, a radio access point (AP), a transmission point, a transmission node, a remote radio unit (RRU) remote radio head (RRH), a core network node (e.g., a mobility management entity (MME), a self-organizing network (SON) node, a coordination node, a positioning node, an MDT node, etc.), an external node (e.g., a third-party node, a node outside the current network), a node in a distributed antenna system (DAS), a spectrum access system (SAS) node, an element management system (EMS), etc. The network node may also include a test device. The term "radio node" used herein may also be used to represent a wireless device (WD) or a radio network node.

[0090] In some embodiments, the non-limiting terms WD or user equipment (UE) can be used interchangeably. The WD herein can be any type of wireless device capable of communicating with a network node or another WD via a radio signal. The WD can also be a radio communication device, a target device, a device-to-device (D2D) WD, a machine type WD, or a WD capable of machine-to-machine communication (M2M), a low-cost and / or low-complexity WD, a sensor equipped with a WD, a tablet computer, a mobile terminal, a smart phone, a laptop embedded device (LEE), a laptop mounted device (LME), a USB dongle, a customer premises equipment (CPE), an Internet of Things (IoT) device, or a narrowband Internet of Things (NB-IOT) device, etc.

[0091] In addition, in some embodiments, the general term "radio network node" is used. It can be any type of radio network node, which can include any of a base station, a radio base station, a base transceiver station, a base station controller, a network controller, an RNC, an eNB, a NB, a gNB, an MCE, an IAB node, a relay node, an access point, a radio access point, an RRU, and an RRH.

[0092] Note that although terminology from one particular wireless system (e.g., 3GPP LTE and / or NR) may be used in this disclosure, this should not be viewed as limiting the scope of this disclosure to only the aforementioned systems. Other wireless systems, including but not limited to Wideband Code Division Multiple Access (WCDMA), Worldwide Interoperability for Microwave Access (WiMax), Ultra Mobile Broadband (UMB), and Global System for Mobile Communications (GSM), may also benefit from utilizing the ideas covered within this disclosure.

[0093] Further note that the functions performed by a wireless device or network node described herein may be distributed across multiple wireless devices and / or network nodes. In other words, it is contemplated that the functions of the network nodes and wireless devices described herein are not limited to being performed by a single physical device, but may, in fact, be distributed across multiple physical devices.

[0094] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those of ordinary skill in the art to which the present disclosure belongs. It should also be understood that the terms used herein should be interpreted as having the same meaning as they have in the context of this specification and the relevant technology, and should not be interpreted in an idealized or overly formal sense unless explicitly defined herein.

[0095] Some embodiments provide Doppler estimation based on a Tracking Reference Signal (TRS).Measurement of autocorrelations for multiple delays allows for better accuracy in Doppler spread estimation and avoids ambiguity in Doppler spread estimation.

[0096] Measurement of autocorrelations for multiple delays provides information about the variations of the radio channel on different time scales, which allows network nodes to make better decisions, for example, about switching between different modes (e.g. CSI feedback mode and reciprocity mode), or to decide on an appropriate number of additional DMRS symbols.

[0097] Measurement of autocorrelation at larger delays, such as across TRS bursts, provides information about how the channel varies over longer time scales. This can be critical when using autocorrelation to decide on mode switching / selection (e.g. CSI feedback mode or reciprocity mode) or selecting the number of additional DMRS symbols to use.

[0098] Measurements of Doppler shift, frequency offset, Doppler spread, and Doppler power spectrum across TRS bursts can provide better accuracy for these measurements. This can be critical when using autocorrelation to decide on mode switching / selection (e.g., CSI feedback mode or reciprocity mode) or selecting the number of additional DMRS symbols to use.

[0099] Now turning to the drawings, in which like elements are represented by like reference numerals, FIG. 4 shows a schematic diagram of a communication system 10 according to an embodiment, such as a 3GPP type cellular network that can support standards such as LTE and / or NR (5G), which includes an access network 12 (e.g., a radio access network) and a core network 14. The access network 12 includes a plurality of network nodes 16a, 16b, 16c (collectively referred to as network nodes 16), such as NBs, eNBs, gNBs, or other types of wireless access points, each of which defines a corresponding coverage area 18a, 18b, 18c (collectively referred to as coverage area 18). Each network node 16a, 16b, 16c can be connected to the core network 14 via a wired or wireless connection 20. A first WD 22a located in the coverage area 18a is configured to be wirelessly connected to or paged by the corresponding network node 16a. A second WD 22b in the coverage area 18b can be wirelessly connected to the corresponding network node 16b. Although multiple WDs 22a, 22b (collectively referred to as wireless devices 22) are shown in this example, the disclosed embodiments are equally applicable to situations where a single WD is within the coverage area or a single WD is connected to a corresponding network node 16. Note that although only two WDs 22 and three network nodes 16 are shown for convenience, the communication system may include more WDs 22 and network nodes 16.

[0100] Furthermore, it is contemplated that the WD 22 may simultaneously and / or be configured to communicate with multiple network nodes 16 and multiple types of network nodes 16, respectively. For example, the WD 22 may have dual connectivity with a network node 16 supporting LTE and the same or different network node 16 supporting NR. As an example, the WD 22 may communicate with an eNB for LTE / E-UTRAN and a gNB for NR / NG-RAN.

[0101] The communication system 10 itself can be connected to a host computer 24, which can be embodied in the hardware and / or software of a stand-alone server, a cloud-enabled server, a distributed server, or as a processing resource in a server farm. The host computer 24 can be owned or controlled by a service provider, or can be operated by or on behalf of a service provider. The connections 26, 28 between the communication system 10 and the host computer 24 can extend directly from the core network 14 to the host computer 24, or can extend via an optional intermediate network 30. The intermediate network 30 can be one of a public, private, or managed network, or a combination of multiple networks. The intermediate network 30 (if any) can be a backbone network or the Internet. In some embodiments, the intermediate network 30 can include two or more subnetworks (not shown).

[0102] The communication system in FIG. 4 enables a connection between one of the connected WDs 22a, 22b and the host computer 24 as a whole. The connection can be described as an over-the-top (OTT) connection. The host computer 24 and the connected WDs 22a, 22b are configured to use the access network 12, the core network 14, any intermediate network 30, and possible other infrastructure (not shown) as an intermediary to transmit data and / or signaling through the OTT connection. The OTT connection can be transparent in the sense that at least some of the participating communication devices through which the OTT connection passes do not know the routes of the uplink and downlink communications. For example, the network node 16 may not be informed or need not be informed of the past routes of the incoming downlink communications, wherein the data originating from the host computer 24 will be forwarded (e.g., handed over) to the connected WD 22a. Similarly, the network node 16 does not need to know the future routes of the outgoing uplink communications originating from the WD 22a to the host computer 24.

[0103] The network node 16 is configured to include a configuration unit 32, which can be configured to select an operating mode based at least in part on the received Doppler correlation measurement, the operating mode being related to at least one of the feedback mode and the number of demodulation reference signals DMRS. The configuration unit 32 can be configured to configure the WD 22 using an autocorrelation configuration, the autocorrelation configuration including an indication of M time delays, M being an integer.

[0104] The wireless device 22 is configured to include a measurement unit 34, which may be configured to perform Doppler-related measurements on the TRS according to a configuration received from the network node 16. The measurement unit 34 may be configured to determine an autocorrelation estimate for the channel between the WD 22 and the network node 16 for each of M time delays, M being an integer.

[0105] According to an embodiment, an example implementation of the WD 22, network node 16, and host computer 24 discussed in the previous paragraphs will now be described with reference to FIG. 5. In the communication system 10, the host computer 24 includes hardware (HW) 38, which includes a communication interface 40, which is configured to establish and maintain a wired or wireless connection with the interface of different communication devices of the communication system 10. The host computer 24 further includes a processing circuit 42, which may have storage and / or processing capabilities. The processing circuit 42 may include a processor 44 and a memory 46. Specifically, in addition to or in place of a processor (e.g., a central processing unit) and a memory, the processing circuit 42 may include an integrated circuit for processing and / or control, for example, one or more processors and / or processor cores and / or FPGAs (field programmable gate arrays) and / or ASICs (application-specific integrated circuits) suitable for executing instructions. The processor 44 can be configured to access (e.g., write to and / or read) a memory 46, which can include any type of volatile and / or non-volatile memory, such as cache and / or buffer memory and / or RAM (random access memory) and / or ROM (read only memory) and / or optical memory and / or EPROM (erasable programmable ROM).

[0106] Processing circuitry 42 may be configured to control any of the methods and / or processes described herein and / or cause such methods and / or processes to be performed, for example, by host computer 24. Processor 44 corresponds to one or more processors 44 for performing the functions of host computer 24 described herein. Host computer 24 includes memory 46 configured to store data, programming software code, and / or other information described herein. In some embodiments, software 48 and / or host application 50 may include instructions that, when executed by processor 44 and / or processing circuitry 42, cause processor 44 and / or processing circuitry 42 to perform the processes described herein with respect to host computer 24. The instructions may be software associated with host computer 24.

