System and method for efficient channel state information-reference signal resources transmission

Abstract

The present disclosure provides a system (108) and a method (800) for efficient channel state information-reference signal (CSI-RS) resources transmission. The system (108) determines a channel sounding configuration and correspondingly configures resource(s) to sound a set of ports for deployment of UEs (104). The system (108) transmits, to the UEs (104), a first 5 reference signal in a first transmission period with occasional sounding of a full set of ports and transmits a second reference signal in a second transmission period with frequent sounding of a subset of ports. The system (108) receives Channel State Information (CSI) reports from the UEs (104) for a first transmission period corresponding to first channel vectors associated with the full set of ports and for a second transmission period 0 corresponding to second channel vectors associated with the subset of ports. The system (108) determines, from the received CSI reports, a precoding matrix for data transmission.

Description

SYSTEM AND METHOD FOR EFFICIENT CHANNEL STATE INFORMATION-REFERENCE SIGNAL RESOURCES TRANSMISSION FIELD OF INVENTION

[0001] The embodiments of the present disclosure generally relate to a field of wireless networks. More particularly, the present disclosure relates to a system and a method for efficient channel state information reference signal resources transmission. BACKGROUND

[0002] The following description of the related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section is used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of the prior art.

[0003] With each generation of telecommunication network, the number of antennae deployed in base stations is increasing. For instance, base stations of recent generations have antennae in the order of hundreds and thousands, which are implemented as massive multiple input multiple output (MIMO) arrays to increase the capacity and performance of the network. With a larger number of antenna array elements, the design of antenna arrays has enhanced from uniform linear array (ULA) to uniform planar array (UPA) and non-uniform planar array (NUPA). Typically, in a planar array design, the number of antenna elements (without virtualization) / antenna ports in the horizontal and vertical dimension, represented by N1 and N2, respectively, are selected based on the form factor of the base station (where N2= 1 in the ULA designs). The choice of N1 and N2 is also governed by the user distribution characteristics of the serving cell.

[0004] Channel state information (CSI)-reference signals (RS) are transmitted through each of the antenna ports to estimate downlink radio channel quality. Some earlier releases of the technical standards supported certain predefined N1, N2 values for the base station antenna layout such that the number of CSI-RS ports (represented as PCSIRS) is specified as 2N1N2≤32. While implementing closed-loop MIMO, user equipments (UEs) generate and report channel measurement report (CMR), for which the base station is required to transmit downlink (DL) CSI-RS signals for sounding the CSI-RS antenna ports up to 32.

[0005] In some recent releases, for UEs that support a larger number of base station antennae, the number of CSI-RS ports specifying the number of digitally pre-coded ports canbe greater than 32, such as up to 128. In such releases, channel sounding is enabled with greater than 32 antenna ports by using K M-port resources in a single resource set, i.e., where ^^CSIRS=N is the number of CSI-RS ports supported at a single transmit receive point (sTRP) site, with N= K∗M. Such configurations allow the number of CSI-RS antenna ports to be scaled up to higher order MIMO and higher operating frequencies, like sub-6 GHz, mm Wave, and THz bands.

[0006] However, increasing CSI-RS resources to K (where, K=N / M) to support larger number of ports requires extending the CSI-RS pattern in time or frequency or both, thereby requiring a larger number of resource elements (REs) for transmitting reference signals. The increase in reference signal REs also increases the CSI-RS resource overhead on the downlink, and the increment is also on the dimension of the number of CSI-RS ports. Consequentially, the network observes a huge reduction in the DL throughput, guided by multiple factors, such as, the number of resources in a resource set, the frequency domain density of the resources (0.5 or 1), and the periodicity of CSI-RS (also known as the rate of CSI occasions). This significantly degrades the network load and capacity in advanced wireless systems with large-scale antennas and large antenna ports, and is a major problem.

[0007] Addressing the problem by handling any of the aforementioned guiding factors is challenging in a practical network, as each factor is critical for determining an accurate CSI and plays a role in improving network performance. For instance, the number of resources (which may also be derived as K=N / M for the case of aggregated resources) is likely fixed as they are essential to sound all antenna ports used by the base station. The frequency domain density of resources helps to efficiently manage the frequency-selectivity of the channel. A higher density is often required to improve the channel estimation accuracy at the UE, and to achieve enhanced spectral efficiency, coverage and robustness to channel variations. Further, the CSI-RS periodicity is typically identified based on the coherence time of the propagation channel, and its increase from the determined value affects the network performance. The network generally determines the period or transmission occasion of CSI-RS based on user mobility, channel variability, UE capabilities, and the scale of antenna configurations, among others. CSI-RS overhead reduction in the Release-19 enhanced CSI framework includes configuring CSI-RS resources up to 128 ports, where K M-port resources configured in a single resource are set to sound PCSI-RS = N CSI-RS ports, where N=K∗M. Consequently, the base station (gNB) expends more resources and more ports, while UE experiences higher CSI compute complexity. These implications could be trivial in rural deployments, but non-trivial in dense urban environments, smart city infrastructure, and industrial Internet-of- Things (IoT), etc., that requires frequent CSI occasions for accurate and reliable network quality.

[0008] Therefore, there is a need for a method and a system for efficiently transmitting CSI-RS resources that improves DL throughput and addresses other problems mentioned above. OBJECTS OF THE INVENTION

[0009] Some of the objects of the present disclosure, which at least one embodiment herein satisfies are listed herein below.

[0010] It is an object of the present disclosure to provide a system and a method for efficient channel state information reference signal resources transmission that determines a channel sounding configuration and correspondingly configures resources to sound a set of ports for deployment scenario associated with user equipments (UEs).

[0011] It is an object of the present disclosure to provide a system that transmits a first reference signal in a first transmission period with occasional sounding of a full set of ports from the set of ports and transmits a second reference signal in a second transmission period with frequent sounding of a subset of ports from the set of ports to the UEs, where the first transmission period and the second transmission period are based on network conditions.

[0012] It is an object of the present disclosure to provide a system that receives channel state information (CSI) reports from the UEs (104) for a first transmission period corresponding to first channel vectors associated with the full set of ports and for a second transmission period corresponding to second channel vectors associated with the subset of ports, where the subset of ports indicates a subset of the full set of ports.

[0013] It is an object of the present disclosure to provide a system that determines from the received CSI reports, a precoding matrix for downlink data transmission. SUMMARY

[0014] This section is provided to introduce certain objects and aspects of the present disclosure in a simplified form that are further described below in the detailed description. This summary is not intended to identify the key features or the scope of the claimed subject matter.

[0015] In an aspect, the present disclosure relates to a system for efficient channel state information (CSI) reference signal (RS) transmission, the system includes a processorcommunicatively coupled to a base station. A memory operatively coupled with the processor, where the memory stores instructions which, when executed by the processor, causes the processor to determine a channel sounding configuration and correspondingly configure one or more resource(s) to sound a set of ports for deployment scenario associated with one or more UEs. The processor transmits, to the one or more UEs, a first reference signal in a first transmission period with occasional sounding of a full set of ports from the set of ports and transmit a second reference signal in a second transmission period with frequent sounding of a subset of ports from the set of ports, wherein the first transmission period and the second transmission period are based on network conditions. The processor receives one or more channel state information (CSI) reports from the one or more UEs for a first transmission period corresponding to one or more first channel vectors associated with the full set of ports and for a second transmission period corresponding to one or more second channel vectors associated with the subset of ports, where the subset of ports indicates a subset of the full set of ports. The processor determines, from the received one or more CSI reports, a precoding matrix for downlink data transmission.

[0016] In an embodiment, to determine the deployment scenario associated with the one or more UEs, the processor may be configured to determine one or more distribution characteristics associated with the one or more UEs. The processor may be configured to determine that the one or more UEs are in an azimuth plane based on the determined one or more distribution characteristics. The processor may be configured to map the one or more resource(s) to sound the set of ports of an antenna array, where the mapping may include assigning the one or more resource(s) to the set of ports arranged in horizontal directions across the antenna array to provide beamforming resolution in the azimuth plane.

[0017] In an embodiment, based on the determination one or more UEs are in the azimuth plane, the processor may be configured to transmit, in the first transmission period, the one or more resource(s) mapped to the full set of ports to the one or more UEs to identify, one or more first spatial domain (SD) basis vectors corresponding to the one or more first channel vectors. The processor may be configured to receive, from the one or more UEs, a first CSI report with codeword indices including a horizontal basis vector index and a vertical basis vector index associated with the azimuth plane and a corresponding elevation plane. The processor may be configured to generate a first precoding matrix based on the first CSI report. The processor may be configured to subsequently transmit, in the second transmission period, a reduced subset of ports to track variations in the azimuth plane. The processor may be configured to receive, from the one or more UEs, a second CSI feedback reportcomprising at least an updated horizontal basis vector index indicating the variations in the azimuth plane. The processor may be configured to generate a second precoding matrix based on the second CSI report.

[0018] In an embodiment, to determine the deployment scenario associated with the one or more UEs, the processor may be configured to determine one or more distribution characteristics associated with the one or more UEs. The processor may be configured to determine that the one or more UEs are in an elevation plane based on the determined one or more distribution characteristics. The processor may be configured to map the one or more resource(s) to sound the set of ports of an antenna array, where the mapping may include assigning the one or more resource(s) to the set of ports arranged in vertical directions across the antenna array to provide beamforming resolution in the elevation plane.

[0019] In an embodiment, based on the determination that the UEs are in the elevation plane, the processor may be configured to transmit, in the first transmission period, the one or more resource(s) mapped to the full set of ports to the one or more UEs to identify, one or more first spatial domain (SD) basis vectors corresponding to the one or more first channel vectors. The processor may be configured to receive, from the one or more UEs, a first CSI report with codeword indices including a vertical basis vector index and a horizontal basis vector index associated with the elevation plane and a corresponding azimuth plane. The processor may be configured to generate a first precoding matrix based on the first CSI report. The processor may be configured to subsequently transmit, in the second transmission period, a reduced subset of ports to track variations in the elevation plane. The processor may be configured to receive, from the one or more UEs, a second CSI feedback report including at least an updated vertical basis vector index indicating the variations in the elevation plane. The processor may be configured to generate a second precoding matrix based on the second CSI report.

[0020] In an embodiment, to determine the deployment scenario associated with one or more UEs, the processor may be configured to use a conventional approach or an AI based approach for determining UE distribution estimation or spatial flatness estimation either instantaneously or in a semi-static or in a static manner, where the processor may be configured to perform signalling and receive acknowledgement to identify the conventional approach or the AI based approach. The processor may be configured to configure and transmit one or more signals to the one or more UEs indicating RRC signalling, medium access control (MAC) Control Element (CE) signalling or downlink control information(DCI) signalling, and correspondingly receive an acknowledgement from the one or more UEs.

