Methods and systems for port adaptation using channel and interference feedback

Abstract

The present disclosure relates to a 5G communication system or a 6G communication system for supporting higher data rates beyond a 4G communication system such as long-term evolution (LTE). An embodiment herein discloses methods for providing CSI feedback that will allow the gNB to perform port muting and port power-adaptation dynamically. The method includes configuring the at least one UE to report one or more downlink channel state information (CSI) feedback reports that comprise at least one of estimated channel information or estimated interference information for at least one of a fully unmuted CSI port pattern or a partially unmuted CSI port pattern. The method includes receiving the one or more CSI feedback reports for at least one of the fully unmuted CSI port pattern or the partially unmuted CSI port pattern. The method includes handling the port adaptation based on the received one or more downlink CSI feedback reports.

Description

METHODS AND SYSTEMS FOR PORT ADAPTATION USING CHANNEL AND INTERFERENCE FEEDBACK

[0001] An embodiment disclosed herein relates to wireless communication networks (wireless communication systems), and more particularly to saving energy by performing port adaptation using channel and interference feedback in the wireless communication networks.

[0002] Considering the development of wireless communication from generation to generation, the technologies have been developed mainly for services targeting humans, such as voice calls, multimedia services, and data services. Following the commercialization of 5G (5th-generation) communication systems, it is expected that the number of connected devices will exponentially grow. Increasingly, these will be connected to communication networks. Examples of connected things may include vehicles, robots, drones, home appliances, displays, smart sensors connected to various infrastructures, construction machines, and factory equipment. Mobile devices are expected to evolve in various form-factors, such as augmented reality glasses, virtual reality headsets, and hologram devices. In order to provide various services by connecting hundreds of billions of devices and things in the 6G (6th-generation) era, there have been ongoing efforts to develop improved 6G communication systems. For these reasons, 6G communication systems are referred to as beyond-5G systems.

[0003] 6G communication systems, which are expected to be commercialized around 2030, will have a peak data rate of tera (1,000 giga)-level bps and a radio latency less than 100μsec, and thus will be 50 times as fast as 5G communication systems and have the 1 / 10 radio latency thereof.

[0004] In order to accomplish such a high data rate and an ultra-low latency, it has been considered to implement 6G communication systems in a terahertz band (for example, 95GHz to 3THz bands). It is expected that, due to severer path loss and atmospheric absorption in the terahertz bands than those in mmWave bands introduced in 5G, technologies capable of securing the signal transmission distance (that is, coverage) will become more crucial. It is necessary to develop, as major technologies for securing the coverage, radio frequency (RF) elements, antennas, novel waveforms having a better coverage than orthogonal frequency division multiplexing (OFDM), beamforming and massive multiple input multiple output (MIMO), full dimensional MIMO (FD-MIMO), array antennas, and multiantenna transmission technologies such as large-scale antennas. In addition, there has been ongoing discussion on new technologies for improving the coverage of terahertz-band signals, such as metamaterial-based lenses and antennas, orbital angular momentum (OAM), and reconfigurable intelligent surface (RIS).

[0005] Moreover, in order to improve the spectral efficiency and the overall network performances, the following technologies have been developed for 6G communication systems: a full-duplex technology for enabling an uplink transmission and a downlink transmission to simultaneously use the same frequency resource at the same time; a network technology for utilizing satellites, high-altitude platform stations (HAPS), and the like in an integrated manner; an improved network structure for supporting mobile base stations and the like and enabling network operation optimization and automation and the like; a dynamic spectrum sharing technology via collision avoidance based on a prediction of spectrum usage; an use of artificial intelligence (AI) in wireless communication for improvement of overall network operation by utilizing AI from a designing phase for developing 6G and internalizing end-to-end AI support functions; and a next-generation distributed computing technology for overcoming the limit of UE computing ability through reachable super-high-performance communication and computing resources (such as mobile edge computing (MEC), clouds, and the like) over the network. In addition, through designing new protocols to be used in 6G communication systems, developing mechanisms for implementing a hardware-based security environment and safe use of data, and developing technologies for maintaining privacy, attempts to strengthen the connectivity between devices, optimize the network, promote softwarization of network entities, and increase the openness of wireless communications are continuing.

[0006] It is expected that research and development of 6G communication systems in hyper-connectivity, including person to machine (P2M) as well as machine to machine (M2M), will allow the next hyper-connected experience. Particularly, it is expected that services such as truly immersive extended reality (XR), high-fidelity mobile hologram, and digital replica could be provided through 6G communication systems. In addition, services such as remote surgery for security and reliability enhancement, industrial automation, and emergency response will be provided through the 6G communication system such that the technologies could be applied in various fields such as industry, medical care, automobiles, and home appliances.

[0007] The principal object of an embodiment herein is to disclose methods and systems for providing CSI feedback that will allow the network entity (e.g., gNB) to perform port muting and port power-adaptation dynamically.

[0008] Another object of an embodiment herein is to configure, by the network entity, at least one UE to measure channel-state for at least one first layer and an interference state for at least one second layer for at least one of: a fully unmuted CSI port pattern and a partially unmuted CSI port pattern.

[0009] Another object of an embodiment herein is to receive, by the network entity, at least one reporting information for at least one of: the fully unmuted CSI port pattern and the partially unmuted CSI port pattern upon the measurement.

[0010] Another object of an embodiment herein is to handle, by the network entity, a port adaptation based on the at least one received reporting information

[0011] Accordingly, an embodiment herein provides a method for handling a port adaptation in a wireless network (wireless system) by a network entity. The method includes configuring at least one UE to report one or more downlink channel-state information feedback reports, wherein the one or more downlink CSI feedback reports comprise at least one of estimated channel information or estimated interference information for at least one of a fully unmuted CSI port pattern or a partially unmuted CSI port pattern. Further, the method includes receiving, from the at least one UE, the one or more downlink CSI feedback reports for at least one of the fully unmuted CSI port pattern or the partially unmuted CSI port pattern. Further, the method includes handling the port adaptation based on the received one or more downlink CSI feedback reports.

[0012] Accordingly, an embodiment herein provides a method performed by a UE. The method includes measuring a channel-state for at least one first layer and an interference state for at least one second layer for at least one of a fully unmuted channel state information (CSI) port pattern or a partially unmuted CSI port pattern. Further, the method includes sending, to a network entity, one or more downlink CSI feedback reports for at least one of the fully unmuted CSI port pattern or the partially unmuted CSI port pattern upon the measurement.