[0107] The software 48 can be executed by the processing circuit 42. The software 48 includes a host application 50. The host application 50 can operate to provide services to remote users, such as WD 22 connected via an OTT connection 52 that terminates at WD 22 and the host computer 24. When providing services to remote users, the host application 50 can provide user data sent using the OTT connection 52. "User data" can be data and information that implement the functions described herein. In some embodiments, the host computer 24 can be configured to provide control and functions to the service provider, and can be operated by or on behalf of the service provider. The processing circuit 42 of the host computer 24 can enable the host computer 24 to observe, monitor, control, send and / or receive information to the network node 16 and / or the wireless device 22.

[0108] The communication system 10 further includes a network node 16, which is provided in the communication system 10 and includes hardware 58, which enables the network node 16 to communicate with the host computer 24 and the WD 22. The hardware 58 may include: a communication interface 60, which is used to establish and maintain a wired or wireless connection with the interface of different communication devices of the communication system 10, and a radio interface 62, which is used to establish and maintain at least a wireless connection 64 with the WD 22 located in the coverage area 18 served by the network node 16. The radio interface 62 can be formed as or can include, for example, one or more RF transmitters, one or more RF receivers, and / or one or more RF transceivers. The communication interface 60 can be configured to facilitate a connection 66 to the host computer 24. The connection 66 can be direct, or it can be through the core network 14 of the communication system 10 and / or through one or more intermediate networks 30 external to the communication system 10.

[0109] In the illustrated embodiment, the hardware 58 of the network node 16 further includes a processing circuit 68. The processing circuit 68 may include a processor 70 and a memory 72. Specifically, in addition to or in place of a processor (e.g., a central processing unit) and a memory, the processing circuit 68 may include an integrated circuit for processing and / or control, such as one or more processors and / or processor cores and / or FPGAs and / or ASICs adapted to execute instructions. The processor 70 may be configured to access (e.g., write and / or read) the memory 72, which may include any type of volatile and / or non-volatile memory, such as a cache and / or buffer memory and / or RAM and / or ROM and / or optical memory and / or EPROM.

[0110] Therefore, the network node 16 also has software 74, which is stored internally, for example, in the memory 72, or stored in an external memory (e.g., a database, a storage array, a network storage device, etc.) that the network node 16 can access via an external connection. The software 74 can be executed by the processing circuit 68. The processing circuit 68 can be configured to control any method and / or process described herein and / or cause such method and / or process to be performed by the network node 16. The processor 70 corresponds to one or more processors 70 for performing the functions of the network node 16 described herein. The memory 72 is configured to store data, programming software code and / or other information described herein. In some embodiments, the software 74 may include instructions that, when executed by the processor 70 and / or the processing circuit 68, cause the processor 70 and / or the processing circuit 68 to perform the process described herein with respect to the network node 16. For example, the processing circuit 68 of the network node 16 may include a configuration unit 32, which may be configured to select an operating mode based at least in part on the received Doppler-related measurement, the operating mode being related to at least one of the feedback mode and the number of demodulation reference signals DMRS. Configuration unit 32 may be configured to configure WD 22 using an autocorrelation configuration including indications of M time delays, M being an integer.

[0111] The communication system 10 further includes the already mentioned WD 22. The WD 22 may have hardware 80, which may include a radio interface 82 configured to establish and maintain a wireless connection 64 with a network node 16 serving the coverage area 18 in which the WD 22 is currently located. The radio interface 82 may be formed as or may include, for example, one or more RF transmitters, one or more RF receivers, and / or one or more RF transceivers.

[0112] Hardware 80 of WD 22 further includes processing circuitry 84. Processing circuitry 84 may include processor 86 and memory 88. Processor 86 and memory 88 may be similar to processor 68 and memory 72 described above.

[0113] Therefore, WD 22 may also include software 90, which is stored in, for example, the memory 88 of WD 22, or in an external memory (e.g., a database, a storage array, a network storage device, etc.) accessible to WD 22. Processing circuit 84 may execute software 90. Software 90 may include client application 92. Client application 92 may operate to provide services to human or non-human users via WD 22 with the support of host computer 24. In host computer 24, the executed host application 50 may communicate with the executed client application 92 via an OTT connection 52 terminated at WD 22 and host computer 24. When providing services to users, client application 92 may receive request data from host application 50 and provide user data in response to the request data. OTT connection 52 may send both request data and user data. Client application 92 may interact with the user to generate the user data it provides.

[0114] The processing circuit 84 may be configured to control any method and / or process described herein and / or cause such method and / or process to be performed by the WD 22. The processor 86 corresponds to one or more processors 86 for performing the WD 22 functions described herein. The WD 22 includes a memory 88 configured to store data, programming software code, and / or other information described herein. In some embodiments, the software 90 and / or the client application 92 may include instructions that, when executed by the processor 86 and / or the processing circuit 84, cause the processor 86 and / or the processing circuit 84 to perform the process described herein with respect to the WD 22. For example, the processing circuit 84 of the wireless device 22 may include a measurement unit 34 that may be configured to perform Doppler-related measurements on the TRS according to a configuration received from the network node 16. The measurement unit 34 may be configured to determine an autocorrelation estimate of a channel between the WD 22 and the network node 16 for each of the M time delays, where M is an integer.

[0115] In some embodiments, the internal workings of network nodes 16, WD 22, and host computer 24 may be as shown in FIG. 5, and independently, the surrounding network topology may be the network topology shown in FIG.

[0116] exist Figure 5, the OTT connection 52 has been abstractly drawn to illustrate communications between a host computer 24 and a wireless device 22 via a network node 16, without explicit reference to any intermediate devices and the precise routing of messages via those devices. The network infrastructure may determine the route, which may be configured to hide the route from the WD 22 or from the service provider operating the host computer 24, or from both. While the OTT connection 52 is active, the network infrastructure may further make decisions by which it dynamically changes the route (e.g., based on load balancing considerations or reconfiguration of the network).

[0117] The wireless connection 64 between the WD 22 and the network node 16 is in accordance with the teachings of the embodiments described in the present disclosure. One or more of the various embodiments improve the performance of OTT services provided to the WD 22 using the OTT connection 52, wherein the wireless connection 64 may form the last leg. More specifically, the teachings of some of these embodiments may improve data rates, latency, and / or power consumption, thereby providing benefits such as reduced user waiting time, relaxed file size restrictions, better responsiveness, and extended battery life.

[0118] In some embodiments, a measurement process may be provided for the purpose of monitoring data rates, delays, and other factors improved by one or more embodiments. There may also be an optional network function for reconfiguring the OTT connection 52 between the host computer 24 and the WD 22 in response to changes in the measurement results. The measurement process and / or the network function for reconfiguring the OTT connection 52 may be implemented in the software 48 of the host computer 24 or in the software 90 of the WD 22, or in both. In an embodiment, a sensor (not shown) may be deployed in or associated with a communication device through which the OTT connection 52 passes; the sensor may participate in the measurement process by providing the values ​​of the monitored quantities exemplified above or providing the values ​​of other physical quantities from which the software 48, 90 can calculate or estimate the monitored quantities. The reconfiguration of the OTT connection 52 may include message formats, retransmission settings, preferred routes, etc.; the reconfiguration does not need to affect the network node 16, and the network node 16 may not know or perceive it. Some such processes and functions may be known and practiced in the art. In some embodiments, the measurement may involve proprietary WD signaling, which facilitates the host computer 24 to measure throughput, propagation time, delay, etc. In some embodiments, the measurements may be implemented such that the software 48 , 90 causes a message, particularly an empty or “dummy” message, to be sent using the OTT connection 52 while it monitors propagation times, errors, etc.

[0119] Thus, in some embodiments, the host computer 24 includes a processing circuit 42 configured to provide user data, and a communication interface 40 configured to forward the user data to a cellular network for transmission to the WD 22. In some embodiments, the cellular network further includes a network node 16 having a radio interface 62. In some embodiments, the network node 16 is configured to, and / or the processing circuit 68 of the network node 16 is configured to, perform the functions and / or methods described herein for preparing / starting / maintaining / supporting / terminating transmissions to the WD 22, and / or preparing / terminating / maintaining / supporting / terminating reception of transmissions from the WD 22.

[0120] In some embodiments, host computer 24 includes: processing circuitry 42 and communication interface 40, which is configured to receive user data originating from transmissions from WD 22 to network node 16. In some embodiments, WD 22 is configured to perform the functions and / or methods described herein, and / or includes a radio interface 82 and / or processing circuitry 84, which is configured to perform the functions and / or methods described herein for preparing / initiating / maintaining / supporting / terminating transmissions to network node 16, and / or preparing / terminating / maintaining / supporting / terminating reception of transmissions from network node 16.

[0121] Although Figures 5 and 6 show various "units", such as configuration unit 32 and measurement unit 34, which are located within respective processors, it is contemplated that these units may be implemented so that a portion of the unit is stored in a corresponding memory within the processing circuit. In other words, these units may be implemented in hardware or in a combination of hardware and software within the processing circuit.