[0021] In an embodiment, to determine granularity associated with the first transmission period and the second transmission period, the processor may be configured to use a first conventional approach or a first AI based approach for determining one or more channel variations due to user mobility, environmental changes, or network congestion, where the processor may be configured to perform signalling and receive acknowledgement to identify the first conventional approach or the first AI based approach. The processor may be configured to configure and transmit one or more signals to the one or more UEs indicating RRC signalling, MAC CE signalling or DCI signalling, and correspondingly receive an acknowledgement from the one or more UEs.

[0022] In an embodiment, based on a non-existence of spatial flatness associated with the deployment scenario, the processor may be configured to configure the subset of ports to be mapped and sounded continuously or sparsely across horizontal and vertical dimensions in the second transmission period. The processor may be configured to configure and transmit one or more signals to the one or more UEs indicating RRC signalling, MAC CE signalling or DCI signalling, and correspondingly receive an acknowledgement from the one or more UEs. The processor may be configured to subsequently receive from the one or more UEs, first information associated with the full set of ports derived from the second information associated with the subset of ports, where the first information may be generated using a second conventional approach or a second AI based approach, and where the processor may be configured to perform signalling and receive acknowledgement to identify the second conventional approach or the second AI based approach.

[0023] In an embodiment, to implement a learning method associated with the processor may be configured to use a signalling and an acknowledgement to indicate if a conventional or an AI / ML technique is implemented.

[0024] In an aspect, the present disclosure relates to a method for efficient channel state information (CSI) reference signal (RS) transmission. The method includes determining, a channel sounding configuration and correspondingly configuring one or more resources to sound a set of ports for deployment scenario associated with one or more UEs. The method includes transmitting, to the one or more UEs, a first reference signal in a first transmission period with occasional sounding of a full set of ports from the set of ports and transmitting a second reference signal in a second transmission period with frequent sounding of a subset of ports from the set of ports, where the first transmission period and the second transmissionperiod are based on network conditions. The method includes receiving, one or more channel state information (CSI) reports from the one or more UEs including one or more first channel vectors associated with the full set of ports and for a second transmission period corresponding to one or more second channel vectors associated with the subset of ports, where the subset of ports indicates a subset of the full set of ports. The method includes determining, from the received one or more CSI reports, a precoding matrix for downlink data transmission.

[0025] In an embodiment, for determining the deployment scenario associated with the one or more UEs, the method may include determining, one or more distribution characteristics associated with the one or more UEs. The method may include determining, that the one or more UEs are in an azimuth plane based on the determined one or more distribution characteristics. The method may include mapping, the one or more resources to sound the set of ports of an antenna array, where the mapping includes assigning the one or more resource(s) to the set of ports arranged in horizontal directions across the antenna array to provide beamforming resolution in the azimuth plane.

[0026] In an embodiment, based on the determination that the one or more UEs are in the azimuth plane, the method may include transmitting, in the first transmission period, the one or more resource(s) mapped to the full set of ports to the one or more UEs (104) for identifying, one or more first spatial domain (SD) basis vectors corresponding to the one or more first channel vectors. The method may include receiving, from the one or more UEs, a first CSI report with codeword indices including a horizontal basis vector index and a vertical basis vector index associated with the azimuth plane and a corresponding elevation plane. The method may include generating, a first precoding matrix based on the first CSI report. The method may include subsequently transmitting, in the second transmission period, a reduced subset of ports for tracking variations in the azimuth plane. The method may include receiving, from the one or more UEs, a second CSI feedback report comprising at least an updated horizontal basis vector index indicating the variations in the azimuth plane. The method may include generating, a second precoding matrix based on the second CSI report.

[0027] In an embodiment, for determining the deployment scenario associated with the one or more UEs, the method may include determining, the one or more distribution characteristics associated with the one or more UEs. The method may include determining, that the one or more UEs are in an elevation plane based on the determined one or more distribution characteristics. The method may include mapping, the one or more resource(s) to sound the set of ports of the antenna array, where the mapping may include assigning the oneor more resource(s) to the set of ports arranged in vertical directions across the antenna array to provide beamforming resolution in the elevation plane.

[0028] In an embodiment, based on the determination that the one or more UEs are in the elevation plane, the method may include transmitting, in the first transmission period, the one or more resource(s) mapped to the full set of ports to the one or more UEs for identifying, one or more first spatial domain (SD) basis vectors corresponding to the one or more first channel vectors. The method may include receiving, from the one or more UEs, a first CSI report including a vertical basis vector index and a horizontal basis vector index associated with the elevation plane and a corresponding azimuth plane. The method may include generating, a first precoding matrix based on the first CSI report. The method may include subsequently transmitting, in the second transmission period, a reduced subset of ports to track variations in the elevation plane. The method may include receiving, from the one or more UEs, a second CSI feedback report comprising at least an updated vertical basis vector index indicating the variations in the elevation plane. The method may include generating, a second precoding matrix based on the second CSI report.

[0029] In an embodiment, for determining the deployment scenario associated with one or more UEs, the method may include using, by the processor, a conventional approach or an AI based approach for determining UE distribution estimation or spatial flatness estimation either instantaneously or in a semi-static or in a static manner, where the processor may be configured to perform signalling and receive acknowledgement to identify the conventional approach or the AI based approach. The method may include configuring and transmitting, by the processor, one or more signals to the one or more UEs indicating RRC signalling, MAC CE signalling or DCI signalling, and correspondingly receiving an acknowledgement from the one or more UEs.

[0030] In an embodiment, wherein for determining granularity associated with the first transmission period and the second transmission period, the method may include using, by the processor, a first conventional approach or a first AI based approach for determining one or more channel variations due to user mobility, environmental changes, or network congestion, where the processor may be configured to perform signalling and receive acknowledgement to identify the first conventional approach or the first AI based approach. The method may include configuring and transmitting, by the processor, one or more signals to the one or more UEs indicating RRC signalling, MAC CE signalling or DCI signalling, and correspondingly receiving an acknowledgement from the one or more UEs.

[0031] In an embodiment, based on a non-existence of spatial flatness associated with the deployment scenario, the method may include configuring, by the processor, the subset of ports to be mapped and sounded continuously or sparsely across horizontal and vertical dimensions in the second transmission period. The method may include configuring and transmitting, by the processor, one or more signals to the one or more UEs indicating RRC signalling, MAC CE signalling or DCI signalling, and correspondingly receiving an acknowledgement from the one or more UEs. The method may include subsequently receiving, by the processor, from the one or more UEs, first information associated with the full set of ports derived from the second information associated with the subset of ports, where the first information is generated using a second conventional approach or a second AI based approach, where the processor may be configured to perform signalling and receive acknowledgement to identify the second conventional approach or the second AI based approach.

[0032] In an embodiment, for implementing a learning method, the method may include using, by the processor, a signalling and an acknowledgement to indicate if a conventional or AI / ML technique is implemented.

[0033] In an aspect, the present disclosure relates to a user equipment (UE) for sending requests may include one or more processors communicatively coupled to a processor associated with a system, where the one or more processors are coupled with a memory, and where said memory stores instructions which, when executed by the one or more processors, cause the one or more processors to transmit one or more CSI reports, for a first transmission period corresponding to one or more first channel vectors associated with the full set of ports and for a second transmission period corresponding to one or more second channel vectors associated with the subset of ports, where the subset of ports indicate a subset of the full set of ports. The processor is configured to determine a channel sounding configuration and correspondingly configure one or more resource(s) to sound a set of ports for deployment scenario associated with the UE. The processor is configured to transmit, to the UE, a first reference signal in a first transmission period with occasional sounding of a full set of ports from the set of ports and transmit a second reference signal in a second transmission period with frequent sounding of a subset of ports from the set of ports, where the first transmission period and the second transmission period are based on network conditions. The processor is configured to receive one or more channel state information (CSI) reports from the UE for the first transmission period corresponding to the one or more first channel vectors associated with the full set of ports and for the second transmissionperiod corresponding to one or more second channel vectors associated with the subset of ports. The processor is configured to determine, from the received CSI reports, a precoding matrix for downlink data transmission.

[0034] In an aspect, the present disclosure relates to a non-transitory computer readable medium including a processor with executable instructions, causing the processor to determine a channel sounding configuration and correspondingly configure one or more resource(s) to sound a set of ports for deployment scenario associated with one or more UEs. The processor transmits, to the one or more UEs, a first reference signal in a first transmission period with occasional sounding of a full set of ports from the set of ports and transmit a second reference signal in a second transmission period with frequent sounding of a subset of ports from the set of ports, where the first transmission period and the second transmission period are based on network conditions. The processor receives one or more channel state information (CSI) reports from the one or more UEs for a first transmission period corresponding to one or more first channel vectors associated with the full set of ports and for a second transmission period corresponding to one or more second channel vectors associated with the subset of ports, where the subset of ports indicates a subset of the full set of ports. The processor determines, from the received one or more CSI reports, a precoding matrix for downlink data transmission. BRIEF DESCRIPTION OF DRAWINGS

[0035] The accompanying drawings, which are incorporated herein, and constitute a part of this disclosure, illustrate exemplary embodiments of the disclosed methods and systems which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure. Some drawings may indicate the components using block diagrams and may not represent the internal circuitry of each component. It will be appreciated by those skilled in the art that disclosure of such drawings includes the disclosure of electrical components, electronic components, or circuitry commonly used to implement such components.

[0036] FIG. 1 illustrates an example network architecture (100) implementing a system (108) for efficiently transmitting channel state information (CSI)-reference signal (RS) resources to user equipment (UE), in accordance with an embodiment of the present disclosure.

[0037] FIG. 2A illustrates an example block diagram (200A) of the system (108), in accordance with an embodiment of the present disclosure.

[0038] FIG. 2B illustrates an example block diagram (200B) of the UE (104), in accordance with an embodiment of the present disclosure.

[0039] FIGs. 3A and 3B illustrate example mappings (300A, 300B) of CSI-RS resources to antennae ports, according to embodiments of the present disclosure.

[0040] FIGs. 4A-4C illustrate signal flow representations (400A, 400B, 400C) of CSI determination and transmission for downlink communication, in accordance with an embodiment of the present disclosure.

[0041] FIGs. 4D-4F illustrate signal flow representations (400D, 400E, 400F) of CSI determination and transmission for downlink communication, where the resource is mapped to the N antenna ports, in accordance with an embodiment of the present disclosure.

[0042] FIGs. 5A to 5E illustrate representations (500A, 500B, 500C, 500D, 500E) of reference beams determined based on feedback reports, including the reduced CSI feedback report, in accordance with an embodiment of the present disclosure.