[0013] Accordingly, an embodiment herein provides a network entity including a processor, a memory and a port adaptation controller coupled with the processor and the memory. The port adaptation controller is configured to configure at least one user equipment (UE) to report one or more downlink channel state information (CSI) feedback reports, wherein the one or more downlink CSI feedback reports comprise at least one of estimated channel information or estimated interference information for at least one of a fully unmuted CSI port pattern or a partially unmuted CSI port pattern. Further, the port adaptation controller is configured to receive, from the at least one UE, the one or more downlink CSI feedback reports for at least one of the fully unmuted CSI port pattern or the partially unmuted CSI port pattern. Further, the port adaptation controller is configured to handle the port adaptation based on the received one or more downlink CSI feedback reports.

[0014] Accordingly, an embodiment herein provides a UE comprising a port adaptation controller coupled with a processor and a memory. The port adaptation controller is configured to measure a channel-state for at least one first layer and an interference state for at least one second layer for at least one of: a fully unmuted CSI port pattern and a partially unmuted CSI port pattern. Further, the port adaptation controller is configured to send at least one reporting information for at least one of: the fully unmuted CSI port pattern and the partially unmuted CSI port pattern upon the measurement. Further, the port adaptation controller is configured to handle a port adaptation based on the at least one received reporting information.

[0015] Accordingly, an embodiment herein provides a wireless network. The wireless network obtains one or more downlink channel state information (CSI) feedback reports corresponding to the one or more CSI-RS port muting patterns. The one or more downlink CSI feedback reports includes at least one of, one or more CSI feedback reports having quantized version of an SVD decomposed downlink channel matrix and an EVD decomposed downlink interference matrix for the one or more CSI-RS port muting patterns. Further, the wireless network determines, to mute at least one CSI-RS port belonging to the one or more CSI-RS port muting patterns or to unmute at least one CSI-RS port belonging to the network entity, based on the received one or more downlink CSI feedback reports.

[0016] Further, the wireless network estimates one or more fractions of energy captured for one or more CSI-RS port muting patterns. Further, the wireless network determines to mute at least one CSI-RS port belonging to the one or more CSI-RS port muting patterns or to unmute at least one CSI-RS port belonging to the network entity, based on the one or more energy feedback reports.

[0017] These and other aspects of an embodiment herein will be better appreciated and understood when considered in conjunction with the following description and the accompanying drawings. It should be understood, however, that the following descriptions, while indicating at least one embodiment and numerous specific details thereof, are given by way of illustration and not of limitation. Many changes and modifications may be made within the scope of an embodiment herein without departing from the scope thereof, and an embodiment herein includes all such modifications.

[0018] An embodiment herein is illustrated in the accompanying drawings, throughout which like reference letters indicate corresponding parts in the various figures. An embodiment herein will be better understood from the following description with reference to the following illustratory drawings. An embodiment herein is illustrated by way of examples in the accompanying drawings, and in which:

[0019] FIG. 1A depicts a process for providing CSI feedback (including channel-state and interference covariance) that will allow a network entity (e.g., gNB) to perform port muting and port power-adaptation dynamically, according to an embodiment as disclosed herein;

[0020] FIG. 1B depicts a process for providing CSI feedback (including channel-state and interference covariance) that will allow a network entity (e.g., gNB) to perform port muting and port power-adaptation dynamically, according to an embodiment as disclosed herein;

[0021] FIG. 2 depicts a process for providing CSI feedback that will allow the gNB to perform port muting and port power-adaptation dynamically, according to an embodiment as disclosed herein;

[0022] FIG. 3 depicts a scenario, wherein fully-unmuted or partially-unmuted CSI port patterns are used for channel-state and / or interference-covariance feedback, according to an embodiment as disclosed herein;

[0023] FIG. 4 is a sequence diagram illustrating a method for handling the port adaptation in the wireless network, according to an embodiment as disclosed herein;

[0024] FIG. 5 shows various hardware components of a network entity, according to an embodiment as disclosed herein;

[0025] FIG. 6 shows various hardware components of the UE, according to an embodiment as disclosed herein;

[0026] FIG. 7 is a flow chart illustrating a method for handling a port adaptation in a wireless network by the network entity, according to an embodiment as disclosed herein; and

[0027] FIG. 8 is a flow chart illustrating a method for handling a port adaptation in a wireless network by the UE, according to an embodiment as disclosed herein.

[0028] An embodiment herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting an embodiment that is illustrated in the accompanying drawings and detailed in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure an embodiment herein. The examples used herein are intended merely to facilitate an understanding of ways in which an embodiment herein may be practiced and to further enable those of skill in the art to practice an embodiment herein. Accordingly, the examples should not be construed as limiting the scope of an embodiment herein.

[0029] The words / phrases "exemplary", "example", "illustration", "in an instance", "and the like", "and so on", "etc.", "etcetera", "e.g.,", "i.e.," are merely used herein to mean "serving as an example, instance, or illustration. Any embodiment or implementation of the present subject matter described herein using the words / phrases "exemplary", "example", "illustration", "in an instance", "and the like", "and so on", "etc.", "etcetera", "e.g.,", "i.e.," is not necessarily to be construed as preferred or advantageous over an embodiment.

[0030] An embodiment herein may be described and illustrated in terms of blocks which carry out a described function or functions.　These blocks, which may be referred to herein as managers, units, modules, hardware components or the like, are physically implemented by analog and / or digital circuits such as logic gates, integrated circuits, microprocessors, microcontrollers, memory circuits, passive electronic components, active electronic components, optical components, hardwired circuits and the like, and may optionally be driven by a firmware. The circuits may, for example, be embodied in one or more semiconductor chips, or on substrate supports such as printed circuit boards and the like.　The circuits constituting a block may be implemented by dedicated hardware, or by a processor (e.g., one or more programmed microprocessors and associated circuitry), or by a combination of dedicated hardware to perform some functions of the block and a processor to perform other functions of the block.　Each block of an embodiment may be physically separated into two or more interacting and discrete blocks without departing from the scope of the disclosure.　Likewise, the blocks of an embodiment may be physically combined into more complex blocks without departing from the scope of the disclosure.