[0122] FIG. 6 is a flow chart showing an example method implemented in a communication system (e.g., such as the communication system of FIGS. 4 and 5 ) according to one embodiment. The communication system may include a host computer 24, a network node 16, and a WD 22, which may be those described with reference to FIG. 5 . In the first step of the method, the host computer 24 provides user data (box S100). In an optional substep of the first step, the host computer 24 provides user data by executing a host application (e.g., host application 50) (box S102). In the second step, the host computer 24 initiates a transmission carrying user data to the WD 22 (box S104). In an optional third step, in accordance with the teachings of the embodiments described throughout the present disclosure, the network node 16 transmits the user data carried in the transmission initiated by the host computer 24 to the WD 22 (box S106). In an optional fourth step, the WD 22 executes a client application, for example, a client application 92 associated with the host application 50 executed by the host computer 24 (box S108).

[0123] FIG. 7 is a flow chart showing an example method implemented in a communication system (e.g., such as the communication system of FIG. 4 ) according to one embodiment. The communication system may include a host computer 24, a network node 16, and a WD 22, which may be those described with reference to FIGS. 4 and 5 . In the first step of the method, the host computer 24 provides user data (frame S110). In an optional sub-step (not shown), the host computer 24 provides user data by executing a host application (e.g., host application 50). In a second step, the host computer 24 initiates a transmission carrying user data to the WD 22 (frame S112). According to the teachings of the embodiments described throughout the present disclosure, the transmission may be passed via the network node 16. In an optional third step, the WD 22 receives the user data carried in the transmission (frame S114).

[0124] FIG8 is a flow chart showing an example method implemented in a communication system (e.g., the communication system of FIG4 ) according to one embodiment. The communication system may include a host computer 24, a network node 16, and a WD 22, which may be those described with reference to FIGS. 4 and 5 . In an optional first step of the method, the WD 22 receives input data provided by the host computer 24 (box S116). In an optional sub-step of the first step, the WD 22 executes a client application 92, which provides user data in response to the received input data provided by the host computer 24 (box S118). Additionally or alternatively, in an optional second step, the WD 22 provides user data (box S120). In an optional sub-step of the second step, the WD provides user data (box S122) by executing a client application (e.g., client application 92). In providing user data, the executed client application 92 may also consider user input received from a user. Regardless of the specific manner in which the user data is provided, the WD 22 may initiate the transmission of user data to the host computer 24 in an optional third sub-step (box S124). In a fourth step of the method, host computer 24 receives user data sent from WD 22 (block S126 ), in accordance with the teachings of the embodiments described throughout this disclosure.

[0125] FIG. 9 is a flow chart illustrating an example method implemented in a communication system (e.g., the communication system of FIG. 4 ) according to one embodiment. The communication system may include a host computer 24, a network node 16, and a WD 22, which may be those described with reference to FIGS. 4 and 4 . In an optional first step of the method, in accordance with the teachings of the embodiments described throughout the present disclosure, the network node 16 receives user data from the WD 22 (block S128). In an optional second step, the network node 16 initiates a transmission of the received user data to the host computer 24 (block S130). In a third step, the host computer 24 receives the user data carried in the transmission initiated by the network node 16 (block S132).

[0126] 10 is a flow chart of an example process for Doppler estimation based on a tracking reference signal (TRS) in the network node 16. The network node 16 is configured to receive a measurement of Doppler correlation of the TRS from the WD via, for example, the processing circuit 68 and / or the processor 70 and / or the radio interface 62 and / or the communication interface 60 (block S134). The process further includes selecting an operating mode based at least in part on the received Doppler correlation measurement, the operating mode being related to at least one of the feedback mode and the number of demodulation reference signals DMRS (block S136).

[0127] In some embodiments, Doppler-related measurements from the WD are post-processed by at least one of the WD and the network node before selecting an operating mode. In some embodiments, the feedback mode includes one of a CSI feedback mode and a reciprocity mode. In some embodiments, the Doppler-related measurements include measurements of at least one of a Doppler shift, a frequency offset, a Doppler spread, and a Doppler power spectrum. In some embodiments, the Doppler-related measurements are based at least in part on an autocorrelation of a channel estimate.

[0128] Fig.11 is a flow chart of an example process in the WD 22 according to some embodiments. The wireless device 22 is configured to receive a configuration of Doppler-related measurements of a TRS from a network node, for example, via the processing circuit 84 and / or the processor 86 and / or the radio interface 82 (block S138). The process further includes performing Doppler-related measurements on the TRS according to the configuration (block S140).

[0129] In some embodiments, the configuration of the Doppler-related measurement is based at least in part on an operating mode of the network node, the operating mode being related to at least one of a feedback mode and a number of DMRSs. In some embodiments, the Doppler-related measurement comprises a measurement of at least one of a Doppler shift, a frequency offset, a Doppler spread, and a Doppler power spectrum. In some embodiments, the Doppler-related measurement is based at least in part on an autocorrelation of a channel estimate.

[0130] Fig.12 1 is a flowchart of an example process for Doppler estimation based on a tracking reference signal (TRS) in a network node 16. One or more blocks described herein may be performed by one or more elements of the network node 16, such as by one or more of the processing circuit 68 (including the configuration unit 32), the processor 70, the radio interface 62, and / or the communication interface 60. The network node 16 is configured, for example, via the processing circuit 68 and / or the processor 70 and / or the radio interface 62 and / or the communication interface 60 to configure the WD 22 using an autocorrelation report configuration, the autocorrelation report configuration including an indication of M time delays, M being an integer (block S142). The method further includes receiving from the WD 22 an indication of the magnitude of the autocorrelation estimate of the channel between the WD 22 and the network node 16 for each of the M time delays (block S144).

[0131] In some embodiments, the M time delays are selected from a group of N configured time delays, N being an integer greater than or equal to M. In some embodiments, the N configured time delays are preconfigured in WD 22. In some embodiments, the method includes sending an indication of the N configured time delays to WD 22. In some embodiments, the method includes receiving a phase of an autocorrelation estimate for each of the M time delays from WD 22. In some embodiments, the autocorrelation report configuration includes at least one periodic tracking signal TRS for channel measurement and autocorrelation estimation.

[0132] Fig.13 is a flow chart of an example process in a wireless device 22 according to some embodiments of the present disclosure. One or more blocks described herein may be performed by one or more elements of the wireless device 22, such as by one or more of the processing circuit 84 (including the measurement unit 34), the processor 86, the radio interface 82, and / or the communication interface 60. The wireless device 22 is configured, for example, via the processing circuit 84 and / or the processor 86 and / or the radio interface 82, to determine an autocorrelation estimate for a channel between the WD 22 and the network node 16 for each of the M time delays, M being an integer (block S146). The method further includes reporting to the network node 16 an indication of the magnitude of each of the autocorrelation estimates for the M time delays (block S148).

[0133] In some embodiments, the M time delays are selected from a group of N configured time delays, N being an integer greater than or equal to M. In some embodiments, the N configured time delays are preconfigured in the WD 22. In some embodiments, the method further includes receiving an indication of the N configured time delays from the network node 16. In some embodiments, the method further includes receiving an indication of the M time delays from the network node 16. In some embodiments, an autocorrelation estimate for a channel for a time delay is determined at least in part based on a channel estimate at at least two time instances in a plurality of time instances, wherein the two time instances are separated by a duration equal to the time delay. In some embodiments, each of the M time delays is given in accordance with one of a number of symbols and a number of slots in time. In some embodiments, the method further includes reporting to the network node 16 a phase of the autocorrelation estimate for each of the M different time delays. In some embodiments, the method includes estimating a channel at a plurality of time instances based at least in part on at least one reference signal, wherein the plurality of time instances are associated with the M time delays. In some embodiments, each of the at least one reference signal is a tracking reference signal TRS. In some embodiments, at least one of the at least one reference signal is a periodic TRS sent periodically in one of: two consecutive time slots and one time slot in each period. In some embodiments, at least one of the at least one reference signal is an aperiodic TRS sent in one of: one time slot and two consecutive time slots. In some embodiments, the method includes determining an autocorrelation estimate for each of the M time delays based on channel estimates at multiple time instances. In some embodiments, each of the M amplitudes is a normalized amplitude. In some embodiments, the method includes quantizing the amplitude and phase of the autocorrelation estimate for each of the M time delays. In some embodiments, the autocorrelation estimate for each of the M time delays is determined based at least in part on at least one channel state information reference signal CSI-RS and a demodulation reference signal DMRS separated in time. In some embodiments, the reporting of the indication of the autocorrelation estimate to the network node 16 is one of periodic, semi-persistent and aperiodic. In some embodiments, the method includes receiving at least one reference signal and a configuration of a channel state information CSI report, the CSI report being used to report the autocorrelation estimate for the M time delays based on the at least one reference signal.

[0134] Having described the general process flow of arrangements of the present disclosure and having provided examples of hardware and software arrangements for implementing the processes and functions of the present disclosure, the following sections provide details and examples of arrangements for TRS-based Doppler estimation.