[0043] FIG. 6A illustrates an example representation (600A) of finer and coarser periodicity for the transmission occasion, in accordance with an embodiment of the present disclosure.

[0044] FIG. 6B illustrates an example representation (600B) of finer and coarser periodicity for the transmission occasion, where the resource is mapped to the N antenna ports and N' antenna ports, in accordance with an embodiment of the present disclosure.

[0045] FIG. 7 illustrates an example computer system (700) in which or with which embodiments of the present disclosure may be implemented, in accordance with embodiments of the present disclosure.

[0046] FIG. 8 illustrates an example flow diagram (800) of a method implemented by the system (108), in accordance with embodiments of the present disclosure.

[0047] FIG. 9 illustrates an example high-level flow diagram (900) of a method implemented by the system (108), in accordance with embodiments of the present disclosure.

[0048] FIGs.10A-10B illustrate example representations (1000A, 1000B) of finer and coarser periodicity for the transmission occasion based on a non-existence of spatial flatnessassociated with the deployment scenario, in accordance with embodiments of the present disclosure.

[0049] The foregoing shall be more apparent from the following more detailed description of the disclosure. DEATILED DESCRIPTION

[0050] In the following description, for the purposes of explanation, various specific details are set forth in order to provide a thorough understanding of embodiments of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter can each be used independently of one another or with any combination of other features. An individual feature may not address all of the problems discussed above or might address only some of the problems discussed above. Some of the problems discussed above might not be fully addressed by any of the features described herein.The ensuing description provides exemplary embodiments only and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the disclosure as set forth.

[0051] Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. In other instances, well-known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail to avoid obscuring the embodiments.

[0052] Also, it is noted that individual embodiments may be described as a process that is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed but could have additional steps not included in a figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a processcorresponds to a function, its termination can correspond to a return of the function to the calling function or the main function.

[0053] The word “exemplary” and / or “demonstrative” is used herein to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” and / or “demonstrative” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used in either the detailed description or the claims, such terms are intended to be inclusive in a manner similar to the term “comprising” as an open transition word without precluding any additional or other elements.

[0054] Reference throughout this specification to “one embodiment” or “an embodiment” or “an instance” or “one instance” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0055] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used herein, the singular forms “a”, “an”, and “the” are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms “comprises” and / or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. As used herein, the term “and / or” includes any and all combinations of one or more of the associated listed items.

[0056] The present disclosure introduces a flexible channel state information - reference signal (CSI-RS) transmission scheme that involves transmitting full port CSI-RS (covering one or all resources associated with full ports) occasionally, while transmitting partial port CSI-RS (covering one or a subset of resources associated with partial ports) more frequently. This scheme is useful for overhead reduction in static deployment aware channelsounding for up to 128 port narrow beam systems in 5GA and for larger than 128 port narrow beam systems in 6G, which demand increased channel state information (CSI) occasions due to their increased channel variability. This simple incremental enhancement benefits infrastructure and user equipment (UE) vendors, especially making the roll out of 128 port implementations easier and proliferating its deployments in fifth generation advanced (5GA) mobile networks. As frequent updates of two-dimensional (2D) spatial variations are not needed everywhere in commercial deployments, the present disclosure leverages spatial flatness in one dimension to seamlessly bring in spatial domain overhead reduction. Further, the present disclosure captures and reports 2D spatial variations at a lower frequency, and spatial variations along a single dimension, particularly where spatial variability is high, at a higher frequency by leveraging the deployment scenario.

[0057] The present disclosure proposes to configure K CSI-RS resources with different granularity / density in each CSI-RS resource set by exploiting the channel characteristics. The present disclosure efficiently reduces the downlink CSI-RS resource overhead thereby increasing downlink throughput / spectral efficiency. The reduction in downlink (DL) CSI-RS resource overhead may be achieved by relaxing the need for transmitting full CSI-RS resources, which helps improve the data throughput. The proposed system is channel aware, and retains the precision of the reference beam identified for codebook-based data transmission. Also, the present disclosure proposes a few modifications to CSI-RS configurations, allowing to efficiently realize the scheme of sending full or a subset of ports (resources) interchangeably based on network requirements.

[0058] Various embodiments of the present disclosure will be explained in detail with reference to FIGs.1-10.

[0059] FIG. 1 illustrates an example architecture (100) that implements a system (108), in accordance with an embodiment of the present disclosure. As shown, the architecture (100) may include one or more users, such as users (102-1, 102-2) (collectively referred to as users (102)), operating one or more user equipment (UEs), such as UE (104-1, 104-2) (collectively referred to as UE (104)). The users (102) may avail one or more services from a telecommunication network (not shown) through their UEs (104) by connecting to a base station (106). The base station (106) may include the system (108), and one or more physical antennae / antennae units (110) that may be used to determine channel state information (CSI) using corresponding reference signals (RS), and transmit signals / data through downlink channels, among performing other functions. The base station (106) mayalso be connected to a core network (not shown), which may be configured to provide services to the UEs (104), such as telecommunication services, among others.

[0060] In some embodiments, the antennae (110) may be arranged in any array, based on dimensions of the base station (106). In some embodiments, the antennae (110) may be arranged either linearly, or in a planar arrangement. In some embodiments, the system (108) may be configured to cause the base station (106) to transmit CSI-RS resources to determine channel state quality (also referred to as CSI and / or channel estimation interchangeably throughout the disclosure), such as in terms of signal strength, interference levels, and noise. The quality of the channels may be derived from the CSI-RS, which may be subsequently used by the system (108) for beamforming. The CSI may allow the system (108) to improve signal strength, reduce interference, and the like. Determining the CSI may also enable for multiple input multiple output (MIMO) operation. However, as the number of antennae (110) implemented in the base station (106) increases, the number of CSI-RS ports (resources) required to be transmitted for estimation of the channel quality may also correspondingly increase, thereby increasing the downlink overheads and reducing downlink throughput. The system (108) addresses this problem by reducing the number of CSI-RS ports (resources) transmitted in each transmission occasion based on mapping of the CSI-RS resources to antenna ports of the antennae (110), among other factors.

[0061] In some embodiments, the system (108) may be configured to efficiently reduce downlink CSI-RS resource overhead by rationally relaxing the need for transmitting all the CSI-RS resources (which are configured for aggregating ports across resources) in every CSI-RS transmission period by employing deployment-based CSI-RS mapping and by modifying CSI framework signalling, while preserving the precision of the reference beams identified for codebook-based data transmission. In some embodiments, the system (108) may be configured to transmit a subset of resources in a few transmission occasions / periods by leveraging the unique channel characteristics observed from the deployment-based CSI- RS mapping practice (i.e., resource to port / antenna mapping), such as based on the mappings shown in FIGs. 3A and 3B. The details of the system (108), and the UEs (104) adapted to operate with the system (108), are described subsequently in the present disclosure.

[0062] FIG. 2A illustrates an example block diagram (200A) of the proposed system (108), in accordance with an embodiment of the present disclosure.

[0063] In an embodiment, and as shown in FIG. 2, the system (108) may include one or more processors (202). The one or more processors (202) may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, centralprocessing units, logic circuitries, and / or any devices that manipulate data based on operational instructions. Among other capabilities, the one or more processor(s) (202) may be configured to fetch and execute computer-readable instructions stored in a memory (204) of the system (108). The memory (204) may store one or more computer-readable instructions or routines, which may be fetched and executed to create or share the data units over a network service. The memory (204) may include any non-transitory storage device including, for example, volatile memory such as a Random-Access Memory (RAM), or a non-volatile memory such as an Erasable Programmable Read-Only Memory (EPROM), a flash memory, and the like.

[0064] In an embodiment, the system (108) may also include an interface(s) (206). The interface(s) (206) may include a variety of interfaces, for example, interfaces for data input and output devices, referred to as I / O devices, storage devices, and the like. The interface(s) (206) may facilitate communication of the system (108) with various devices coupled thereto. The interface(s) (206) may also provide a communication pathway for one or more components of the system (108). Examples of such components include, but are not limited to, processing engine(s) (208) and a database (210).

[0065] In an embodiment, the processing engine(s) (208) may be implemented as a combination of hardware and software / programming (for example, programmable instructions) to implement one or more functionalities of the processing engine(s) (208). In examples, described herein, such combinations of hardware and software / programming may be implemented in several different ways. For example, the software / programming for the processing engine(s) (208) may be processor-executable instructions stored on a non- transitory machine-readable storage medium and the hardware for the one or more processors (202) may include a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the processing engine(s) (208). In such examples, the system (108) may include the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to the system (108) and the processing resource. In other examples, the processing engine(s) (208) may be implemented by an electronic circuitry.

[0066] In an embodiment, the database (210) may include data that may be either stored or generated as a result of functionalities implemented by any of the components of the processor(s) (202) or the processing engine(s) (208) or the system (108). In someembodiments, the processing engine(s) (208) may include one or more engines or one or more modules, such as a determination engine (212), a communication engine (214), and other units / engines (218). The other units / engines (216) may be used for supporting functions of the system (108). In some embodiments, the determination engine (212) may be configured to determine the number of CSI-RS resources to be transmitted to the UE (104) in each transmission occasion, such as based on the mapping CSI-RS resources to ports of antennae (110) in a vertical direction or a horizontal direction. In some embodiments, the determination engine (212) may be configured to determine the number of CSI-RS resources to be transmitted to the UE (104) in each transmission occasion, such as to exploit the channel characteristics in any one spatial direction / domain. In some embodiments, the communication engine (214) may be configured to sound the antennae (110) based on the number of CSI-RS resources determined to be transmitted to the UEs (104). In some embodiments, the communication engine (214) and other units / engines (218) may be configured to sound only a subset of CSI-RS resources mapped to a part of full antenna ports / physical antenna units, such as a reduced number of units reduce the overall power consumption. Further, the communication engine (214) may be configured to receive CSI feedback from the UE (104), and determine pre-coding weight matrix for downlink data transmission.

[0067] FIG. 2B illustrates an example block diagram (200B) of the UEs (104), in accordance with an embodiment of the present disclosure.

[0068] As shown, the UEs (104) may include one or more processors (222), a memory (224), and an interface (226), which may be implemented similarly to those of the system (108). The UEs (104) may also include processing engines (228), such as a channel estimation engine (232), a transmission engine (234), and other engines (236).