[0031] It should be noted that elements in the drawings are illustrated for the purposes of this description and ease of understanding and may not have necessarily been drawn to scale. For example, the flowcharts / sequence diagrams illustrate the method in terms of the steps required for understanding of aspects of an embodiment as disclosed herein. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the drawings by conventional symbols, and the drawings may show only those specific details that are pertinent to understanding the present embodiment so as not to obscure the drawings with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein. Furthermore, in terms of the system, one or more components / modules which comprise the system may have been represented in the drawings by conventional symbols, and the drawings may show only those specific details that are pertinent to understanding the present embodiment so as not to obscure the drawings with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein.

[0032] The accompanying drawings are used to help easily understand various technical features and it should be understood that an embodiment presented herein is not limited by the accompanying drawings. As such, the present disclosure should be construed to extend to any modifications, equivalents, and substitutes in addition to those which are particularly set out in the accompanying drawings and the corresponding description. Usage of words such as first, second, third etc., to describe components / elements / steps is for the purposes of this description and should not be construed as sequential ordering / placement / occurrence unless specified otherwise.

[0033] Network energy saving (NES) work-item (WI) considered spatial- and power-domain techniques for Rel-18. As per agreed work item description　(WID): RP-223540, Radio Access Network　(RAN)-1 should specify the following techniques in spatial and power domains:

[0034] a) Specify necessary enhancements on Channel State Information (CSI) and beam management related procedures including measurement and report, and signaling to enable efficient adaptation of spatial elements (e.g. antenna ports, active transceiver chains) [RAN1, RAN2].

[0035] b) Specify necessary enhancements on CSI related procedures including measurement and report, and signaling to enable efficient adaptation of power offset values between Physical Downlink Shared Channel　(PDSCH)　and channel state information reference signal　(CSI-RS) [RAN1, RAN2].

[0036] The above objectives are only for UE specific channels / signals. Further, legacy UE CSI / CSI-RS capabilities applies when considering total number of CSI reports and requirements.

[0037] Environmental sustainability, particularly energy efficiency in the network and devices, is expected to remain an important design consideration going forward towards Rel-20 specifications for a sixth generation (6G).

[0038] Network power savings can be achieved by turning off transceiver units (i.e., TxRU(s)) at a gNB. However, that can adversely impact a cell-capacity if performed (semi-statically). Recovery from the said "turned off" states is another important requirement during dynamic real-time operation.

[0039] It should be noted that port adaptation operations, particularly port muting and / or unmuting, will impact the downlink CSI measurements in the network. The gNB might use:

[0040] Multiple CSI reports, i.e. CSI feedback for each muting or power-adaptation pattern (known as sub-configuration based CSI feedback in 3GPP Rel-18 specifications); and

[0041] More detailed or informative CSI feedback (some more information in addition to Rel-16 / Rel-17 CSI feedback).

[0042] Outline of the legacy CSI feedback procedure: The CSI acquisition and feedback is used in state-of-the-art networks for improving link quality and system capacity. It broadly consists of the following steps:

[0043] The gNB configures / requests UEs to perform CSI-RS measurements on each of the configured sub-configurations.

[0044] The UEs measure the downlink channel information (Channel Quality Indicator (CQI), recoding matrix indicator (PMI), rank indicator (RI), etc.) and feeds back the configured reporting quantities to the gNB.

[0045] The gNB aggregates the CSI information from the connected UEs to design precoders and (co-)schedule users.

[0046] There are various ways that dynamic muting / unmuting can be achieved. Each of these approaches will affect different aspects of the CSI feedback procedure. They will also impact the system performance differently. For example, the existing approach of feeding back CSI measurements for each sub-configuration can be quite prohibitive in terms of the resulting CSI feedback overhead on the uplink when considering even modestly large number of sub-configurations.

[0047] Hence, there is a need in the art for solutions which will overcome the above mentioned drawback(s), among others.

[0048] An embodiment herein discloses methods and systems for providing CSI feedback that will allow the gNB to perform port muting and port power-adaptation dynamically, for the purpose of saving network and UE energy consumption or for reducing CSI feedback overhead.

[0049] An embodiment herein discloses a method for providing CSI feedback that will allow a gNB to perform port muting and port power-adaptation. An embodiment herein provides better network throughput, as the multi-user interference information are provided as additional feedback along with the channel-state information. An embodiment herein is explained using type II codebook-based channel-state and interference covariance feedback, however, it may be obvious to a person of ordinary skill in the art that an embodiment as disclosed herein can also be applied to the type I codebook.

[0050] Referring now to the drawings, and more particularly to FIGS. 1A through 8, where similar reference characters denote corresponding features consistently throughout the figures, there is shown an embodiment.

[0051] FIG. 1A and FIG. 1B depict a process for providing CSI feedback (including channel-state and interference covariance) that will allow a network entity 200 (e.g., gNB) to perform port muting and port power-adaptation dynamically, according to an embodiment as disclosed herein. The operations and functions of the FIG. 1A and FIG. 1B are explained in conjunction with FIG. 2 to FIG. 6.

[0052] FIG. 2 depict a process S200 for providing CSI feedback that will allow the gNB 200a to perform port muting and port power-adaptation dynamically. In step 1, the gNB 200a configures the UEs 100 to measure channel-state for max(v,v') layers (i.e., first layers) and interference state for v''layers (i.e., second layers) for a fully- / partially-unmuted CSI port pattern. Note that this choice can be as per gNB's discretion, UE-assisted or UE-initiated. In step 2, the UE 100 measures CSI for the pattern and feeds back configured reporting quantities (e.g., channel quality indicator (CQI), precoding matrix indicator (PMI), rank indicator (RI), etc.) to the gNB 200a. The PMI information, in case of type 2 codebook, currently comprises of the v right-singular vectors for the v layers requested by the gNB 200a. In addition to the right-singular vectors, the UE 100 may feedback the v'left-singular vectors, and the corresponding v'singular values to the gNB 200a. FIG 1A assumes v and v'are equal, for simplicity of illustration. Additionally, the UE 100 feeds back the measured interference covariance information to the gNB 200a, by feeding back v''eigenvectors for the v''layers (second layers) and v''eigenvalues to the gNB. Note that the v''eigenvalues will be real-valued. In step 3, the gNB 200a collects the channel and interference information from all UEs 100 and uses that for co-scheduling users. Since the gNB 200a has the v-rank approximation of each user's channel and v''-rank approximation of each user's interference covariance, the gNB 200a can now decide on the transmit port(s) to mute or adapt power on so as to minimally impact network capacity or some other system metric of choice.