[0135] Autocorrelation-based methods

[0136] Estimation of autocorrelation

[0137] Random channel h i,j The autocorrelation function of (t) is defined as:

[0138]

[0139] Among them, h i,j (t) is the channel between the i-th transmit (Tx) antenna port of the network node 16 and the j-th Rx antenna port of the WD 22 at time t; τ is the time delay; (.) * For TRS, a single port is used, i.e., the index i takes only one value and can therefore be omitted.

[0140] As long as τ<<Δt, R i,j (t,τ) is considered to be roughly independent of t over time intervals less than some value Δt. The delay τ captures rapid fading of the channel, while t captures longer term variations of the channel, e.g., depending on changes in the speed of WD 22 or movement of WD 22 into an area with different multipath characteristics. Note that for a wide sense stationary random process, there is no time dependence in the autocorrelation function.

[0141] The normalized autocorrelation function is defined as:

[0142]

[0143] On the other hand, the autocorrelation function of a channel viewed as a continuous-time signal (rather than a random process) can be defined as:

[0144]

[0145] It can also be normalized as:

[0146]

[0147] Define the time-dependent autocorrelation function:

[0148]

[0149] This can be seen as ρ i,j (t,τ) and, for slowly varying ρ i,j (t,τ), can also be used at some time in the future, that is, as ρ i,j An estimate of (t′,τ), where t′>t.

[0150] Obviously, WD 22 does not have full knowledge of the channel in continuous time, but only some knowledge of the channel at certain discrete time opportunities for which there are reference signals (ie, TRS) that can be used for channel estimation.

[0151] In some embodiments, WD 22 estimates the and Therein, for multiple values ​​of τ, there are multiple pairs of reference signals with a time distance given by τ.

[0152] Fig.14 An example delay τ is shown k Graphs / tables for τ k , the autocorrelation can be estimated based on intra-TRS burst measurements using the TRS signal. Note that for τ1 = 4·T OFDM+CP and for τ2 = T SLOT =14·T OFDM+CP , there are two samples in the TRS burst available for measurement, and for τ3 = 18·T OFDM+CP and τ4=10·T OFDM+CP , only one sample within a TRS burst is available for measurement.

[0153] Fig.15 An example delay τ is shown k = k·T TRS-周期 Graphs / charts for τ k = k·T TRS-周期 , the autocorrelation can be estimated based on TRS inter-burst measurements using the TRS signal. Note that for each pair of TRS bursts used, four samples can be used since each burst can consist of four TRS symbols.

[0154] In some embodiments, WD 22 estimates the and For multiple τ values, there are multiple pairs of reference signals with a time distance of τ, wherein a pair of reference signals may include a periodic TRS and an aperiodic triggered TRS (hereinafter referred to as aperiodic TRS), such as Fig.16 In this case, where applicable (i.e., for estimating and For each pair of periodic TRS and aperiodic TRS being QCL), the aperiodic triggered TRS is configured with respect to QCL type A and / or QCL type D with respect to the periodic TRS being QCL. Note that the aperiodic TRS can also be part of an aperiodic TRS burst that contains one or more aperiodic TRSs. In some embodiments, the number of TRS resources and the number of time slots on which the TRSs are located (i.e., on one or two time slots) are the same between the periodic TRS burst and the aperiodic TRS burst. As shown in M17, for a periodic TRS and an aperiodic TRS burst using and The estimated τ value depends on the time slot in which the aperiodic TRS is triggered. Fig.16 In the example, Fig.16 The first periodic TRS burst shown in TRS-周期 Therefore, using the first periodic TRS burst and the non-periodic TRS burst, for 0.25T TRS-周期 The value of τ can be estimated and Fig.16 The time distance between the second periodic TRS burst and the non-periodic TRS burst shown in FIG is 0.75T. TRS-周期 . Using the second periodic TRS burst and the non-periodic TRS burst, for 0.75T TRS-周期 The value of τ can be estimated and

[0155] In some embodiments, WD 22 will and The integral over time is estimated as a discrete sum over time opportunities.

[0156] References: Δt (t,τ), some example embodiments of how to perform such estimation are described below.

[0157] Let X l [n], n = 0 ... N-1 are the received frequency domain reference signal samples after matched filtering. Index l represents different OFDM symbols carrying reference symbols for correlation estimation. The time starting point of OFDM symbol l is t l Given (to be precise, t l denotes the start of the non-cyclic prefix (CP) part of an OFDM symbol). The index n denotes the reference signal sample index (assumed to be proportional to the subcarrier index). In some embodiments, the reference signal used is assumed to be on a regular comb.

[0158] Let P m(n),m=1…M,n=1,2 is used for l indices of the M symbol pairs with the estimate of the autocorrelation of . It can be assumed that all symbol pairs are separated by the same distance in time (small differences due to the presence of two different cyclic prefix (CP) lengths can usually be safely ignored, so it is sufficient that the symbol pairs are separated by the same inter-symbol distance counted by the number of OFDM symbols).

[0159] In some embodiments, a low complexity estimate of the normalized autocorrelation for delay τ is computed in the frequency domain as follows:

[0160]

[0161] In some embodiments, the inverse DFT is calculated for each OFDM symbol l:

[0162] Y l [k] = ifft(X l [n])

[0163] An estimate of the normalized autocorrelation over the time interval Δt can be calculated as:

[0164]

[0165] where the sum of the time samples is over a set Γ(m) defined, for example, by using a noise threshold for suppressing noise, such as, for example:

[0166]

[0167] in is the noise estimate. Alternatively, Γ(m) may be the interval that separates the channel from the noise based on the Akaike criterion.

[0168] For φ Δt (t b ,τ) can be defined as the measurement period [t a ,t b ]

[0169] in

[0170]

[0171] In some embodiments, WD 22 measures and reports φ Δt Individual measurements of (t,τ).

[0172] In some embodiments, WD 22 is measured over a longer measurement period [T a ,T b ] to perform multiple measurements φ Δt (ti ,τ), and reports φ filtered and / or averaged over multiple measurements over a longer measurement period Δt .

[0173] Normalized autocorrelation function ρ i,j (t,τ) is the inverse Fourier transform of the Doppler spectrum. It is real valued and takes values ​​between -1 and 1. However, due to the offset in frequency used by WD 22 for downward expansion and also due to the finite number of averages in time, the estimate φ Δt (t,τ) may be complex.

[0174] In some embodiments, the complex-valued estimate φ is reported Δt (t,τ).

[0175] In some embodiments, the absolute value |φ is reported Δt (t,τ)|.

[0176] In some embodiments, the report |φ Δt (t,τ)|·sgn(Re(φ Δt (t,τ))).

[0177] In some embodiments, WD 22 uses the estimated autocorrelation to estimate the Doppler spread of the channel and reports the estimated Doppler spread.

[0178] Autocorrelation estimation across different TRS bursts

[0179] If the autocorrelation delay τ is large, for example, τ is equal to the TRS burst period or a multiple of the TRS burst period if estimated between two different TRS bursts (or equal to an integer multiple of the slot time if estimated between a periodic TRS burst and an aperiodic TRS burst or between two aperiodic TRS bursts), the WD 22 may have adjusted the OFDM window between the reception of the first TRS symbol and the second TRS symbol used in the measurement. This may result in a cyclic shift Δk of the channel impulse response in the delay. Furthermore, phase coherence may be lost, resulting in an overall phase difference between the measurements performed at two opportunities in time.

[0180] This paper presents a method for estimating the cyclic shift Δk of the channel impulse response.

[0181] In some embodiments, WD 22 compensates for OFDM adjustments by a cyclic shift having a number of samples Δk and / or by a complex phase to compensate for the phase incoherence and thus estimate the autocorrelation in the time domain, e.g.

[0182]

[0183] In some embodiments, WD 22 is rotated by a frequency-dependent phase to compensate for OFDM adjustments and / or by the overall phase factor Compensate for phase incoherence and thus estimate autocorrelation in the frequency domain, for example:

[0184]

[0185] In some embodiments, the OFDM window offset Δk samples is estimated by finding the offset Δk that gives the best match between the impulse responses at two time opportunities. In some embodiments, the best match is defined as the match that gives the highest number of matching peaks.

[0186] In some embodiments, the phase is the estimated phase difference of the channel impulse response at the strongest peak at delay k′, for example:

[0187]

[0188] In some embodiments, no compensation is performed for phase incoherence, i.e.

[0189] Note that in the above formula, it is assumed that the OFDM symbol P m (1), there is no phase incoherence or OFDM window variation between m=1…M. Similarly, assuming that the OFDM symbol P m (2) There is no phase incoherence or OFDM window change between m = 1…M. It can be assumed that the phase incoherence or OFDM window change occurs in the OFDM symbol P m (1) and P m′ (2) This is usually when the OFDM symbol P m (1), m = 1…M are all in the same TRS burst, and P m′ (2) When m=1…M′ are all in another TRS burst. Usually, The sum Δk may be allowed to depend on m, and then the formula should be modified so that the summing / averaging is not done over m, or the summing / averaging is restricted to a set of m values ​​for which coherence can be assumed.