[0069] In some embodiments, the channel estimation engine (232) may be configured to determine the CSI based on the CSI-RS resources transmitted thereto. The channel estimation engine (232) may be configured to generate a CSI feedback report having the precoding matrix indicator (PMI) to the base station (106). The channel estimation engine (232) may also be configured to generate a reduced CSI feedback report having a part of the precoding matrix indicator (PMI) to the base station (106). The channel estimation engine (232) may further be configured to create a full channel knowledge from an estimated partial channel knowledge and generate a CSI feedback report having the precoding matrix indicator (PMI) to the base station (106). In some embodiments, the transmission engine (234) may be configured to transmit the CSI feedback report to the base station (106). The system (108) inthe base station (106) may be configured to receive the CSI feedback report, based on which the system (108) may determine the precoding weights matrix.

[0070] Although FIGs.2A and 2B show example components of the system (108) and the UEs (104), respectively, in other embodiments, the system (108) and the UEs (104) may include fewer components, different components, differently arranged components, or additional functional components than depicted in FIGs. 2A and 2B. Additionally, or alternatively, one or more components of the system (108) and the UEs (104) may perform functions described as being performed by one or more other components thereof.

[0071] In an embodiment, the processor (202) may determine a channel sounding configuration through the determination engine (212) and correspondingly configure one or more resources to sound a set of ports for deployment scenario associated with one or more UEs (104) using the communication engine (214).

[0072] In an embodiment, the processor (202) may estimate the angle of arrival (AoA) and angle of departure (AoD) associated with the UEs (104) for determining the deployment scenario associated with the UEs (104). The processor (202) may determine if the spatial vector (or channel state vector) is varying predominantly in the horizontal (azimuthal) domain or the elevation plane. The processor (202) may use artificial intelligence / machine learning (AI / ML) models for estimation of the AoA and the AoD associated with the UEs (104). This may allow the processor (202) to sound the set of ports based on the predetermined deployment scenario.

[0073] In an embodiment, the AI / ML models may predict the variation in the AoA and the AoD for a predetermined period and classify the type of spatial vector. Further, the processor (202) may optimize reporting (associated with the deployment scenario) based on significant changes in the AoA and the AoD.

[0074] In an embodiment, the processor (202) may implement a positioning and sensing algorithm designed to enable the base station (106) to determine the precise location of a UE (104) in real time. This algorithm may leverage a combination of advanced radio measurements and sensor data fusion to achieve high-accuracy positioning. Specifically, the base station (106) may collect multi-dimensional radio parameters including the angle of arrival (AoA) of uplink signals, the angle of departure (AoD) inferred from downlink transmissions and UE (104) feedback, time of arrival (ToA) or round-trip time (RTT) measurements for distance estimation, as well as received signal strength indicators (RSSI / RSRP) and Doppler shifts that capture relative motion. By integrating measurements from multiple neighbouring base stations or transmission points, the processor (202) forms adataset that supports both triangulation (based on directional angles) and trilateration (based on distance estimates). In addition to purely radio-based techniques, the algorithm can incorporate optional inertial sensor data from the UE (104) such as accelerometer and gyroscope readings, which provide short-term motion information to refine the positioning estimate between radio measurement intervals. The processor (202) may use machine learning models trained on site-specific data. For example, a neural network may be trained to map complex channel state information (CSI) or multi-antenna signal patterns directly to (x, y, z) location coordinates, enabling more robust estimates even in dense urban or non- line-of-sight scenarios.

[0075] In an embodiment, by adaptively weighting different inputs, prioritizing AoA when multipath distortion is minimal, or ToA when timing measurements are clean, the processor (202) may intelligently balance available data to maximize positioning accuracy. This approach may not only enhance precision but also reduces latency in updating the UE’s (104) location, which is crucial for applications such as beamforming, resource scheduling, or location-based services.

[0076] In an embodiment, GPS (Global Positioning System) or more broadly GNSS based positioning may be used for determining the geographic location of the UEs (104) in order to estimate the distribution of the UEs (104) in the network. In this approach, the UE (104) may be equipped with a GNSS receiver that continuously listens to signals broadcast by multiple orbiting satellites. By measuring the precise time delays (or pseudo-ranges) from at least four different satellites, the UE (104) may calculate its three-dimensional position (latitude, longitude, and altitude) using trilateration. Modern GNSS systems also support advanced corrections such as differential GNSS or assisted GPS (A-GPS), which leverage ground-based reference stations or cellular networks to improve accuracy and reduce time-to- first-fix. GNSS-based positioning is particularly effective in open outdoor environments where clear line-of-sight to multiple satellites is available. However, the performance associated with the GNSS-based positioning can degrade in urban canyons, dense foliage, or indoor settings due to multipath effects and signal attenuation. To address such limitations, GNSS positioning may be often combined with other technologies to provide a more reliable and precise location estimate. In the context of aiding the base station (106), GNSS coordinates reported by the UE (104) may serve as a valuable absolute positioning input, complementing radio-based positioning algorithms.

[0077] In an embodiment, the processor (202) may transmit, to the one or more UEs (104), a first reference signal in a first transmission period with occasional sounding of a fullset of ports from the set of ports and transmit a second reference signal in a second transmission period with frequent sounding of a subset of ports from the set of ports, where the first transmission period and the second transmission period may be based on network conditions.

[0078] In an embodiment, the processor (202) may receive one or more channel state information (CSI) reports from the one or more UEs (104) for a first transmission period corresponding to one or more first channel vectors associated with the full set of ports and for a second transmission period corresponding to one or more second channel vectors associated with the subset of ports, where the subset of ports may indicate a subset of the full set of ports.

[0079] In an embodiment, the processor (202) may determine from the received one or more CSI reports, a precoding matrix for downlink data transmission.

[0080] In an embodiment, to determine the deployment scenario associated with the one or more UEs (104), the processor (202) may be configured to determine one or more distribution characteristics associated with the one or more UEs (104). The processor (202) may be configured to determine that the one or more UEs (104) are in an azimuth plane based on the determined one or more distribution characteristics. The processor (202) may be configured to map the one or more resource(s) to sound the set of ports of an antenna array, wherein the mapping may include assigning the one or more resource(s) to the set of ports arranged in horizontal directions across the antenna array to provide beamforming resolution in the azimuth plane.

[0081] In an embodiment, based on the determination that the one or more UEs (104) are in the azimuth plane, the processor (202) may be configured to transmit, in the first transmission period, the one or more resource(s) mapped to the full set of ports to the one or more UEs (104) to identify, one or more first spatial domain (SD) basis vectors corresponding to the one or more first channel vectors. The processor (202) may be configured to receive, from the one or more UEs (104), a first CSI report with codeword indices comprising a horizontal basis vector index and a vertical basis vector index associated with the azimuth plane and a corresponding elevation plane. The processor (202) may be configured to generate a first precoding matrix based on the first CSI report. The processor (202) may be configured to subsequently transmit, in the second transmission period, a reduced subset of ports to track variations in the azimuth plane. The processor (202) may be configured to receive, from the one or more UEs (104), a second CSI feedback report including at least an updated horizontal basis vector index indicating the variations in theazimuth plane. The processor (202) may be configured to generate a second precoding matrix based on the second CSI report. For instance, applying a pre-stored SD bases vector indication pertaining to the spatially flat channel dimension to the newly received updated SD bases vector indication pertaining to the other dimension to create the narrow beam SD basis vector for full ports.

[0082] In an embodiment, to determine the deployment scenario associated with the one or more UEs (104), the processor (202) may be configured to determine one or more distribution characteristics associated with the one or more UEs (104). The processor (202) may be configured to determine that the one or more UEs (104) are in an elevation plane based on the determined one or more distribution characteristics. The processor (202) may be configured to map the one or more resource(s) to sound the set of ports of an antenna array, where the mapping may include assigning the one or more resource(s) to the set of ports arranged in vertical directions across the antenna array to provide beamforming resolution in the elevation plane.

[0083] In an embodiment, based on the determination that the one or more UEs (104) are in the elevation plane, the processor (202) may be configured to transmit, in the first transmission period, the one or more resource(s) mapped to the full set of ports to the one or more UEs (104) to identify, one or more first spatial domain (SD) basis vectors corresponding to the one or more first channel vectors. The processor (202) may be configured to receive, from the one or more UEs (104), a first CSI report with codeword indices including a vertical basis vector index and a horizontal basis vector index associated with the elevation plane and a corresponding azimuth plane. The processor (202) may be configured to generate a first precoding matrix based on the first CSI report. The processor (202) may be configured to subsequently transmit, in the second transmission period, a reduced subset of ports to track variations in the elevation plane. The processor (202) may be configured to receive, from the one or more UEs (104), a second CSI feedback report comprising at least an updated vertical basis vector index indicating the variations in the elevation plane. The processor (202) may be configured to generate a second precoding matrix based on the second CSI report.

[0084] In an embodiment, the deployment scenarios may be learnt, for the purpose of determining the mapping method, using a traditional / conventional approach or AI based approach for UE (104) distribution estimation or spatial flatness estimation. Sample algorithms may include, but not limited to, Random Forest (RF), Neural networks, and LSTMs that leverage spatial and temporal data to learn the channel. In either case, thenetwork may configure and transmit signals to realize the method by RRC signalling, MAC CE signalling or DCI signalling, a UE (104) may receive the network indication and respond to that network indication through an acknowledgement or a set of measurements or both. The traditional approach may use a plurality of non-AI based methods to derive the inference. The AI based method may follow a pipeline, which may include a data collection phase that gathers spatial and signal data from the network / UEs (104) or using spatial indexing to organize data by location for efficient querying. The AI based method may include a pre- processing phase that may extract a plurality of features from the obtained data or normalize signal measurements and map them to a 2D spatial grid or handle a missing data. The AI based method may include a model selection and training phase for UE (104) localization or density estimation of UEs (104) in the 3D plane. The AI based method may include an output generation phase that generates a spatial heatmap of UE (104) density or a list of estimated UE (104) coordinates for UE (104) positions or cluster centroids, not excluding other analogous metrics.

[0085] In an embodiment, to determine the deployment scenario associated with one or more UEs (104), the processor (202) may be configured to use a conventional approach or an AI based approach for determining UE distribution estimation or spatial flatness estimation either instantaneously or in a semi-static or in a static manner. The processor (202) may be configured to perform signalling and receive acknowledgement to identify the conventional approach or the AI based approach. The processor (202) may be configured to configure and transmit one or more signals to the one or more UEs (104) by RRC signalling, MAC CE signalling or DCI signalling, and correspondingly receive an acknowledgement from the one or more UEs (104).