[0053] As mentioned in step 2 (channel-state feedback), for the current CSI acquisition instance, the UE 100 estimates the downlink channel and performs singular-value decomposition (SVD) on it:

[0054]

[0055] where denotes the conjugate-transpose of matrix and is a diagonal matrix containing the singular values of in descending order of magnitude. Here we assume ports at the transmit side and ports at a receive side were used for current CSI occasion. The gNB 200a can then send v-layer downlink data using the v right-singular vectors for precoding.

[0056] Type II PMI codebook assumes precoder structure, where , is composed ofLoversampled 2D DFT beams. ConsideringMsubbands, the following matrix dimensions are present:

[0057]

[0058]

[0059]

[0060] Currently, the above type II structure can be used to feed back the right-singular vectors (columns ofVmatrix). The same type II structure is used to feed back the columns ofUmatrix as well. In addition, the singular values from the diagonal matrix in the type II CSI report are provided as feedback. This extra feedback is expected to be much smaller in comparison since a typical deployment scenario would have .

[0061] We will typically have and hence, we can assume the remaining corresponding singular values in matrix to be zero while computing matrix . Similarly, if we have , we assume the remaining corresponding singular values in matrix to be zero. In either case, we might instead want to feedback max( ) singular values to the gNB and use the same while computing matrix .

[0062] Current type II feedback comprises only of the right-singular vectors (columns ofVmatrix). The extra feedback (columns ofUmatrix and singular values from the diagonal matrix ) can either be sent along with existing feedback as part of the same CSI report. Otherwise, this extra feedback can be sent separately, possibly with lower or higher periodicity, to reduce the overall feedback overhead even more.

[0063] As mentioned in step 2 (interference-covariance feedback), for the current CSI acquisition instance, the UE 100 estimates the downlink interference covariance matrix (of dimension ) and performs eigenvalue decomposition (EVD) on it:

[0064]

[0065] where denotes the conjugate-transpose of matrix and is a diagonal matrix containing the eigenvalues of in descending order of magnitude. Here, it is assumed that the ports at the receive side were used for current CSI occasion. The gNB can then attempt a v''-layer approximation using the v''eigenvectors.

[0066] Similar to Type II channel-state PMI, Type II interference covariance matrix assumes decomposition, where , is composed ofKoversampled 2D DFT beams. ConsideringMsubbands as before, the following matrix dimensions are present:

[0067]

[0068]

[0069]

[0070] The above type II codebook decomposition is used to feed back v''eigenvectors of matrix. In addition, the real-valued eigenvalues from the diagonal matrix in the type II codebook-based interference covariance matrix feedback is also provided as feedback. This extra feedback is expected to be even smaller in comparison to the proposed extra feedback for channel-state, since the eigenvalues are expected to be real-valued.

[0071] The extra interference-covariance feedback (columns ofQmatrix and eigenvalues from the diagonal matrix ) can either be sent along with the channel-state report. Otherwise, this interference-covariance feedback can also be sent separately, possibly with lower or higher periodicity, to reduce the overall CSI feedback overhead even more. Once the gNB 200a receives the feedback quantities for both channel-state and interference-covariance from all the users. The gNB 200a can jointly determine the users to be (co-)scheduled and the transmit ports to mute or power-adapt. For example, the gNB 200a can suitably determine the transmit ports to mute / adapt to incur minimal capacity loss. The gNB 200a even dynamically changes the transmit ports to mute / adapt from slot-to-slot.

[0072] FIG. 3 depicts a scenario, wherein partially-unmuted CSI port patterns are used for channel-state and / or interference-covariance feedback. In step 1, the gNB 200a configures the UEs 100 to measure channel-state over v layers (right-singular sense) and v'layers (left-singular sense), and interference covariance over v''layers for the partially- / fully-unmuted CSI port pattern. In step 2, the UE 100 measures channel-state and interference covariance for the pattern and feeds back the CQI, PMI and RI information. This PMI information, (just like discussed in FIG. 2), consists of the v right-singular and v'left-singular vectors, and the corresponding singular values. The PMI information also includes, (just like in discussed in FIG. 2), v''eigenvectors of matrix, and real-valued eigenvalues from the matrix. The UE 100 can additionally send some more CSI-related information to the gNB for ease of (co-) scheduling and port muting / unmuting. In step 3, the gNB 200a collects the channel-state and interference covariance information from all UEs 100. The gNB 200a then uses that information for (co-) scheduling users and to decide on the transmit port(s) to mute or unmute.

[0073] Additional CSI-related information that the UE 100 can send to the gNB 200a in step 2 of the above procedure, or can utilize by itself as the gNB 200a configured threshold to determine the CSI reports to send to the gNB 200a, can comprise of an estimate performed by the UE 100 of the fraction of energy captured in the low-rank channel estimate it fed back to the gNB 200a. For example, it can be of the following forms:

[0074] (where theabs(·)is taken element-by-element)

[0075]

[0076] where denotes thei-th singular value of downlink channel matrix . This and other forms of fractions will help the gNB estimate the residual energy in the UE's downlink channel that was not fed back. Similarly, the UE can also share estimates of the fraction of energy captured in the low-rank interference covariance estimate to the gNB, using similar formulae as given above.

[0077] The wireless network (1000) obtains one or more downlink channel state information (CSI) feedback reports corresponding to the one or more CSI-RS port muting patterns. The one or more downlink CSI feedback reports includes at least one of, one or more CSI feedback reports having quantized version of an SVD decomposed downlink channel matrix and an EVD decomposed downlink interference matrix for the one or more CSI-RS port muting patterns. Further, the wireless network (1000) determines, to mute at least one CSI-RS port belonging to the one or more CSI-RS port muting patterns or to unmute at least one CSI-RS port belonging to the network entity (200), based on the received one or more downlink CSI feedback reports.

[0078] Further, the wireless network (1000) estimates one or more fractions of energy captured for one or more CSI-RS port muting patterns. Further, the wireless network (1000) determines to mute at least one CSI-RS port belonging to the one or more CSI-RS port muting patterns or to unmute at least one CSI-RS port belonging to the network entity (200), based on the one or more energy feedback reports.