[0190] Method for estimating Doppler spread based on autocorrelation

[0191] In the Jake model (i.e. for a two-dimensional uniform channel), the Doppler spectrum is:

[0192]

[0193] And the autocorrelation, which is the Fourier transform of the Doppler spectrum, is equal to:

[0194] J0(2π·τ·f max ),

[0195] where J0(·) is the zero-order Bessel function of the first kind, which is shown in Fig.17 .

[0196] In some embodiments, the network node 16 or WD 22 estimates the Doppler spread as:

[0197]

[0198] The restrictions are:

[0199] 2π·f max τ<2.4048.

[0200] In some embodiments, the network node 16 or WD 22 estimates the Doppler spread as:

[0201]

[0202] The restrictions are:

[0203] 2π·f max τ<3.8317.

[0204] The accuracy of the estimate using the inverse of the Bessel function depends on the correlation function with f max How fast the change is depends on the magnitude of:

[0205]

[0206] Since the derivative of the Bessel function is zero at zero, a small delay will result in low accuracy. On the other hand, a larger delay can lead to ambiguity in the inverse of the Bessel function. A large delay can also cause the inverse point to be close to the Bessel function minimum at 3.8317, where the derivative is also zero, resulting in low accuracy. A delay can be used that makes |2π·τ·J0′(2π·τ·f max )|as large as possible, while guiding to avoid ambiguity. This will depend on f max itself (or equivalently depends on the WD 22 velocity), in such a way that a smaller Doppler spread (or WD 22 velocity) requires a larger delay.

[0207] In some embodiments, network node 16 or WD 22 estimates for multiple delays τ k The autocorrelation of k+1 >τ k , and continuously calculate:

[0208]

[0209] As long as f max,k ·τ k+1 <Threshold

[0210] The last calculated f max,k (i.e. for the highest k or equivalently for the largest τ k Calculated f max,k ) is used as f max Estimates.

[0211] In some embodiments, network node 16 or WD 22 estimates for multiple delays τ k The autocorrelation of k+1 >τ k , and continuously calculate:

[0212]

[0213] As long as f max,k ·τ k+1 <Threshold

[0214] The last calculated f max,k (i.e. for the highest k or equivalently for the largest τ k Calculated f max,k ) can be used as f max Estimates.

[0215] In some embodiments, network node 16 or WD 22 estimates for multiple delays τ k The autocorrelation of k+1 >τ k , and continuously calculate:

[0216]

[0217] if only:

[0218] |τ k+1 ·J0′(2π·τ k+1 ·f max,k )|>|τ k ·J0′(2π·τ k ·f max,k )|

[0219] and

[0220] f max,k ·τ k+1 <Threshold.

[0221] The last calculated f max,k (i.e. for the highest k or equivalently for the largest τk Calculated f max,k ) can be used as f max Estimates.

[0222] In some embodiments, network node 16 or WD 22 estimates for multiple delays τ k The autocorrelation of k+1 >τ k , and continuously calculate:

[0223]

[0224] if only:

[0225] |τ k+1 ·J0′(2π·τ k+1 ·f max,k )|>|τ k ·J0′(2π·τ k ·f max,k )|

[0226] and

[0227] f max,k ·τ k+1 <Threshold.

[0228] The last calculated f max,k (i.e., for the highest k or equivalently for the largest τ k Calculated f max,k ) can be used as f max In some embodiments, the network node 16 or WD 22 calculates J0(2π·τ k ·f max ) is fitted to multiple delays τ k The estimated autocorrelation of is used to estimate the Doppler spread f max , for example, the following least squares fit:

[0229] J0(2π·τ k ·f max )=|φ Δt (t,τ k )|·sgn(Re(φ Δt (t,τ k )))

[0230] Or alternatively:

[0231] J0(2π·τ k ·f max )=|φ Δt (t,τ k )|

[0232] In some embodiments, the network node 16 or WD 22 converts the estimated Doppler spread into an estimate of the WD 22 velocity and reports the WD 22 velocity. In some embodiments, the WD 22 estimates the WD 22 velocity as:

[0233]

[0234] where f carrier is the carrier frequency, c is the speed of light, f D is the estimated Doppler spread.

[0235] In some embodiments, other assumptions about the Doppler spectrum and the form of the autocorrelation are used to estimate the Doppler spread based on the autocorrelation.

[0236] In some embodiments, the Doppler spectrum is assumed to be a square function:

[0237]

[0238] With autocorrelation function:

[0239]

[0240] and by using the inverse sinc (using a restricted sinc in the domain to make the inverse unambiguous) or by k The estimated autocorrelation at is fitted to the sinc function of the autocorrelation, which is used to estimate the Doppler spread f m .

[0241] Reported autocorrelation-based measurements of network nodes using

[0242] In some embodiments, the network node 16 decides on a mode switch based on the estimated autocorrelations at one or more delays.

[0243] In some embodiments, the network node 16 uses a threshold on the autocorrelation at a certain delay τ to decide on mode switching, for example:

[0244] |φ Δt (t,τ)|>threshold→switch to mode 2

[0245] |φ Δt (t,τ)|<threshold-hysteresis→switch to mode 1

[0246] Or as:

[0247] |φ Δt (t,τ)|·sgn(Re(φ Δt (t,τ)))>threshold → switch to mode 2

[0248] |φΔt (t, τ)|·sgn(Re(φ Δt (t, τ))) < Threshold - Hysteresis → Switch to Mode 1

[0249] In some embodiments, network node 16 uses the reported autocorrelation to estimate the Doppler spread (e.g., using one of the methods described herein) and uses the estimated Doppler spread to decide on mode switching, e.g.:

[0250] doppler_spread > Threshold → Switch to Mode 2

[0251] doppler_spread < Threshold - Hysteresis → Switch to Mode 1

[0252] In some embodiments, network node 16 uses the Doppler spread reported by WD 22 to decide on mode switching, e.g.:

[0253] doppler_spread > Threshold → Switch to Mode 2

[0254] doppler_spread < Threshold - Hysteresis → Switch to Mode 1

[0255] Signaling embodiments

[0256] In some embodiments, WD 22 may be configured to report the normalized autocorrelation of the channel at multiple delays τ. In some embodiments, the delay τ is pre - configured in WD 22. In some embodiments, the delay τ may be configured by higher - layer signaling (e.g., in a measurement configuration signaling message).

[0257] In some embodiments, WD 22 reports multiple normalized autocorrelation values at different delays τ along with the different delays τ. In this case, WD 22 is not explicitly configured regarding which delays τ for which the normalized autocorrelation should be fed back. Instead, WD 22 decides which delay values for which to calculate the normalized autocorrelation based on the available TRS reference, and WD22 reports the delay values and the calculated normalized autocorrelation values to network node 16.

[0258] In some embodiments, the network configures N different delay values (i.e., N different τ values) for WD 22. Then, WD 22 will calculate the normalized autocorrelation values for a subset of N’ < N different delay values. This is beneficial in cases where, depending on the available computing resources for WD 22, WD 22 may only have the computing resources to calculate the normalized autocorrelation values for only a subset of N’ < N different delay values.

[0259] In some embodiments, WD 22 is also configured with a number of samples that WD 22 may calculate for each delay value. For example, network node 16 may configure WD 22 to calculate and report S different samples of the normalized autocorrelation value for a given delay τ.

[0260] In another embodiment, a finite number of bits are used to quantize the normalized autocorrelation values ​​to be reported. For example, each normalized autocorrelation value may be quantized by X bits. The step size or granularity of the quantized normalized autocorrelation may be predefined in the 3GPP specification. In some embodiments, the step size or granularity may be configured by a higher layer (e.g., RRC configuration) from the network node 16 to the WD 22. In some embodiments, the number of bits X may also be configured by a higher layer (e.g., RRC configuration) from the network node 16 to the WD 22.

[0261] In some embodiments, the delay value when reported by WD 22 is quantized together with the normalized autocorrelation value. The step size or granularity of the delay value may be predefined in the 3GPP specification. In some embodiments, the step size or granularity may be configured by the network node 16 to the WD 22 at a higher level (e.g., a radio resource control (RRC) configuration). In some embodiments, the number of bits used to quantize the delay value may also be configured by the network node 16 to the WD 22 at a higher level (e.g., an RRC configuration).

[0262] In some embodiments, the preconfigured or configurable delay τ may be a subset of the following values:

[0263] Four OFDM symbols including CP;

[0264] 10 OFDM symbols including CP;

[0265] 14 OFDM symbols including the CP, i.e. the length of the time slot;

[0266] 18 OFDM symbols including CP;

[0267] The period of TRS burst;

[0268] An integer multiple of the period of the TRS burst; and / or

[0269] An integer multiple of a time slot.

[0270] Note that in some embodiments, the TRS burst period can be configured to be 10ms, 20ms, 40ms, or 80ms. By triggering aperiodic TRS at appropriate time instances, a delay of an integer multiple of the time slot length can be achieved.

[0271] When reporting multiple estimated autocorrelations associated with different delays, in some embodiments the autocorrelations are arranged in the report in increasing order of the associated delay values, for example:

[0272] {φ Δt (t,τ1),φ Δt (t,τ2),…,φ Δt (t,τ k )} or {|φ Δt (t,τ1)|,|φ Δt (t,τ2)|,…,|φ Δt (t,τ k )|}

[0273] where τ1<τ2<…<τ k .