[0086] In one or more embodiments, the choice of granularity for the coarser and finer periods for sounding and reporting, i.e., for full ports and partial ports respectively, may be based on the time varying distributions or the UE (104) mobility derived using a traditional approach or an AI based approach. In either case, the network may configure and transmit the signals to realize the method by RRC signalling, MAC CE signalling or DCI signalling, a UE (104) may receive the network indication and respond to that network indication through an acknowledgement, a set of measurements or both. The approach may use the knowledge of coherence time by using a Doppler estimation by a gNB (106) or a UE (104). Alternatively, the network may collect and analyze CSI to schedule the optimal granularity. To be more specific, the network may use an indication of the channel variations due to user mobility, environmental changes, or network congestion, not excluding the usageof one or more parameters based on the technical idea of the disclosure. The traditional approach may use a plurality of non-AI based methods to derive the inference. The AI assisted method, at the network, for determining the rate of coarser and finer CSI-RS occurrences in the time domain may follow a pipeline which may include a data collection phase that gathers time and signal data from the network / UEs (104). The AI assisted method may include a pre-processing phase that may extract a plurality of features from the obtained data or normalize signal measurements or handle a missing data. The AI assisted method may include a model selection and training phase for analyzing and predicting the channel coherence in time. The AI assisted method may include an output generation phase that generates a CSI-RS rate of occurrences for full port and partial port channel sounding, measurement and feedback. Sample algorithms may include, but not limited to, Random Forest (RF), Neural networks, and LSTMs that leverage temporal data to learn the channel.

[0087] In an embodiment, to determine granularity associated with the first transmission period and the second transmission period, the processor (202) may be configured to use a first conventional approach or a first AI based approach for determining one or more channel variations due to user mobility, environmental changes, or network congestion, where the processor (202) may be configured to perform signalling and receive acknowledgement to identify the first conventional approach or the first AI based approach. The processor (202) may be configured to configure and transmit one or more signals to the one or more UEs (104) by RRC signalling, MAC CE signalling or DCI signalling, and correspondingly receive an acknowledgement from the one or more UEs (104).

[0088] In one or more embodiments, the CSI-RS ports may be mapped and sounded across horizontal and vertical dimensions or mapped and sounded sparsely with missing assignments at random. In such cases, without relying on estimating partial channel and reporting reduced SD bases vector dimensions, the UE (104) may choose to create the full channel knowledge from the estimated partial channel knowledge using a traditional approach or an AI based approach. The traditional approach may include an interpolation technique, without excluding the usage of other techniques based on the technical idea of the disclosure. Alternatively, the UE (104) may perform a machine learning (ML) based imputation for channel estimation, at the UE (104), which further may include a data collection phase for collecting the data from the first transmission occasion of full port sounding. The machine learning based imputation for channel estimation may include a pre- processing phase that may extract a plurality of features from the obtained data or use a parameter from received from the gNB (108). The machine learning based imputation forchannel estimation may include a model selection and training phase for training a model on known CSI data. The machine learning based imputation for channel estimation may include a prediction phase that uses the training to predict or fill in the gaps in CSI of the second transmission. Sample algorithms may include, but not limited to, Neural networks (NNs), Support vector Machines (SVMs), k-Nearest neighbors (KNN), Random forests (RF), Gaussian process regressions (GPRs).

[0089] In an embodiment, based on a non-existence of spatial flatness associated with the deployment scenario, the processor (202) may be configured to configure the subset of ports to be mapped and sounded continuously or sparsely across horizontal and vertical dimensions in the second transmission period. The processor (202) may be configured to configure and transmit one or more signals to the one or more UEs (104) by RRC signalling, MAC CE signalling or DCI signalling, and correspondingly receive an acknowledgement from the one or more UEs (104). The processor (202) may be configured to subsequently receive from the one or more UEs (104), first information associated with the full set of ports derived from the second information associated with the subset of ports, where the first information may be generated using a second conventional approach or a second AI based approach, and wherein the processor (202) may be configured to perform signalling and receive acknowledgement to identify the second conventional approach or the second AI based approach.

[0090] In an embodiment, to implement a learning method associated with the processor (202) may be configured to use a signalling and an acknowledgement to indicate if a conventional or AI / ML technique is implemented.

[0091] The functioning of the system (108) and the UEs (104) are described in further detail in reference to FIGs.3A to 5E.

[0092] FIGs. 3A and 3B illustrate example mappings (300A, 300B) of CSI-RS resources to antennae ports, according to embodiments of the present disclosure.

[0093] As stated, the antenna (110) may be arranged in an array. In a typical antenna array deployment at the base station (106), the values of N1 and N2 (corresponding to dimensions of a planar array of the antennae (110)) may be selected and balanced out so that the base station (106) is configured to support a variety of flexible antenna layouts and configurations that offer spatial (beam) resolution in either horizontal dimension, vertical dimension, or both. In some embodiments, in the base station (106), K CSI-RS resources may be mapped to the N antenna ports and their physical antenna (110).

[0094] In some embodiments, a first mapping (300A) may provision CSI-RS resources to have a vertical direction split of antenna units (in the N2 direction), as shown in FIG. 3A. Such embodiments / configurations may be used in deployments that require higher beamforming resolution in the horizontal domain / azimuth plane. For example, in deployment scenarios with users distributed largely along the same azimuth plane including, but not limited to, an urban macro, urban micro open-square, or rural deployment of the base station (106), where the service is provided to on-the-ground users or users belonging to the same floor / vertical height. In the example mapping (300A), a dual polarized larger antenna panel may have dimensions N1=16, N2=4. Other identical deployments are not precluded in the present disclosure.

[0095] In other embodiments, a second mapping may provision CSI-RS resources to have a horizontal split of antenna units (in the N1direction), which may be used in deployments that require higher beamforming resolution in vertical domain / elevation plane. For example, in deployment scenarios with several high-rise buildings with users distributed largely along the same elevation plane similar to urban micro street canyon, without precluding other identical deployments. In the example mapping of FIG. 3B, a dual polarized larger antenna panel (112) may have dimensions N1=16, N2=4.

[0096] FIGs. 4A-4C illustrate signal flow representations (400A, 400B, 400C) of CSI determination and transmission for downlink communication when resources are aggregated to sound larger ports and FIGs. 4D-4F illustrate signal flow representations (400D, 400E, 400F) of CSI determination and transmission for downlink communication when single resources are used to sound larger ports, in accordance with an embodiment of the present disclosure.

[0097] In some embodiments, the system (108) and the UEs (104) may be configured to enhance the CSI framework for large antenna deployments that configure multiple CSI-RS resources, which are aggregated to sound the channel corresponding to the overall antenna panel. The system (108) and the UEs (104) may be configured to implement the flow (400) to reduce the CSI-RS overheads, to allow for scaling up of the antenna deployments. As shown, the CSI-RS resources may be transmitted aperiodically, periodically, or semi-persistently.

[0098] For a first CSI transmission occasion, all the K M-port CSI-RS resources mapped to the N antenna ports may be configured and sent from base station (106) to the UE (104). For example, for a 64 port base station (106), 2 (K = 2) 32 port CSI-RS resources may be configured in a single CSI-RS resource set to sound 64 CSI-RS ports (or antenna units) or a 128 port base station (106) where 4 (K = 4) 32 port CSI-RS resources may be configured ina single resource set to sound 128 CSI-RS ports (antenna elements). It may be appreciated by those skilled in the art that these examples are indicative and may be extendible to scenarios in which N ports are sounded using reference signals that are configured as K resources of M port in 1 resource set or 1 M port resource each in K resource sets (such that K∗M = N), if they are intended for aggregating to derive a single N port channel sounding. The aggregated N port resources indicate the resources across which a single CSI reporting is configured.

[0099] In an embodiment, on receiving the aggregated channel estimates from all CSI- RS resources from the base station (106) / system (108), the UE (104) may be configured to process the CSI-RS resources to capture long-term spatial domain (SD) channel characteristics in the azimuth and elevation planes by appropriately choosing the value of ^^ (^^1,1) and ^^ (^^1,2) respectively, for eventually identifying the strongest 2D SD basis vector for the reference first beam. The CSI feedback report may include the PMI that includes ^^1= [i1,1^^1,2^^1,3] reported by the UE (104) to the base station (106) as configured. An example illustration (500A) of reference beam indication in the first CSI occasion is shown in FIG. 5A, with indicators ^^1,1, ^^1,2for a dual polarized larger antenna panel with N1=8, N2=4.

[0100] In some embodiments, for each subsequent transmission occasion (until notified via signalling or for a preconfigured occasions), the system (108) in the base station (106) may be configured to transmit one or a subset of CSI-RS resources, indicated by L∈{1,..,K}, such that L∗M = N′. Here, L, or alternately N′, may be enumerated through a low layer trigger transmitted before each transmission occasion. The indication that a resource set includes all or a subset of the CSI-RS resources may be provided to the UE (104) via higher layer (Radio Resource Control) signalling. Hence, based on the mapping of the antennae (110) (as shown in FIGs. 3A and 3B), either CSI-RS resources split in the vertical direction or in the horizontal direction may be transmitted in the downlink channel, i.e., one CSI-RS resource (such as CSIRS #0) or a subset of CSI-RS resources (such as CSIRS #0, CSIRS #1).

[0101] In some embodiments, on receiving the channel estimates from one or subset of resources, the UE (104) may be configured to process the CSI-RS resources differently, based on the mapping. In some embodiments, the UEs (104) may be distributed predominantly in the azimuth plane, such as in the deployments and service beams where there may be fewer high-rise buildings / scatterers in the elevation plane and more scatterers in the azimuth plane. In such embodiments, the vertical beam identified in the first CSI occasion, determined by the vertical SD basis vector indicator ^^, and reported through the feedback index ^^1,2,may be mostly static. The time evolving changes in the channel scatterersmay create a variation in the beam in horizontal / azimuth domain, and its SD basis vector may be identified by ^^ and reported through index ^^1,1. Hence, the variation in ^^ may be determined by estimating one (CSIRS #0) or a subset of CSI-RS resources (say, CSIRS #0, CSIRS #1) and reported as ^^1,1alone, such as by setting reportQuantity as ‘cri-RI-i11’. An example representation (500B) of a reference beam indication in the next CSI occasion using reduced resources withindicators ^^1,1, ^^1,2' is shown in FIG. 5B, considering dual polarized larger antenna panel (N1=8, N2=2).

[0102] In other embodiments, the UE (104) may be distributed predominantly in the elevation plane, such as in deployments and service beams where there may be more high- rise buildings / scatterers in the elevation plane and less scatterers in the azimuth plane. In such embodiments, the horizontal beam identified in the first CSI occasion, determined by the horizontal SD basis vector indicator ^^ and reported through the feedback index ^^1,1, may be mostly static. The time evolving changes in the channel scatterers may create a variation in the beam in vertical / elevation domain, and its SD basis vector may be identified by ^^ and reported through index ^^1,2. Hence, the variation in ^^ may be determined by estimating one (CSIRS #0) or a subset of CSI-RS resources (say, CSIRS #0, CSIRS #1) and reported as ^^1,2alone, such as by setting reportQuantity as ‘cri-RI-i12’. An example representation (500C) of a reference beam indication in the next CSI occasion using reduced resources is shown in FIG. 5C, with updated indicators ^^1,1', ^^1,2, considering dual polarized larger antenna panel (N1=4, N2=4).