[0079] FIG. 4 is a sequence diagram illustrating a method for handling the port adaptation in the wireless network, according to an embodiment as disclosed herein. At step 1, the gNB 200a configures the UEs 100 to measure channel-state for max(v,v') layers (i.e., first layers) and interference state for v'' layers (i.e., second layers) for the fully- / partially-unmuted CSI port pattern. At step 2, the gNB 200a receives the information (Legacy CSI report - V (T2 codebook) and additional NES-specific reporting of channel-state (Σ and U) or interference-state (Q and Λ), conditional upon comparison analysis of the corresponding energy-estimates for channel-state and interference-state against gNB-configured thresholds by the UE (100). At step 3, the gNB 200a collects the channel and interference information from all UEs and uses that for co-scheduling users.

[0080] FIG. 5 shows various hardware components of the network entity (200), according to an embodiment as disclosed herein. In an embodiment, the network entity (200) includes a processor (210), a communicator (220), a memory (230), and a port adaptation controller (240). The processor (210) is coupled with the communicator (220), the memory (230), and the port adaptation controller (240).

[0081] The port adaptation controller (240) configures the UE (100) to measure channel-state for at least one first layer and an interference state for at least one second layer for at least one of: the fully unmuted CSI port pattern and the partially unmuted CSI port pattern. Upon the measurement, the port adaptation controller (240) receives at least one reporting information for at least one of: the fully unmuted CSI port pattern and the partially unmuted CSI port pattern. The at least one reporting information includes at least one of: the CQI, the PMI, and the RI. Based on the at least one received reporting information, the port adaptation controller (240) handles the port adaptation using at least one of: an explicit reconfiguration of its antenna ports and an implicit muting, unmuting or application of an appropriate precoding weight on its antenna ports.

[0082] The port adaptation controller (240) obtains the channel information and interference information from the UE (100) from the plurality of UEs. Further, the port adaptation controller (240) uses the obtained channel information and the obtained interference information for co-scheduling of the at least one UE from the plurality of UEs. Further, the port adaptation controller (240) receives a feedback about a measured interference covariance information from the UE (100).

[0083] In an embodiment, the port adaptation controller (240) receives the at least one downlink CSI feedback report having at least one of: a quantized version of a SVD decomposed downlink channel matrix and a quantized version of an EVD decomposed downlink interference covariance matrix for the one or more CSI-RS port muting patterns upon measuring the one or more downlink CSI for the one or more CSI-RS port muting patterns at the UE (100). The at least one CSI feedback report comprises at least one PMI parameter. The at least one PMI parameter includes at least one of: one or more right singular vectors, one or more left singular vectors, and one or more singular values corresponding to the SVD decomposed downlink channel matrix, and at least one of: one or more eigenvectors, and one or more eigenvalues corresponding to the EVD decomposed downlink interference covariance matrix for the one or more CSI-RS port muting patterns. Further, the port adaptation controller (240) determines to mute at least one CSI-RS port belonging to the one or more CSI-RS port muting patterns or to unmute at least one CSI-RS port belonging to the network entity (200), based on the received at least one CSI feedback report.

[0084] The one or more downlink CSI corresponding to the one or more CSI-RS port muting patterns comprise the CQI, the PMI, the RI, and the interference-state indicator.

[0085] The one or more downlink CSI feedback reports includes of at least one of: one or more quantized versions of at least a singular-value decomposition (SVD) decomposed downlink channel matrix and one or more quantized versions of at least an eigenvalue decomposition (EVD) decomposed downlink interference covariance matrix. The one or more CSI-RS port muting patterns are at least one of: one or more fully unmuted CSI-RS port muting patterns, and one or more partially unmuted CSI-RS port muting patterns.

[0086] In an embodiment, the one or more right singular vectors and the one or more left singular vectors comprise at least one of: one or more wideband and long-term downlink channel properties, and one or more sub-band and short-term downlink channel properties. The one or more eigenvectors includes at least one of: one or more wideband and long-term downlink interference properties, and one or more sub-band and short-term downlink interference properties. The number of right singular vectors and the number of left singular vectors fed back by the UE (100) are same. In an embodiment, the number of right singular vectors and the number of left singular vectors fed back by the UE (100) may be different. The number of right singular vectors and the number of left singular vectors fed back by the UE (100) may be different, the remaining singular values will be assumed to be zero.

[0087] In an embodiment, the port adaptation controller (240) configures the UE (100) to measure the one or more downlink CSI for the one or more CSI-RS port muting patterns.

[0088] In an embodiment, the port adaptation controller (240) determines whether to mute, at least one CSI-RS port belonging to the one or more CSI-RS port muting patterns or to unmute at least one CSI-RS port belonging to the network entity (200), based upon at least one of: the received CSI reports from the at least one UE (100) and by: estimating residual energy, which has not been fed back, in the one or more downlink channel-state and in the one or more downlink interference-state corresponding to the at least one CSI-RS port muting pattern of the at least one UE (100).

[0089] In an embodiment, the port adaptation controller (240) determines at least one downlink channel matrix for one or more CSI-RS transmission corresponding to the one or more CSI-RS port muting patterns.

[0090] In an embodiment, the downlink channel matrix is obtained from at least one right precoder matrix having one or more right singular vectors. The at least one right precoder matrix has total number of rows equal to total number of CSI-RS transmit ports at a CSI-RS transmitter side, and total number of columns equal to a first number of right-singular CSI-RS layers configured by the network entity (200) or determined by the UE (100) based on comparison analysis. In an embodiment, the at least one downlink channel matrix is obtained from at least one left precoder matrix having one or more left singular vectors, wherein the at least one left precoder matrix has total number of rows equal to total number of CSI-RS receiving antenna ports at a CSI-RS receiver side, and total number of columns equal to a second number of left-singular CSI-RS layers configured by the network entity (200) or determined by the UE (100) based on comparison analysis. In an embodiment, the one or more singular values of the estimated downlink channel matrix configured by the network entity (200) or determined by the UE (100) based on comparison analysis as obtained from the at least one UE (100).