[0274] For a given reference signal with N1 OFDM symbols configured for autocorrelation measurement, assume that there are N2 unique delays τ1<τ2<…<τ over which the autocorrelation can be estimated. N2 WD 22 may be configured to report autocorrelations associated with a subset of N3 ≤ N2 delays. In some embodiments, the subset corresponds to the first N3 delays τ1 < τ2 < ... < τ N3 .

[0275] Each of the autocorrelations to be reported can be quantified. When only the magnitude is reported, i.e. |φ Δt (t,τ)|, it can be linearly quantized between 0 and 1 using multiple bits. In some embodiments, it can be quantized in dB, that is, quantized in steps of p dB. Δt (t,τ)|).

[0276] In some embodiments, the complex autocorrelation function φ Δt (t,τ k )'s real part Re(φ Δt (t,τ k )) and the imaginary part Im(φ Δt (t,τ k )) reports to the network node 16.

[0277] In some embodiments, the complex autocorrelation function φ Δt (t,τ k ) absolute value |φ Δt (t,τ k )| and the complex phase arg(φ Δt (t,τ k )) is reported to the network node 16. In some embodiments, the complex phase arg(φ Δt (t,τk )) is signaled in degrees and quantized in equidistant steps from 0 to 360 degrees.

[0278] The reporting can be periodic, aperiodic, semi-persistent, or event-triggered.

[0279] In some embodiments, when a measurement (eg, autocorrelation or Doppler spread at a particular delay) exceeds a threshold, a report is triggered.

[0280] In some embodiments, the measurement configuration may include one or more of the following parameters:

[0281] What measurements to report (e.g., Doppler spread, autocorrelation, ...);

[0282] The delay or delays for which the autocorrelation should be reported;

[0283] The maximum delay between TRS symbols that can be used for measurement;

[0284] Report type: periodic, aperiodic, semi-persistent, or event-triggered;

[0285] Periodicity of reporting;

[0286] The timeslot offset relative to the start of the system frame for periodic / semi-persistent reporting;

[0287] Thresholds for event-triggered reporting;

[0288] · Hysteresis value for event-triggered reporting;

[0289] ID for TRS for measurement (CSI-RS for tracking);

[0290] One or more NZP CSI-RS resource sets, with the higher layer parameter trs-info set to a value of true; in some embodiments, a mix of periodic NZCP CSI-RS resource sets and aperiodic NZP CSI-RS resource sets may be configured (i.e., when both periodic TRS and aperiodic TRS are used to compute normalized autocorrelation or Doppler spread); and / or

[0291] • The time period over which the measurement filtering / averaging should be performed.

[0292] Note that one or more of the above parameters may be configured in the reporting configuration instead of the measurement configuration.

[0293] In some embodiments, the network node 16 configures the WD 22 to measure the autocorrelation at a specific delay and then triggers a non-periodic TRS pair whose interval in time corresponds to the configured delay. The WD 22 can use the non-periodic TRS pair to perform the measurement of the autocorrelation and report the autocorrelation and / or the quantity derived from the autocorrelation to the network node 16.

[0294] Doppler spread estimation based on Doppler shift or frequency offset

[0295] WD 22 may estimate the channel impulse response (CIR) and the corresponding power delay profile (PDP, ie, the absolute square of the CIR) at multiple time instances where a reference signal (ie, TRS) is available.

[0296] WD 22 can identify multiple peaks in PDP.

[0297] WD 22 may estimate the frequency shift for each peak.

[0298] In some embodiments, the frequency offset is a frequency offset relative to a receive frequency of the WD.

[0299] In some embodiments, the frequency shift is a frequency shift relative to the frequency of the strongest detected peak.

[0300] In some embodiments, the frequency shift of peak i is estimated as

[0301]

[0302] Among them, δ i is the delay of peak i in the CIR, and t1 and t2 are the times of the two reference signal symbols used.

[0303] In some embodiments, the frequency offset of peak i relative to peak 0 (eg, the strongest peak) is estimated as

[0304]

[0305] In some embodiments, multiple pairs of reference signal symbols, where each pair is separated in time by the same distance, are used to improve the accuracy of the frequency offset estimate. Below is a more detailed example of how this is done.

[0306] Let X l [n], n = 0 ... N-1 are the received frequency domain reference signal samples after matched filtering. The index l represents the different OFDM symbols carrying the reference symbols used for estimation. The starting point of OFDM symbol l in time is t l Given (to be precise, t ldenotes the start of the non-CP part of an OFDM symbol). The index n denotes the reference signal sample index (assumed to be proportional to the subcarrier index). In some embodiments, it may be assumed that the reference signals used are located on a regular comb.

[0307] Let P m (n),m=1…M,n=1,2 is used for time offset l indices of the estimated M symbol pairs. It can be assumed that all symbol pairs are separated by the same distance in time (however, small differences due to the presence of two different CP lengths can usually be safely ignored, so it is sufficient that all symbol pairs are separated by the same inter-symbol distance counted by the number of OFDM symbols).

[0308] CIR Y l [k] is calculated as the inverse DFT for each OFDM symbol l:

[0309] Y l [k] = ifft(X l [n])

[0310] PDP l [k] is calculated as:

[0311] P l [k]=|Y l [k]| 2

[0312] In the PDP, it is identified that the delay k i Here, a noise threshold can be used to avoid detecting false noise peaks. Methods to avoid detecting side peaks (sometimes called side lobes) as real peaks can also be used, such as a threshold that depends on the relative delay between the detected peak and the candidate peak.

[0313] In some embodiments, after delay k i The frequency shift at peak i is calculated as:

[0314]

[0315] In some embodiments, after delay k i The frequency shift of peak i at φ relative to peak 0 (eg, the strongest peak) is estimated as:

[0316]

[0317] If the delay τ is large, for example, if the estimation is made across two different TRS bursts τ, τ being equal to the TRS burst period or a multiple of the TRS burst period, then the WD 22 may have adjusted the OFDM window between the reception of the first and second TRS symbols used for the measurement. This results in a cyclic shift Δk of the channel impulse response in the delay. Furthermore, phase coherence may be lost, resulting in an overall phase difference between the measurements performed at the two opportunities in time. A method for estimating the cyclic shift Δk of the channel impulse response is given. Based on the estimated cyclic shift Δk, for the measurement at the delay k i The above formula for the frequency shift of peak i at can be adjusted to:

[0318]

[0319] Similarly, for the delay k i The formula for the frequency offset of peak i at θ relative to peak 0 (eg, the strongest peak) can be adjusted to:

[0320]

[0321] In order to compensate for the phase coherence, i The frequency shift of peak i at is estimated as:

[0322]

[0323] in, is an estimate of the phase offset. In some embodiments, is an estimate of the phase difference of the channel impulse response at delay k′ of the strongest peak, for example estimated as:

[0324]

[0325] Note the frequency offset relative to peak 0:

[0326]

[0327] By construction, it is independent of this phase shift.

[0328] In some embodiments, the Doppler spread is estimated as:

[0329]

[0330] For example, due to the different intensities of the different peaks, different frequency shifts Δf iThe accuracy of the frequency offset estimate is usually different. This is not taken into account in the above measurements, which may result in the accuracy of the Doppler spread estimate not improving with SINR as might be expected. When SINR increases, additional peaks may be detected above the noise and interference. The new peaks have the potential to reduce the bias of the estimate, but since they are close to the noise and interference level, the accuracy of the frequency offset estimate is low, which affects the accuracy of the Doppler spread estimate. This can be addressed by a number of alternative methods described below.

[0331] In some embodiments, the Doppler spread is estimated as:

[0332]

[0333] Among them, p max is the power of the strongest peak detected, and η is a threshold parameter between 0 and 1, i.e., only peaks with a power above the threshold relative to the strongest peak are included. This may introduce a stronger bias from the estimate of . But this is not the case from the alternative measurement of Doppler shift. In some embodiments, the relative threshold is preconfigured for WD 22. In some embodiments, the relative threshold η is signaled to WD 22. In some embodiments, the relative threshold is signaled to WD 22 in a logarithmic scale of 10·log10(η)dB. In some embodiments, the relative threshold is preconfigured for WD 22. In some embodiments, the relative threshold η is signaled to WD 22. In some embodiments, the relative threshold is signaled to WD 22 in a logarithmic scale (such as 10·log10(η)dB).

[0334] In some embodiments, the Doppler spread is estimated as:

[0335]

[0336] Among them, σ i is the frequency offset estimate Δf i is an estimate of the variance of , and κ is a positive constant.

[0337] In some embodiments, the Doppler spread is estimated as:

[0338] f D =BA

[0339] Where A and B are given by solving the following formula for A and B:

[0340]

[0341] For some parameter value p between 0 and 1, where Δf ia is the frequency shift of peak i, and Δf i est is the estimated frequency shift of peak i.