[0103] In some embodiments, on receiving the proposed CSI report from the UE (104), the base station (106) / system (108) may be configured to perform at least one of the two procedures based on an attribute, such as ‘reportQuantity’. In some embodiments, the system (108) may be configured to combine the received 10 ^^1,1with a pre-stored ^^1,2to create the narrow beam SD basis vector for full ports (corresponding to all CSI-RS antenna ports), if the reportQuantity is set as ‘cri-RI-i11’, as shown in representation (500D) of FIG.5D. In the representation (500D), the updated narrow beam may be generated as ^^1,1indicator (shown using dotted arrow mark) and pre-stored ^^1,2, considering dual polarized larger antenna panel (N1=8, N2=4). In some embodiments, the system (108) may be configured to combine the received ^^1,2with a pre-stored ^^1,1to create the narrow beam SD basis vector for full ports (corresponding to all CSI-RS antenna ports), if the reportQuantity is set as ‘cri-RI-i12’, as shown in representation (500E) of FIG. 5E). The updated narrow beam may be generated as^^1,2indicator (shown 20 using dotted arrow mark) and pre-stored ^^1,1, considering dual polarized larger antenna panel (N1=8, N2=4).

[0104] In some embodiments, the system (108) may be configured to use the narrow beam SD basis vector given by ^^^,^, of dimension N1N2x 1 to create the precoding weight matrix for downlink data transmission.

[0105] In somethe system (108) may be configured to determine the number of CSI-RS resources to be transmitted in each transmission occasion (indicated as L∈{2,..,K)). Reducing the number of resources by following any of the mapping configurations / types (such as those shown in FIGs. 3A and 3B) implies that a lesser number of antennae (110) are sounded in a specific dimension, thereby creating wider beams in that dimension. Hence, with a single CSI-RS resource, the beam corresponding to the reduced antenna dimension may be relatively large and due to the reduced beam resolution and the presence of multiple strong clusters captured by the wider beam, which may imply that the beam index for the narrow beam may be misjudged. In such cases, where the channel in the wider beam dimension is less flat, the beam resolution in that direction may be increased by increasing the CSI-RS resources in the subset. The size of the subset may be a configured choice of the system (108).

[0106] To realize the reduction in downlink resource overhead, it may be necessary for the base station (106) to be aware of the deployment choice and channel characteristics, and accordingly decide the mapping of antenna ports to physical antenna units / antenna arrays, which helps to exploit the channel characteristics (for example the channel being flat) in any one SD. For example, if the channel is flat in vertical domain, the same may be exploited to reduce the number of CSI-RS resources in N2dimension, and if the channel is flat in a horizontal domain, the same may be exploited to reduce the number of CSI-RS resources in N1dimension.

[0107] In some embodiments, the system (108) may be configured to variably / flexibly determine the number of resources / resource sets across CSI-RS transmission occasions applicable only to CSI-RS resources that are mapped to a part of full antenna ports / physical antenna units based on the suggested deployment choice. In some embodiments, the CSI-RS transmission occasions may be configured / triggered either as periodic, semi-persistent or aperiodic, as shown in FIG. 4. To realize the proposed system (108), existing Releases or Technical Specifications (such as those proposed by Third Generation Partnership Project (3GPP)) for CSI framework configuration settings may be updated. For example, a provisionto allow the system (108) to configure K CSI-RS resources in each CSI-RS resource set (without excluding configuration having K linked CSI-RS resource sets with 1 CSI-RS resource each) with different time domain granularity / period through physical signalling may be included. The physical signalling may be via RRC or Medium Access Control (MAC) Control Element (CE) Downlink Control Information (DCI). In the existing 3GPP specification, all Non-Zero Power (NZP) CSI-RS resources follow certain restrictions on the resource periodicity, such that, all the CSI-RS resources within one set are configured with the same periodicity, while the slot offset may be same or different for different CSI-RS resources. Further, a provision may be included for embodiments where the system (108) may be configured to define a finer and coarser period for the resources indicated in the disclosure as a configured choice of the network, and may be enumerated through higher layer (such as RRC) signalling or low layer MAC CE / DCI trigger, where the finer time resolution provides to update one of the SD basis vector indicators for generating CSI feedback report from reduced resources for frequent sub-optimal beam refinement, and the coarser time resolution provides to update both SD basis vector indicators using all the K CSI-RS resources for occasional optimal beam refinement, as shown representation (600A) of FIG.6A.

[0108] Further, a provision may be included to allow for embodiments where the system (108) may be configured to determine the size of the subset, L∈{1,..,K}, as a configured choice of the network, and may be enumerated through higher layer (RRC) signalling or low layer MAC CE / DCI trigger. Another provision may be included to allow for embodiments where the system (108) may be configured to indicate that a resource set may include a whole or a subset of the CSI-RS resources sent to the UE via higher layer (RRC) signalling as part of the CSI Resource set configuration by introducing a new parameter setting to ‘NZP-CSI-RS-ResourceSet’. Additionally, a provision may be included to allow for embodiments where the UE (104) may be configured to modify the CSI reporting configuration by including the following settings for reportQuantity: ‘cri-RI-i11’, ‘cri-RI-i12’ in addition to existing enumerations of cri-RI-PMI-CQI, cri-RI-i1, cri-RI-i1-CQI, cri-RI-CQI, CRI-Reference Signal Received Power (RSRP), ssb-Index-RSRP, cri-RI-LI-PMI-CQI (default = cri-RI-PMI-CQI).

[0109] The system (108) and method (800) of the present disclosure propose to configure K CSI-RS resources with different granularity / density in each CSI-RS resource set by exploiting the channel characteristics. The proposed solution efficiently reduces thedownlink CSI-RS resource overhead thereby increasing downlink throughput / spectral efficiency.

[0110] The system (108) of the present disclosure may provide for the reduction in downlink CSI- RS resource overhead, achieved by relaxing the need for transmitting full CSI-RS resources, which helps improve the data throughput. The system (108) is channel aware, and hence, retains the precision of the reference beam identified for codebook-based data transmission. The present disclosure further suggests a few modifications to CSI-RS configurations, allowing to efficiently realize the system (108) to send full or a subset of resources interchangeably based on network requirements.

[0111] The present disclosure may be applicable for single panel codebooks, and / or multi panel codebooks. The embodiments of the present disclosure may be used for, among other purposes, reducing the downlink CSI-RS overheads, exploiting channel characteristics for efficient deployment and reference signal transmission, and providing support for larger number of antennae (for large antenna deployments like enhanced MIMO, massive MIMO, and ultra-massive MIMO, without excluding other large-scale multi-antenna deployments) and higher operating frequencies, enabling UEs (104) to support base stations (106) with larger number of antennas with CSI-RS ports (such as those specifying digitally pre-coded ports greater than 32), allowing K CSI-RS resources to be configured with different granularity / density in each CSI-RS resource set, and the like. The present disclosure may also allow for applications where a part of ^^1 index in the UE PMI feedback report is configured and transmitted, and applied to CSI Resource Setting configuration that allows for aggregating ports across configured CSI-RS resources. Further, the present disclosure enables CSI Resource Setting configuration that allows CSI-RS resource aggregation for generating a full port CSI report. The present disclosure is energy efficient, as only a subset of CSI-RS resources mapped to a part of full antenna ports / physical antenna units are active in the CSI occasions defined by the finer periods. Accordingly, a reduced number of RF frontend units than the maximum number of transmitter antenna ports are active during these slots reducing the overall power consumption and increasing energy efficiency.

[0112] In some embodiments, the system (108) may be configured to reduce the codebook subset restriction (CBSR) construction and indication in large antenna systems with > 32 antenna ports. The CBSR may restrict the set of available beamforming vectors (precoding matrices) from a full codebook of precoding matrices. In some embodiments, a group based CBSR for Type I may be used by the system (108), where the group indication ^^1,2may be derived as a parameter depending on ^^1,^^2. In some embodiments, ^^1,2may bedetermined as a function of ^^1,^^2. In other embodiments, ^^1,2may be mapped to predetermined values of ^^1,^^2, as described below. By defining, ^^=^^^^^^^^^^^^^^_^^^^_^^^^^^^^_^^( ^^^^^^^^^^^^ / 32)Sl. No^^1 ^^2Dependence on^^1, ^^2

[0113] , g CI may be used by the system (108) to indicate to the UE (104) whether CBSR reduction is to be enforced or not. Accordingly, without CBSR reduction, bits may be employed, and with CBSR reduction, bits may be employed. The values of ^^1,2may be derived based on the above table.

[0114] Hence, the system (108) may configure variable / flexible number of resources / resource sets across CSI-RS transmissions applicable only to CSI-RS resources. The CSI-RS resources may be mapped to a part of full antenna ports / physical antenna units based on the suggested deployment choice. As illustrated in FIGs. 4A TO 4C, CSI-RS transmissions may be configured or triggered as periodic, semi-persistent or aperiodic. As per the periodic configuration (400B), CSI-RS (Channel State Information Reference Signal) transmissions may occur at regular, fixed intervals according to a predefined schedule. As per the aperiodic configuration (400A), CSI-RS transmissions may occur irregularly and may be triggered by explicit commands from the network when needed. This gives the network flexibility to send CSI-RS only when necessary, such as in response to sudden channel changes or to conserve resources. As per the semi-persistent configuration (400C), CSI-RS transmissions may follow a pattern that is configured by the network to repeat over time but can be started, stopped, or reconfigured with less signalling than fully dynamic transmissions.

[0115] FIGs. 4D-4F illustrate signal flow representations (400D, 400E, 400F) of CSI determination and transmission for downlink communication, where the full-port resource is mapped to the N antenna ports and partial-port resource (mapping of sub-set of ports to a resource) is mapped to the N' antenna ports, in accordance with an embodiment of the present disclosure.

[0116] As illustrated in FIGs. 4D-4F, in one or more embodiments, the system (108), in the first CSI transmission occasion, may be configured to transmit a CSI-RS resource where the resource is mapped to the N antenna ports and transmitted using full antenna ports. The system (108), in the second CSI transmission occasion, may further be configured to transmit a CSI-RS resource wherein the resource is mapped to the N′ antenna ports and transmitted using a sub-set of antenna ports, where N′ < N.

[0117] FIGs. 5A to 5E illustrate representations (500A, 500B, 500C, 500D, 500E) of reference beams determined based on feedback reports, in accordance with an embodiment of the present disclosure.