[0091] The at least one right precoder matrix is obtained from at least one appropriate beamforming basis vector comprising at least one of at least one oversampled 2D-DFT (discrete Fourier transform) basis, at least one Slepian basis, and at least one polynomial basis and at least one basis determined using machine-learning methods. The at least one left precoder matrix is obtained from at least one appropriate beamforming basis vector comprising at least one of at least one oversampled 2D-DFT (discrete Fourier transform) basis, at least one Slepian basis, at least one polynomial basis and at least one basis determined using machine-learning methods.

[0092] In an embodiment, the port adaptation controller (240) determines at least one downlink interference covariance matrix for one or more CSI-RS transmission corresponding to the one or more CSI-RS port muting patterns. In an embodiment, the at least one downlink interference covariance matrix is obtained from at least one unitary matrix having one or more eigenvectors, wherein the at least one unitary matrix has total number of rows and total number of columns equal to total number of CSI-RS receiving antenna ports at the CSI-RS receiver side indicated by UE (100) to the network entity (200) or configured by the network entity (200). In an embodiment, the at least one downlink interference covariance matrix is obtained from one or more eigenvalues of an estimated downlink interference covariance matrix as obtained from the at least one UE (100). The at least one unitary matrix is obtained from at least one appropriate beamforming basis vector comprising at least one of at least one oversampled 2D-DFT (discrete Fourier transform) basis, at least one Slepian basis, the at least one polynomial basis and at least one basis determined using machine-learning methods.

[0093] In an embodiment, a fraction of captured channel-state energy for the one or more CSI-RS port muting patterns is estimated and possibly fed back to the network entity (200) from a ratio of one or more singular values of the downlink channel matrix corresponding to the one or more CSI-RS port muting patterns, to the trace of a diagonal matrix containing one or more singular values in descending order of magnitude of the downlink channel matrix. In an embodiment, a fraction of captured interference-state energy for the one or more CSI-RS port muting patterns, is estimated and possibly fed back to the network entity (200) from a ratio of, one or more eigenvalues of the downlink interference covariance matrix corresponding to the one or more CSI-RS port muting patterns, to the trace of a diagonal matrix containing one or more eigenvalues in descending order of magnitude of the downlink interference covariance matrix.

[0094] In an embodiment, a fraction of captured channel-state energy for the one or more CSI-RS port muting patterns, is used by the UE (100) to determine to report channel-state in the one or more CSI feedback report via comparison analysis against thresholds configured by the network entity (200).

[0095] In an embodiment, a fraction of captured interference-state energy for the one or more CSI-RS port muting patterns, is used by the UE to determine to report interference-state in the one or more CSI feedback report via comparison analysis against thresholds configured by the network entity (200).

[0096] The port adaptation controller (240) is implemented by analog and / or digital circuits such as logic gates, integrated circuits, microprocessors, microcontrollers, memory circuits, passive electronic components, active electronic components, optical components, hardwired circuits and the like, and may optionally be driven by firmware.

[0097] The processor (210) may include one or a plurality of processors. The one or the plurality of processors may be a general-purpose processor, such as a central processing unit (CPU), an application processor (AP), or the like, a graphics-only processing unit such as a graphics processing unit (GPU), a visual processing unit (VPU), and / or an AI-dedicated processor such as a neural processing unit (NPU). The processor (210) may include multiple cores and is configured to execute the instructions stored in the memory (230).

[0098] Further, the processor (210) is configured to execute instructions stored in the memory (230) and to perform various processes. The communicator (220) is configured for communicating internally between internal hardware components and with external devices via one or more networks. The memory (230) also stores instructions to be executed by the processor (210). The memory (230) may include non-volatile storage elements. Examples of such non-volatile storage elements may include magnetic hard discs, optical discs, floppy discs, flash memories, or forms of electrically programmable memories (EPROM) or electrically erasable and programmable (EEPROM) memories. In addition, the memory (230) may, in some examples, be considered a non-transitory storage medium. The term "non-transitory" may indicate that the storage medium is not embodied in a carrier wave or a propagated signal. However, the term "non-transitory" should not be interpreted that the memory (230) is non-movable. In certain examples, a non-transitory storage medium may store data that can, over time, change (e.g., in Random Access Memory (RAM) or cache).

[0099] Although FIG. 5 shows various hardware components of the network entity (200) but it is to be understood that an embodiment is not limited thereon. In an embodiment, the network entity (200) may include less or more number of components. Further, the labels or names of the components are used only for illustrative purposes and does not limit the scope of the disclosure. One or more components can be combined together to perform the same or substantially similar function in the network entity (200).

[0100] FIG. 6 shows various hardware components of the UE (100), according to an embodiment as disclosed herein. In an embodiment, the UE (100) includes a processor (110), a communicator (120), a memory (130), and a port adaptation controller (140). The processor (110) is coupled with the communicator (120), the memory (130), and the port adaptation controller (140).

[0101] The port adaptation controller (140) measures the channel-state for at least one first layer and the interference state for at least one second layer for at least one of: the fully unmuted CSI port pattern and the partially unmuted CSI port pattern. Further, the port adaptation controller (140) sends at least one reporting information for at least one of: the fully unmuted CSI port pattern and the partially unmuted CSI port pattern upon the measurement. Based on the at least one received reporting information, further, the port adaptation controller (140) handles the port adaptation using at least one of: an explicit reconfiguration of the antenna ports at the network entity (200) and an implicit muting, unmuting or application of an appropriate precoding weight on the antenna ports at the network entity (200).

[0102] Further, the port adaptation controller (140) sends the channel information and interference information to network entity (200), wherein the channel information and the obtained interference information is used for co-scheduling of the at least one UE from the plurality of UEs. Further, the port adaptation controller (140) feedbacks a measured interference covariance information to the network entity (200).

[0103] The one or more downlink CSI corresponding to the one or more CSI-RS port muting patterns includes the CQI, the PMI, the RI, and the interference-state indicator. The one or more downlink CSI feedback reports includes of at least one of: one or more quantized versions of at least a singular-value decomposition (SVD) decomposed downlink channel matrix and one or more quantized versions of at least an eigenvalue decomposition (EVD) decomposed downlink interference covariance matrix. The one or more CSI-RS port muting patterns are at least one of: one or more fully unmuted CSI-RS port muting patterns, and one or more partially unmuted CSI-RS port muting patterns.