[0342] Please note, is the probability that B is an overestimate of the maximum frequency shift among the identified peaks, is the probability of underestimation of the maximum Doppler shift among the identified peaks. Similarly, is the probability of underestimation of the minimum frequency shift among the identified peaks, A is the probability of overestimation of the maximum Doppler shift among the identified peaks.

[0343] In some embodiments, this probability is approximated as:

[0344]

[0345] And solve for A and B in the following formula:

[0346]

[0347] WD 22 can calculate the Doppler spread f estimated by some of the above methods. D Report to the network node 16.

[0348] In some embodiments, WD 22 converts the estimated Doppler spread into an estimate of WD 22 velocity and reports the WD 22 velocity. In some embodiments, WD 22 estimates the WD 22 velocity as:

[0349]

[0350] Among them, f carrier is the carrier frequency, c is the speed of light, f D is the estimated Doppler spread.

[0351] In some embodiments, WD 22 estimates the nth-order moment of the weighted average of the frequency shifts around the identified peak as:

[0352]

[0353] where the weighted average of the frequency offset is calculated as

[0354]

[0355] In some embodiments, the weights used are Among them, σ i is the frequency offset estimate Δf i An estimate of the variance of .

[0356] In some embodiments, the weight used is w i =p i , where p i is an estimate of the power of peak i.

[0357] WD 22 estimates one or more of the n-th order moments and reports them to network node 16 .

[0358] Signaling embodiments for methods based on Doppler shift or frequency offset

[0359] In some embodiments, WD 22 may report the identified peaks, including one or more of the following estimates for each peak i:

[0360] Frequency deviation Δf i ;

[0361] Peak power p i ;

[0362] Peak SINR,

[0363] Frequency offset estimation Δf i The estimated variance σ i ; and / or

[0364] Peak delay k i .

[0365] In some embodiments, WD 22 estimates the Doppler spread based on the frequency offset and reports the Doppler spread to network node 16 .

[0366] In some embodiments, WD 22 estimates one or more of the nth moments of the frequency offset and reports it to network node 16 .

[0367] In some embodiments, the Doppler spread is estimated such that X% of the total received signal energy is contained between the estimated minimum Doppler frequency and the maximum Doppler frequency, where X% may be, for example, 90%. Fig.18 An example is shown in the diagram of , where the estimated Doppler spread is f_max-f_min.

[0368] In some embodiments, reporting is triggered when a measurement (eg, Doppler spread) exceeds a threshold.

[0369] In some embodiments, the measurement configuration may include one or more of the following parameters:

[0370] What measurements to report (e.g., Doppler spread, frequency shift of each peak, ...);

[0371] The maximum delay between TRS symbols that can be used for measurement;

[0372] The type of report: periodic, aperiodic, semi-persistent, or event-triggered;

[0373] Periodicity of reporting;

[0374] The timeslot offset relative to the start of the system frame for periodic / semi-persistent reporting;

[0375] Thresholds for event-triggered reporting;

[0376] · Hysteresis value for event-triggered reporting;

[0377] ID for TRS for measurement (CSI-RS for tracking); and / or

[0378] • The time period over which measurement filtering / averaging should be performed.

[0379] Note that one or more of the above parameters may be configured in the report configuration instead of the measurement configuration.

[0380] Matching of channel impulse responses at different time instances

[0381] For example, WD 22 may sometimes adjust the OFDM window based on the form of the estimated channel impulse response. This adjustment results in a cyclic shift of the channel impulse response in the delay. This should not occur within a time slot and should not occur within a TRS burst. However, it is likely to occur between TRS bursts. Several methods described here rely on the condition of combining channel impulse responses for two different times at the same delay. In some embodiments, it may be necessary to adjust such OFDM window adjustments, i.e., identify the cyclic shift Δk in the delay.

[0382] In some embodiments, WD 22 estimates the OFDM window offset Δk based on an internal clock.

[0383] In some embodiments, the matching of the channel impulse responses is performed based on a machine learning algorithm. In some embodiments, a machine learning (ML) algorithm is trained using real or synthetic channel data for multiple pairs of time opportunities at some interval in time, where one of the two channel impulse responses is artificially rotated cyclically by a random number of steps, and the ML algorithm is trained to identify the number of steps by which one of the two channel impulse responses has been cyclically rotated.

[0384] In some embodiments, the OFDM window offset Δk samples is estimated by finding the offset Δk that gives the best match between the impulse responses at two time opportunities. In some embodiments, the best match is defined as the match that gives the highest number of matching peaks.

[0385] In some embodiments, the OFDM window offset Δk samples is estimated by finding the offset Δk that minimizes a cost function. In some embodiments, the cost function is a sum of terms, where one term is used for each combination of a peak identified in the first symbol and a peak identified in the second symbol, and each term is a function of the cyclic distance between the two peaks after performing a cyclic shift Δk on the second peak. In some embodiments, the terms are weighted based on the peak power. In some embodiments, the terms are weighted based on the peak SINR.

[0386] Some embodiments include letting X l [n], n=0…N-1 are the received frequency domain reference signal samples after matched filtering. Let index l denote the different OFDM symbols carrying reference symbols for estimation. The starting point of OFDM symbol l in time is denoted by t l Given (to be precise, t l Indicates the start of the non-CP part of an OFDM symbol). The index n represents the reference signal sample index (assumed to be proportional to the subcarrier index). The reference signals used are assumed to be located on a regular comb.

[0387] Let P m (n),m=1…M,n=1,2 is used for time offset The l indices of the estimated M symbol pairs are assumed to be separated in time by the same distance (however, small differences due to the presence of two different CP lengths can usually be safely ignored, so it is sufficient that all symbol pairs are separated by the same inter-symbol distance counted by the number of OFDM symbols).

[0388] CIR Y l [k] can be calculated as the inverse DFT for each OFDM symbol l:

[0389] Y l [k] = ifft(X l [n]).

[0390] PDP l [k] can be calculated as:

[0391] P l [k]=|Y l [k]| 2 .

[0392] In each PDB (i.e., for each symbol P m (n),m=1…M,n=1,2) to identify the delay Here, a noise threshold can be used to avoid detecting false noise peaks. Methods to avoid detecting side peaks (sometimes called side lobes) as real peaks can also be used, such as a threshold that depends on the relative delay between the detected peak and the candidate peak.

[0393] In some embodiments, the OFDM window offset Δk samples may be estimated by finding the offset Δk that minimizes a cost function. In some embodiments, the cost function is a sum of terms, where one term is for the first symbol P m The peak identified in (1) and the second symbol P m′ (2), and each term is a function of the cyclic distance between the two peaks after performing a cyclic shift Δk on the second peak, such as:

[0394]

[0395] Among them, k s,j is the delay in time sample units of the jth identified peak in OFDM symbol s, and the cyclic distance is defined as:

[0396] cdist(k,k′)≡min(|kk′|,N-|kk′|)

[0397] In some embodiments, the term-by-term cost function g(k) is a square function for some parameter value a

[0398]

[0399] For example, a certain value a has a magnitude of the same order of magnitude as the inverse of the Nyquist frequency in time sample units.

[0400] In some embodiments, the function g is Gaussian:

[0401]

[0402] In some embodiments, the terms in the cost function are weighted, for example, the weights depend on the power of the peak or the peak SINR, for example:

[0403]

[0404] In some embodiments:

[0405]

[0406] In some embodiments, the terms in the cost function are weighted with weights that depend on the peak SINR, for example:

[0407]

[0408] Among them, σ s is the estimated variance of the noise and interference in symbol s.

[0409] In some embodiments:

[0410]

[0411] Please note that in the above formula, it is assumed that the OFDM symbol P m (1), there is no OFDM window change between m=1…M. Similarly, assuming that the OFDM symbol P m (2), there is no OFDM window change between m=1…M. In this example, it is only assumed that the OFDM window change occurs in OFDM symbol P m (1) and P m′ (2). When OFDM symbol P m (1), m = 1…M are all in the same TRS burst, and P m′ (2), which is usually the case when m=1…M′ are all within another TRS burst. In general, Δk can be allowed to depend on m, and then the formula should be modified so that the summation / average is not performed over m and m′, or so that the summation / average is restricted to a set of m and m′ values ​​for which coherence can be assumed.

[0412] Mode Switching

[0413] In some embodiments, the network node 16 may use autocorrelation, Doppler spread, or an estimate of the WD 22 velocity to switch modes, for example, using a threshold of the type:

[0414] Estimate > Threshold → Switch to Mode 2

[0415] Estimate < Threshold - Hysteresis → Switch to Mode 1

[0416] The pair of mode switches performed between the two could be, for example:

[0417] SRS-based reciprocity mode and CSI feedback-based mode;

[0418] No additional DMRS symbol vs. one additional DMRS symbol; and / or

[0419] Two extra DMRS symbols versus three extra DMRS symbols.

[0420] In some embodiments, the network node 16 makes a decision regarding mode switching based on a number of parameters, including one or more of the following parameters:

[0421] · estimated autocorrelations at one or more delays;

[0422] The estimated Doppler spread; and / or

[0423] Estimated WD 22 speed.

[0424] Higher level configuration

[0425] Some embodiments use higher layer signaling to enable TRS based Doppler estimation.