[0118] In an embodiment, FIG. 5A, illustrates reference beam estimation in the firstCSI occasion defined by ^^^,^, ^^^,ଶ, by considering dual polarized larger antenna panel (N1ൌ 8,N2ൌ 4^ as an example, and its indication with indicators ^^^,^, ^^^,ଶ. The first CSI occasionincludes a first CSI report with the horizontal basis vector index i^,^and the vertical basis vector index i^,ଶassociated with the azimuth planes and elevation planes. Thus, FIG. 5A illustrates how the first CSI occasion leverages the indicators to report the preferred spatial directions (azimuth and elevation) based on the dual-polarized antenna panel configuration enabling efficient reference beam selection and subsequent MIMO transmissions.

[0119] In an embodiment, FIG. 5B illustrates beam estimation in the next CSI occasion using reduced ports (resources) in the vertical domain defined by ^^^,^, ^^^,ଶ', byconsidering dual polarized larger antenna panel (N1ൌ 8, N2ൌ 2^ and its indication with atleast an updated horizontal basis vector index corresponding to the variations in the azimuth plane ^^^,^.

[0120] In an embodiment, FIG. 5C, illustrates beam estimation in the next CSI occasion using reduced ports (resources) in the horizontal domain defined by ^^^,^′, ^^^,ଶ, byconsidering dual polarized larger antenna panel (N1ൌ 4, N2ൌ 4^ and itswith atleast an updated vertical basis vector index corresponding to the variations in the elevation plane ^^^,ଶ.

[0121] In an embodiment, FIG. 5D, illustrates updated reference beam generation in the CSI occasion, having reduced ports (resources) in the vertical domain defined by ^^^,^, ^^^,ଶ', using updated indicators ^^^,^(dotted arrow mark), and buffered (pre-stored) indicator ^^^,ଶ.

[0122] In an embodiment, FIG. 5E, illustrates updated reference beam generation in the CSI occasion, having reduced ports (resources) in the horizontal domain defined by ^^^,^′, ^^^,ଶ, using updated indicators ^^^,ଶ(dotted arrow mark), and buffered (pre-stored) indicator

[0123] In an embodiment, the base station (106) may configure to transmitone resource (a subset of resources, indicated as L∈ {2,..,K). Reducing the number of resources implies that lesser antennas are sounded in a specific dimension, thereby creating wider beams in that dimension. Hence, with a single configured resource, the beam corresponding to the reduced antenna dimension may be relatively large and due to the reduced beam resolution and the presence of multiple strong clusters captured by the wider beam, the beam index for the narrow beam could be misjudged. In such cases, where channel in the wider beam dimension is less flat, the beam resolution in that direction may be increased by increasing the resources in the subset. The size of the subset may be a configured choice of the network.

[0124] FIG. 6A illustrates an example representation (600A) of finer and coarser periodicity for the transmission occasion, in accordance with an embodiment of the present disclosure.

[0125] In an embodiment, the system (108) may configure K CSI-RS resources in each CSI-RS resource set with different time domain granularity / period through physical signalling. The physical signalling may be via RRC or MAC CE / DCI. In legacy Release 15 specifications, all non-zero power (NZP) CSI-RS resources follow certain restrictions on the resource periodicity. In one embodiment, all the CSI-RS resources within one set may be configured with the same periodicity, while the slot offset can be same or different for different CSI-RS resources. Accordingly, it may be desirable to modify existing Third Generation Partnership Project (3GPP) specifications to support the implementations described in the present disclosure.

[0126] In an embodiment, the system (108) may define a finer and coarser period for the resources indicated in the disclosure as a configured choice of the network. This may be enumerated through higher layer (RRC) signalling or low layer MAC CE / DCI trigger. The finer time resolution may update one of the SD basis vector indicators as per the proposedmethod of generating CSI report from reduced resources for frequent sub-optimal beam refinement. The coarser time resolution may update both SD basis vector indicators using all the K CSI-RS resources for occasional optimal beam refinement.

[0127] As illustrated in FIG. 6A, in an embodiment, the flexible sounding of full port CSI-RS and reduced port CSI-RS are represented. All K M-port CSI-RS resources configured for aggregating full N ports may include a coarse period / lower rate of CSI occasions. A subset of L M-port CSI-RS resources from among the aggregated full ports (where L<K) may include a relatively shorter period / higher rate of CSI occasions. Hence, the system (108) provides a flexible CSI-RS transmission scheme that involves transmitting full port CSI-RS (covering all resources) occasionally, while transmitting partial port CSI-RS (covering a subset of resources) more frequently.

[0128] Further, in an embodiment, the system (108) provides a provision to configure the size of the subset, L∈{1,..,K}, as a configured choice of the network, and may be enumerated through higher layer (RRC) signalling or low layer MAC CE / DCI trigger. Further, the system (108) may provide a provision to configure the indication that a resource set may contain resources. The resource set may be configured as a whole or subset can be sent to the UE (104) via higher layer (RRC) signalling as part of the CSI Resource set Configuration by introducing a new parameter setting to ‘NZP-CSI-RS-ResourceSet’. Hence, beam variations in the domain that requires higher beamforming resolution may be well captured with flexible coarse fine sounding.

[0129] Furthermore, in an embodiment, the system (108) provides a provision to modify the CSI reporting configuration by including the following settings reportQuantity: ‘cri-RI-i11’, ‘cri-RI-i12’ in addition to existing enumarations of cri-RI-PMI-channel quality index (CQI), cri-RI-i1, cri-RI-i1-CQI, cri-RI-CQI, CRI-RSRP, ssb-Index-RSRP, cri-RI-LI- PMI-CQI (default = cri-RI-PMI-CQI).

[0130] FIG. 6B illustrates an example representation (600B) of finer and coarser periodicity for the transmission occasion, where the resource is mapped to the N antenna ports and N' antenna ports, in accordance with an embodiment of the present disclosure.

[0131] As illustrated in FIG.6B, in an embodiment, the system (108) may transmit, to the one or more UEs (104), a first reference signal in a first transmission period with occasional sounding (coarse period) of a full set of ports from the set of ports and transmit a second reference signal in a second transmission period with frequent sounding (fine period) of a subset of ports from the set of ports, where the first transmission period and the second transmission period may be based on network conditions.

[0132] FIG. 7 illustrates an example computer system (700) in which or with which embodiments of the present disclosure may be implemented, in accordance with embodiments of the present disclosure.

[0133] As shown in FIG. 7, the computer system (700) may include an external storage device (710), a bus (720), a main memory (730), a read-only memory (740), a mass storage device (750), communication port(s) (760), and a processor (770). A person skilled in the art will appreciate that the computer system (700) may include more than one processor and communication ports. The communication port(s) (760) may be any of an RS-232 port for use with a modem-based dialup connection, a 10 / 100 Ethernet port, a Gigabit or Gigabit port using copper or fibre, a serial port, a parallel port, or other existing or future ports. The communication port(s) (760) may be chosen depending on a network, such a Local Area Network (LAN), Wide Area Network (WAN), or any network to which the computer system (700) connects. The main memory (730) may be a random-access memory (RAM), or any other dynamic storage device commonly known in the art. The read-only memory (740) may be any static storage device(s) including, but not limited to, Programmable Read Only Memory (PROM) chips for storing static information e.g., start-up or basic input / output system (BIOS) instructions for the processor (770). The mass storage device (750) may be any current or future mass storage solution, which may be used to store information and / or instructions.

[0134] The bus (720) communicatively couples the processor (770) with the other memory, storage, and communication blocks. The bus (720) can be, e.g. a Peripheral Component Interconnect (PCI) Extended (PCI-X) bus, a Small Computer System Interface (SCSI), a universal serial bus (USB), or the like, for connecting expansion cards, drives, and other subsystems as well as other buses, such a front side bus (FSB), which connects the processor (770) to the computer system (700).

[0135] Optionally, operator and administrative interfaces, e.g. a display, keyboard, and a cursor control device, may also be coupled to the bus (720) to support direct operator interaction with the computer system (700). Other operator and administrative interfaces may be provided through network connections connected through the communication port(s) (760). In no way should the aforementioned example computer system (700) limit the scope of the present disclosure.

[0136] FIG. 8 illustrates an example flow diagram (800) of a method implemented by the system (108), in accordance with embodiments of the present disclosure.

[0137] As illustrated in FIG. 8, at step 802, the method may include determining, a channel sounding configuration and correspondingly configuring a resource to sound a set of ports based on a deployment scenario associated with one or more UEs (104). At step 804, the method may include transmitting, a first reference signal in a first transmission period with occasional sounding of a full set of ports from the set of ports and transmitting a second reference signal in a second transmission period with frequent sounding of a subset of ports from the set of ports to the one or more UEs (104). At step 806, the method may include receiving, a channel state information (CSI) report from the one or more UEs (104) including a first channel vector based on the transmitted first reference signal and including a second channel vector based on the transmitted second reference signal. At step 808, the method may include determining, a precoding matrix based on the received CSI feedback report for downlink data transmission.

[0138] FIG. 9 illustrates an example high-level flow diagram (900) of a method implemented by the system (108), in accordance with embodiments of the present disclosure. In an embodiment, configuring the method by the system (108) can be explicitly indicated through either MAC CE or DCI signalling or implicitly configured based on the one or more UEs (104) receiving a valid configuration.

[0139] As illustrated in FIG. 9, in an embodiment, at step 902, the method may include selecting, a group of antenna ports associated with a full set of ports mapped to antenna arrays or elements in a first transmission period for CSI sounding and reporting. At step 904, the method may include selecting a group of antenna ports, associated with a subset of ports, mapped to antenna arrays or elements in a second transmission period for CSI sounding and reporting.

[0140] FIGs.10A-10B illustrate example representations (1000A, 1000B) of finer and coarser periodicity for the transmission occasion based on a non-existence of spatial flatness associated with the deployment scenario, in accordance with embodiments of the present disclosure.

[0141] As illustrated in FIGs. 10A-10B, in an embodiment, the CSI-RS ports may be mapped and sounded across horizontal and vertical dimensions or mapped and sounded sparsely with missing assignments at random. In such cases, without relying on estimating partial channel and reporting reduced SD bases vector dimensions, the UE (104) may choose to create a full channel knowledge from the estimated partial channel knowledge using a traditional approach or an AI based approach. The traditional / conventional approach may include an interpolation technique, without excluding the usage of other techniques based onthe technical idea of the disclosure. Alternatively, the UE (104) may perform a machine learning based imputation for channel estimation, at the UE (104), which may further include a data collection phase for collecting the data from the first transmission occasion of full port sounding. This may include a pre-processing phase that may extract a plurality of features from the obtained data or use a parameter from received from gNB. Further, this may include a model selection and training phase for training a model on known CSI data. This may include a prediction phase that uses the training to predict or fill in the gaps in CSI of the second transmission.