[0104] Further, the port adaptation controller (140) estimates one or more fractions of energy captured by a to-be-reported downlink channel matrix and one or more fractions of energy captured by a to-be-reported downlink interference covariance matrix corresponding to the one or more CSI-RS port muting patterns. Further, the port adaptation controller (140) transmits the one or more energy feedback reports including the one or more fractions of energy as captured for the one or more CSI-RS port muting patterns.

[0105] Further, the port adaptation controller (140) transmits the one or more CSI feedback reports to the network entity (200). The one or more CSI feedback reports includes at least one of: the quantized version of the SVD decomposed downlink channel matrix and quantized version of an EVD decomposed downlink interference matrix for the one or more CSI-RS port muting patterns. Further, the port adaptation controller (140) transmits to, the at least one network entity (200), one or more energy-feedback reports on estimated fraction of energy captured by the downlink channel matrix and estimated fraction of energy captured by the downlink interference matrix for the one or more CSI-RS muting patterns.

[0106] Further, the port adaptation controller (140) transmits the plurality of CSI feedback reports corresponding to the plurality of CSI-RS port muting patterns. The plurality of CSI feedback reports comprise a plurality of corresponding PMIs. Further, the port adaptation controller (140) transmits the plurality of energy-feedback reports on estimated fraction of energy captured for the plurality of CSI-RS port muting patterns.

[0107] In an embodiment, the fraction of captured channel-state energy for the one or more CSI-RS port muting patterns, is estimated from a ratio of, one or more singular values of the downlink channel matrix corresponding to the one or more CSI-RS port muting patterns, to the trace of the diagonal matrix containing one or more singular values in descending order of magnitude of the downlink channel matrix.

[0108] In an embodiment, the fraction of captured interference-state energy for the one or more CSI-RS port muting patterns, is estimated from a ratio of, one or more eigenvalues of the downlink interference covariance matrix corresponding to the one or more CSI-RS port muting patterns, to the trace of the diagonal matrix containing one or more eigenvalues in descending order of magnitude of the downlink interference covariance matrix, wherein the fractions of captured channel-state energy for the one or more CSI-RS port muting patterns, is used by the UE to determine to report channel-state in the one or more CSI feedback report via comparison analysis against thresholds configured by the network entity (200),

[0109] In an embodiment, the fractions of captured interference-state energy for the one or more CSI-RS port muting patterns, is used by the UE to determine to report interference-state in the one or more CSI feedback report via comparison analysis against thresholds configured by the network entity (200).

[0110] The port adaptation controller (140) is implemented by analog and / or digital circuits such as logic gates, integrated circuits, microprocessors, microcontrollers, memory circuits, passive electronic components, active electronic components, optical components, hardwired circuits and the like, and may optionally be driven by firmware.

[0111] The processor (110) may include one or a plurality of processors. The one or the plurality of processors may be a general-purpose processor, such as a central processing unit (CPU), an application processor (AP), or the like, a graphics-only processing unit such as a graphics processing unit (GPU), a visual processing unit (VPU), and / or an AI-dedicated processor such as a neural processing unit (NPU). The processor (110) may include multiple cores and is configured to execute the instructions stored in the memory (130).

[0112] Further, the processor (110) is configured to execute instructions stored in the memory (130) and to perform various processes. The communicator (120) is configured for communicating internally between internal hardware components and with external devices via one or more networks. The memory (130) also stores instructions to be executed by the processor (110). The memory (130) may include non-volatile storage elements. Examples of such non-volatile storage elements may include magnetic hard discs, optical discs, floppy discs, flash memories, or forms of electrically programmable memories (EPROM) or electrically erasable and programmable (EEPROM) memories. In addition, the memory (130) may, in some examples, be considered a non-transitory storage medium. The term "non-transitory" may indicate that the storage medium is not embodied in a carrier wave or a propagated signal. However, the term "non-transitory" should not be interpreted that the memory (130) is non-movable. In certain examples, a non-transitory storage medium may store data that can, over time, change (e.g., in Random Access Memory (RAM) or cache).

[0113] Although FIG. 6 shows various hardware components of the UE (100) but it is to be understood that an embodiment is not limited thereon. In an embodiment, the UE (100) may include less or more number of components. Further, the labels or names of the components are used only for illustrative purposes and does not limit the scope of the disclosure. One or more components can be combined together to perform the same or substantially similar function in the UE (100).

[0114] FIG. 7 is a flow chart (S700) illustrating a method for handling a port adaptation in a wireless network by the network entity (200), according to an embodiment as disclosed herein. The operations (S702-S706) are handled by the port adaptation controller (240).

[0115] At S702, the method includes configuring the at least one UE (100) to measure channel-state for the at least one first layer and the interference state for at least one second layer for at least one of: the fully unmuted CSI port pattern and the partially unmuted CSI port pattern. At S704, the method includes receiving the at least one reporting information for at least one of: the fully unmuted CSI port pattern and the partially unmuted CSI port pattern upon the measurement. At S706, the method includes handling the port adaptation based on the at least one received reporting information.

[0116] FIG. 8 is a flow chart (S800) illustrating a method for handling a port adaptation in a wireless network by the UE (100), according to an embodiment as disclosed herein. The operations (S802-S806) are handled by the port adaptation controller (140).

[0117] At S802, the method includes measuring the channel-state for the at least one first layer and the interference state for the at least one second layer for at least one of: the fully unmuted CSI port pattern and the partially unmuted CSI port pattern. At S804, the method includes sending the at least one reporting information for at least one of: the fully unmuted CSI port pattern and the partially unmuted CSI port pattern upon the measurement. At S806, the method includes handling the network-side port adaptation to be used for subsequent data reception, based on the at least one fed-back reporting information.

[0118] An embodiment disclosed herein can be implemented through at least one software program running on at least one hardware device and performing network management functions to control the network elements. The elements include blocks which can be at least one of a hardware device, or a combination of hardware device and software module.

[0119] The embodiment disclosed herein describes methods and systems for providing CSI feedback that will allow the gNB to perform port muting and port power-adaptation dynamically. Therefore, it is understood that the scope of the protection is extended to such a program and in addition to a computer readable means having a message therein, such computer readable storage means contain program code means for implementation of one or more steps of the method, when the program runs on a server or mobile deviceor any suitable programmable device. The method is implemented in at least one embodiment through or together with a software program written in e.g., Very high speed integrated circuit Hardware Description Language (VHDL) another programming language, or implemented by one or more VHDL or several software modules being executed on at least one hardware device. The hardware device can be any kind of portable device that can be programmed. The device may also include means which could be e.g., hardware means like e.g., an ASIC, or a combination of hardware and software means, e.g. an ASIC and an FPGA, or at least one microprocessor and at least one memory with software modules located therein. An embodiment described herein could be implemented partly in hardware and partly in software. Alternatively, the disclosure may be implemented on different hardware devices, e.g., using a plurality of CPUs.