[0426] CSI-MeasConfig

[0427] New csi-TRS resource lists and / or csi-TRS report lists can be added to CSI-MeasConfig,csi-TRS-ResourceConfigToAddModList,csi-TRS-ResourceConfigToReleaseList,csi-TRS-ReportConfigToAddModList,csi-TRS-ReportConfigToReleaseList.

[0428]

[0429]

[0430] The pool of CSI-TRS-ResourceConfig may be referenced from CSI-ResourceConfig or from a Medium Access Control (MAC) Control Element (CE).

[0431] In some embodiments, in CSI-ReportConfig-r18, csi-TRS-ResourceForDoppler is added.

[0432]

[0433]

[0434] An example configuration for csi-TRS-Doppler is here. This configuration can be associated with the measurement method described here.

[0435] In CSI-ReportConfig-r18, a new quantity "trs-Doppler" can be added.

[0436] csi-TRS-DopplerReportMod may be provided to configure the measurement and reporting type for Doppler information.

[0437] numberofTRSBurst may be provided to indicate to WD 22 the time associated with the time delay τ.

[0438] AutoCorrQuantization may be provided to indicate to the WD 22 the quantization for autocorrelation reporting.

[0439] If event-triggered Doppler reporting is configured, triggerQuantityAndThreshold may be provided to WD 22. In one example, one bit per CSI-TRS measurement / report is reserved in the CSI report, and if the event is met, WD 22 reports a 1 using the pre-reserved bit. A typical event may be the number of times a function of the calculated autocorrelation value fluctuates above and below a threshold a certain number of times.

[0440] Use of other signals than TRS and measurements performed by the network node 16

[0441] The methods described here have been based on the use of TRS signals (CSI-RS for tracking). However, they can be used based on other reference signals, such as other types of CSI-RS, uplink and downlink DMRS and uplink SRS.

[0442] Fig.19 and 20 are based on the principles disclosed herein in WD 22 ( Fig.19 ) and a flowchart of an example process in network node 16 (Figure 20).

[0443] When using the uplink signal, the network node 16 can perform the measurements described herein, such as measurements of autocorrelation, frequency shift of each identified peak, Doppler spread, etc. The network node 16 can also perform peak detection and matching of the channel impulse response where applicable. When the network node 16 performs the measurements, no signaling is required to report the measurements from the WD 22 to the network node 16. The network node 16 can use the measurements directly, for example, to decide on a mode switch.

[0444] Those skilled in the art will appreciate that the concepts described herein may be embodied as methods, data processing systems, computer program products, and / or computer storage media storing executable computer programs. Therefore, the concepts described herein may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects, all of which are collectively referred to herein as "circuits" or "modules". Any process, step, action, and / or function described herein may be performed and / or associated with a corresponding module, which may be implemented in software and / or firmware and / or hardware. In addition, the present disclosure may take the form of a computer program product on a tangible computer-usable storage medium having a computer program code embodied in the medium and executable by a computer. Any suitable tangible computer-readable medium may be used, including a hard disk, a CD-ROM, an electronic storage device, an optical storage device, or a magnetic storage device.

[0445] Some embodiments are described herein with reference to the flowcharts and / or block diagrams of methods, systems, and computer program products. It should be understood that each frame in the flowchart and / or block diagram and the combination of frames in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer (thereby creating a special-purpose computer), a special-purpose computer, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device create a device for implementing the function / action specified in the flowchart and / or block diagram frame or multiple frames.

[0446] These computer program instructions may also be stored in a computer-readable memory or storage medium, which may direct a computer or other programmable data processing device to operate in a specific manner so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction device that implements the functions / actions specified in the flowchart and / or block diagram box or multiple boxes.

[0447] The computer program instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are performed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions / actions specified in the flowchart and / or block diagram box or multiple boxes.

[0448] It should be understood that the functions / actions indicated in the blocks may occur in a different order than indicated in the operating instructions. For example, two consecutively displayed blocks may actually be executed substantially simultaneously, or may sometimes be executed in a reverse order, depending on the functions / actions involved. Although some figures include arrows on communication paths to illustrate the primary direction of communication, it should be understood that communication may occur in a direction opposite to the arrows shown.

[0449] Many different embodiments have been disclosed herein in conjunction with the above description and accompanying drawings. It should be understood that literally describing and illustrating every combination and sub-combination of these embodiments would be overly repetitive and confusing. Therefore, all embodiments may be combined in any manner and / or combination, and this specification (including the accompanying drawings) should be interpreted as constituting a complete written description of all combinations and sub-combinations of the embodiments described herein and the manner and process of making and using them, and should support claims to any such combination or sub-combination.

[0450] Those skilled in the art will appreciate that the embodiments described herein are not limited to what has been specifically shown and described herein above. In addition, unless otherwise specified above, it should be noted that all drawings are not drawn to scale. Based on the above teachings, various modifications and variations are possible without departing from the scope of the following claims.

Claims

1. A method in a wireless device WD (22) configured to communicate with a network node (16), the method comprising: determining (S146) an autocorrelation estimate for a channel between the WD (22) and the network node (16) for each of M time delays, M being an integer; as well as An indication of the magnitude of each of the autocorrelation estimates for the M time delays is reported (S148) to the network node (16).

2. The method according to claim 1, wherein: The M time delays are selected from a group of N configured time delays, N being an integer greater than or equal to M.

3. The method according to claim 2, wherein: The N configured time delays are pre-configured in the WD (22).

4. The method of claim 2, further comprising receiving an indication of the N configured time delays from the network node (16).

5. The method according to any of claims 1-4, further comprising receiving an indication of the M time delays from the network node (16).

6. The method according to any one of claims 1 to 5, wherein: Each of the M time delays is given as one of a number of symbols and a number of slots in time.

7. The method according to any of claims 1-6, further comprising reporting to the network node (16) an indication of the phase of each of the autocorrelation estimates for the M time delays.

8. The method according to any one of claims 1-7, further comprising estimating the channel at multiple time instances based at least in part on at least one reference signal, wherein The plurality of time instances are associated with the M time delays.

9. The method according to any one of claims 1 to 8, wherein: The autocorrelation estimate for the channel for a time delay is determined based at least in part on channel estimates at at least two time instances of the plurality of time instances, wherein the two time instances are separated by a time duration equal to the time delay.

10. The method according to claim 9, wherein: Each reference signal of the at least one reference signal is a tracking reference signal TRS.

11. The method according to any one of claims 9 and 10, wherein: At least one of the at least one reference signal is a periodic TRS that is periodically transmitted in one of: two consecutive time slots and one time slot in each period.

12. The method according to any one of claims 9 and 10, wherein: At least one of the at least one reference signal is an aperiodic TRS sent in one of: one slot and two consecutive slots.

13. The method of any one of claims 9-12, further comprising determining the autocorrelation estimate for each of the M time delays based at least in part on channel estimates at the plurality of time instances.

14. The method according to any one of claims 1 to 13, wherein: Each of the M amplitudes is a normalized amplitude.

15. The method of any one of claims 1-14, further comprising quantizing the magnitude and the phase of the autocorrelation estimate for each of the M time delays.

16. The method according to any one of claims 1 to 15, wherein: The autocorrelation estimate for each of the M time delays is determined based at least in part on at least one of a channel state information reference signal (CSI-RS) and a demodulation reference signal (DMRS) separated in time.

17. The method according to any one of claims 1 to 16, wherein: The reporting of the indication of the autocorrelation estimate to the network node (16) is one of periodic, semi-persistent and aperiodic.

18. The method according to any one of claims 1-17, further comprising receiving the at least one reference signal and a configuration of a channel state information (CSI) report, wherein the CSI report is used to report the autocorrelation estimate for the M time delays based on the at least one reference signal.

19. A wireless device WD (22) having a processing circuit (84) and a radio interface (82), the processing circuit (84) and the radio interface (82) configuring the WD (22) to perform the method according to any one of claims 1-18.

20. A method in a network node (16) configured to communicate with a wireless device WD (22), the method comprising: configuring (S142) the WD (22) using an autocorrelation reporting configuration, the autocorrelation reporting configuration comprising indications of M time delays, M being an integer; as well as An indication of a magnitude of an autocorrelation estimate of a channel between the WD (22) and the network node (16) for each of the M time delays is received (S144) from the WD (22).

21. The method according to claim 20, wherein: The M time delays are selected from a group of N configured time delays, where N is an integer greater than or equal to M.

22. The method according to claim 21, wherein: The N configured time delays are pre-configured in the WD (22).

23. The method of claim 21, further comprising sending an indication of the N configured time delays to the WD (22).

24. The method according to any one of claims 21-23, further comprising receiving from the WD (22) a phase of the autocorrelation estimate for each of the M time delays.

25. The method according to any one of claims 21 to 23, wherein: The autocorrelation reporting configuration comprises at least one periodic tracking signal TRS for channel measurement and the autocorrelation estimation.

26. A network node (16) having processing circuitry (68) and a radio interface (62), the processing circuitry (68) and the radio interface (62) configuring the network node (16) to perform the method according to any one of claims 20-25.

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