[0120] The specific examples provided to explain the embodiments according to the present disclosure are merely a combination of each standard, method, detail method, and operation, and the various embodiments described herein can be performed through a combination of at least two or more techniques among the various techniques described. In addition, at this time, it can be performed according to a method determined through a combination of one or at least two or more of the aforementioned techniques. For example, it may be possible to perform a combination of parts of the operation of one embodiment with parts of the operation of another embodiment.

[0121] The foregoing description of the specific embodiment will so fully reveal the general nature of an embodiment herein that others can, by applying current knowledge, readily modify and / or adapt for various applications such specific embodiment without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed an embodiment. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while an embodiment herein has been described in terms of an embodiment, those skilled in the art will recognize that an embodiment herein can be practiced with modification within the scope of an embodiment as described herein.

Claims

1.A method for handling a port adaptation in a wireless network by a network entity, comprising:configuring at least one user equipment (UE) to report one or more downlink channel state information (CSI) feedback reports, wherein the one or more downlink CSI feedback reports comprise at least one of estimated channel information or estimated interference information for at least one of a fully unmuted CSI port pattern or a partially unmuted CSI port pattern;receiving, from the at least one UE, the one or more downlink CSI feedback reports for at least one of the fully unmuted CSI port pattern or the partially unmuted CSI port pattern; andhandling the port adaptation based on the received one or more downlink CSI feedback reports.2.The method of claim 1, wherein the one or more downlink CSI feedback reports comprise at least one of a Channel Quality Indicator (CQI), a precoding matrix indicator (PMI), a rank indicator (RI), an interference-state indicator, or interference covariance information.3.The method of claim 1, wherein the one or more downlink CSI feedback reports comprise of at least one of one or more quantized versions of at least a singular-value decomposition (SVD) decomposed downlink channel matrix or one or more quantized versions of at least an eigenvalue decomposition (EVD) decomposed downlink interference covariance matrix.4.The method of claim 1, wherein the one or more downlink CSI feedback reports comprise at least one precoding matrix indicator (PMI) parameter, wherein the at least one PMI parameter comprises at least one of one or more right singular vectors, one or more left singular vectors, or one or more singular values corresponding to a singular-value decomposition (SVD) decomposed downlink channel matrix, and at least one of one or more eigenvectors or one or more eigenvalues corresponding to an eigenvalue decomposition (EVD) decomposed downlink interference covariance matrix for the one or more CSI-reference signal (CSI-RS) port muting patterns.5.The method of claim 1, wherein the handling the port adaptation comprises determining to mute at least one CSI-reference signal (CSI-RS) port belonging to one or more CSI-RS port muting patterns or to unmute at least one CSI-RS port belonging to the network entity, based on the received one or more downlink CSI feedback reports.6.The method of claim 4, wherein in case a number of right singular vectors and a number of left singular vectors are different, remaining singular values are assumed to be zero.7.The method of claim 4, wherein the one or more right singular vectors, the one or more left singular vectors and the one or more eigenvectors comprise at least one of one or more wideband and long-term downlink channel properties or one or more sub-band and short-term downlink channel properties.8.A network entity, comprising:a processor;a memory; anda port adaptation controller, coupled with the processor and the memory, configured to:configure at least one user equipment (UE) to report one or more downlink channel state information (CSI) feedback reports, wherein the one or more downlink CSI feedback reports comprise at least one of estimated channel information or estimated interference information for at least one of a fully unmuted CSI port pattern or a partially unmuted CSI port pattern;receive, from the at least one UE, the one or more downlink CSI feedback reports for at least one of the fully unmuted CSI port pattern or the partially unmuted CSI port pattern; andhandle the port adaptation based on the received one or more downlink CSI feedback reports.9.The network entity of claim 8, wherein the one or more downlink CSI feedback reports comprise at least one of a Channel Quality Indicator (CQI), a precoding matrix indicator (PMI), a rank indicator (RI), an interference-state indicator, or interference covariance information.10.The network entity of claim 8, wherein the one or more downlink CSI feedback reports comprise of at least one of one or more quantized versions of at least a singular-value decomposition (SVD) decomposed downlink channel matrix or one or more quantized versions of at least an eigenvalue decomposition (EVD) decomposed downlink interference covariance matrix.11.The network entity of claim 8, wherein the one or more downlink CSI feedback reports comprise at least one precoding matrix indicator (PMI) parameter, wherein the at least one PMI parameter comprises at least one of one or more right singular vectors, one or more left singular vectors, or one or more singular values corresponding to a singular-value decomposition (SVD) decomposed downlink channel matrix, and at least one of one or more eigenvectors or one or more eigenvalues corresponding to an eigenvalue decomposition (EVD) decomposed downlink interference covariance matrix for the one or more CSI-reference signal (CSI-RS) port muting patterns.12.The network entity of claim 8, wherein the handling the port adaptation comprises determining to mute at least one CSI-reference signal (CSI-RS) port belonging to one or more CSI-RS port muting patterns or to unmute at least one CSI-RS port belonging to the network entity, based on the received one or more downlink CSI feedback reports.13.The network entity of claim 11, wherein in case a number of right singular vectors and a number of left singular vectors are different, remaining singular values are assumed to be zero.14.The network entity of claim 11, wherein the one or more right singular vectors, the one or more left singular vectors and the one or more eigenvectors comprise at least one of one or more wideband and long-term downlink channel properties or one or more sub-band and short-term downlink channel properties.15.A method performed by a User Equipment (UE), comprising:measuring a channel-state for at least one first layer and an interference state for at least one second layer for at least one of a fully unmuted channel state information (CSI) port pattern or a partially unmuted CSI port pattern; andsending, to a network entity, one or more downlink CSI feedback reports for at least one of the fully unmuted CSI port pattern or the partially unmuted CSI port pattern upon the measurement.

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