[0142] In one or more embodiments, with the use of AI / ML techniques, the methods may be purely based on proprietary implementations and solutions without any dedicated AI / ML-specific signalling enhancement. In one or more embodiments with the use of AI / ML techniques, the methods may also be based on implementations and solutions with signalling- based collaboration between the gNB (108) and the UE (104). This may include modifying air interface, and with new signalling to facilitate efficient AI / ML-based features, such as introducing new measurements and reporting. This may also include a signalling and acknowledgement to indicate whether a traditional or AI / ML technique is employed for realizing the methods.

[0143] While considerable emphasis has been placed herein on the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the present disclosure. These and other changes in the preferred embodiments of the present disclosure will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter to be implemented merely as illustrative of the present disclosure and not as limitation. ADVANTAGES OF THE INVENTION

[0144] The present disclosure provides a system and a method for efficient transmission of channel state information (CSI) reference signal (RS) resources.

[0145] The present disclosure reduces the downlink CSI-RS resource overheads.

[0146] The present disclosure increases downlink (DL) throughput / spectral efficiency without compromising the precision of the reference beam identified for codebook-based data transmission.

[0147] The present disclosure provides efficient mapping of CSI-RS resources to CSI- RS ports.

[0148] The present disclosure supports base stations with larger number of antennae, operating at increased frequencies.

[0149] The present disclosure enables network energy savings by allowing only a subset of antennas to be active during fine periods or occasions when fewer CSI-RS ports are used, thereby reducing overall power consumption on the network side.

[0150] The present disclosure enables reduction in user equipment (UE) complexity by allowing the UE, during fine periods, to measure the channel only over a reduced set of ports. As a result, the UE is not required to estimate the entire channel, thereby potentially lowering computational requirements and simplifying processing.

[0151] The present disclosure enables increased data throughput by utilizing rate matching updates, where the resource elements (REs) freed during fine periods, when only a subset of CSI-RS resources are transmitted, are repurposed to carry additional data, thereby effectively enhancing overall data throughput.

Claims

We Claim:

1. A system (108) for efficient channel state information (CSI) reference signal (RS) transmission, the system (108) comprising: a processor (202) communicatively coupled to a base station (106); and a memory (204) operatively coupled with the processor (202), wherein the memory (204) stores instructions which, when executed by the processor (202), causes the processor (202) to: determine a channel sounding configuration and correspondingly configure one or more resource(s) to sound a set of ports for deployment scenario associated with one or more UEs (104); transmit, to the one or more UEs (104), a first reference signal in a first transmission period with occasional sounding of a full set of ports from the set of ports and transmit a second reference signal in a second transmission period with frequent sounding of a subset of ports from the set of ports, wherein the first transmission period and the second transmission period are based on network conditions; receive one or more channel state information (CSI) reports from the one or more UEs (104) for a first transmission period corresponding to one or more first channel vectors associated with the full set of ports and for a second transmission period corresponding to one or more second channel vectors associated with the subset of ports, wherein the subset of ports indicates a subset of the full set of ports; and determine, from the received one or more CSI reports, a precoding matrix for downlink data transmission.

2. The system (108) as claimed in claim 1, wherein to determine the deployment scenario associated with the one or more UEs (104), the processor (202) is configured to: determine one or more distribution characteristics associated with the one or more UEs (104); determine that the one or more UEs (104) are in an azimuth plane based on the determined one or more distribution characteristics; andmap the one or more resource(s) to sound the set of ports of an antenna array, wherein the mapping comprises assigning the one or more resource(s) to the set of ports arranged in horizontal directions across the antenna array to provide beamforming resolution in the azimuth plane.

3. The system (108) as claimed in claim 2, based on the determination that one or more UEs (104) are in the azimuth plane, the processor (202) is configured to: transmit, in the first transmission period, the one or more resource(s) mapped to the full set of ports to the one or more UEs (104) to identify, one or more first spatial domain (SD) basis vectors corresponding to the one or more first channel vectors; receive, from the one or more UEs (104), a first CSI report with codeword indices comprising a horizontal basis vector index and a vertical basis vector index associated with the azimuth plane and a corresponding elevation plane; generate a first precoding matrix based on the first CSI report; subsequently transmit, in the second transmission period, a reduced subset of ports to track variations in the azimuth plane; and receive, from the one or more UEs (104), a second CSI feedback report comprising at least an updated horizontal basis vector index indicating the variations in the azimuth plane; and generate a second precoding matrix based on the second CSI report.

4. The system (108) as claimed in claim 1, wherein to determine the deployment scenario associated with the one or more UEs (104), the processor (202) is configured to: determine one or more distribution characteristics associated with the one or more UEs (104); determine that the one or more UEs (104) are in an elevation plane based on the determined one or more distribution characteristics; and map the one or more resource(s) to sound the set of ports of an antenna array, wherein the mapping comprises assigning the one or more resource(s) to the set of ports arranged in vertical directions across the antenna array to provide beamforming resolution in the elevation plane.

5. The system (108) as claimed in claim 4, based on the determination that one or more UEs (104) are in the elevation plane, the processor (202) is configured to: transmit, in the first transmission period, the one or more resource(s) mapped to the full set of ports to the one or more UEs (104) to identify, one or more first spatial domain (SD) basis vectors corresponding to the one or more first channel vectors; receive, from the one or more UEs (104), a first CSI report with codeword indices comprising a vertical basis vector index and a horizontal basis vector index associated with the elevation plane and a corresponding azimuth plane; generate a first precoding matrix based on the first CSI report; subsequently transmit, in the second transmission period, a reduced subset of ports to track variations in the elevation plane; and receive, from the one or more UEs (104), a second CSI feedback report comprising at least an updated vertical basis vector index indicating the variations in the elevation plane; and generate a second precoding matrix based on the second CSI report.

6. The system (108) as claimed in claim 1, wherein to determine the deployment scenario associated with one or more UEs (104), the processor (202) is configured to: use a conventional approach or an AI based approach for determining UE distribution estimation or spatial flatness estimation either instantaneously or in a semi-static or in a static manner, wherein the processor (202) is configured to perform signalling and receive acknowledgement to identify the conventional approach or the AI based approach; configure and transmit one or more signals to the one or more UEs (104) indicating RRC signalling, MAC CE signalling or DCI signalling, and correspondingly receive an acknowledgement from the one or more UEs (104).

7. The system (108) as claimed in claim 1, wherein to determine granularity associated with the first transmission period and the second transmission period, the processor (202) is configured to: use a first conventional approach or a first AI based approach for determining one or more channel variations due to user mobility, environmental changes, or network congestion, wherein the processor (202) is configured to perform signallingand receive acknowledgement to identify the first conventional approach or the first AI based approach; and configure and transmit one or more signals to the one or more UEs (104) indicating RRC signalling, MAC CE signalling or DCI signalling, and correspondingly receive an acknowledgement from the one or more UEs (104).

8. The system (108) as claimed in claim 1, based on a non-existence of spatial flatness associated with the deployment scenario, the processor (202) is configured to: configure the subset of ports to be mapped and sounded continuously or sparsely across horizontal and vertical dimensions in the second transmission period; configure and transmit one or more signals to the one or more UEs (104) indicating RRC signalling, MAC CE signalling or DCI signalling, and correspondingly receive an acknowledgement from the one or more UEs (104); and subsequently receive from the one or more UEs (104), first information associated with the full set of ports derived from the second information associated with the subset of ports, wherein the first information is generated using a second conventional approach or a second AI based approach, wherein the processor (202) is configured to perform signalling and receive acknowledgement to identify the second conventional approach or the second AI based approach.

9. The system (108) as claimed in claim 1, wherein to implement a learning method associated with the processor (202) is configured to: use a signalling and an acknowledgement to indicate if a conventional or AI / ML technique is implemented.

10. A method (800) for efficient channel state information (CSI) reference signal (RS) transmission, the method (800) comprising: determining (802), a channel sounding configuration and correspondingly configuring one or more resources to sound a set of ports for deployment scenario associated with one or more UEs (104); transmitting (804), to the one or more UEs (104), a first reference signal in a first transmission period with occasional sounding of a full set of ports from the set of ports and transmitting a second reference signal in a second transmission period with frequent sounding of a subset of ports from the set of ports, wherein the firsttransmission period and the second transmission period are based on network conditions; receiving (806), one or more channel state information (CSI) reports from the one or more UEs (104) for a first transmission period corresponding to one or more first channel vectors associated with the full set of ports and for a second transmission period corresponding to one or more second channel vectors associated with the subset of ports, wherein the subset of ports indicates a subset of the full set of ports; and determining (808), from the received one or more CSI reports, a precoding matrix for downlink data transmission.

11. The method (800) as claimed in claim 10, wherein for determining the deployment scenario associated with the one or more UEs (104), the method comprises: determining, one or more distribution characteristics associated with the one or more UEs (104); determining, that the one or more UEs (104) are in an azimuth plane based on the determined one or more distribution characteristics; and mapping, the one or more resources to sound the set of ports of an antenna array, wherein the mapping comprises assigning the one or more resource(s) to the set of ports arranged in horizontal directions across the antenna array to provide beamforming resolution in the azimuth plane.

12. The method (800) as claimed in claim 11, wherein based on the determination that the one or more UEs (104) are in the azimuth plane, the method comprises: transmitting, in the first transmission period, the one or more resource(s) mapped to the full set of ports to the one or more UEs (104) for identifying, one or more first spatial domain (SD) basis vectors corresponding to the one or more first channel vectors; receiving, from the one or more UEs (104), a first CSI report with codeword indices comprising a horizontal basis vector index and a vertical basis vector index associated with the azimuth plane and a corresponding elevation plane; generating, a first precoding matrix based on the first CSI report; subsequently transmitting, in the second transmission period, a reduced subset of ports for tracking variations in the azimuth plane; andreceiving, from the one or more UEs (104), a second CSI feedback report comprising at least an updated horizontal basis vector index indicating the variations in the azimuth plane; and generating, a second precoding matrix based on the second CSI report.

13. The method (800) as claimed in claim 10, wherein for determining the deployment scenario associated with the one or more UEs (104), the method comprises: determining, one or more distribution characteristics associated with the one or more UEs (104); determining, that the one or more UEs (104) are in an elevation plane based on the determined one or more distribution characteristics; and mapping, the one or more resource(s) to sound the set of ports of an antenna array, wherein the mapping comprises assigning the one or more resource(s) to the set of ports arranged in vertical directions across the antenna array to provide beamforming resolution in the elevation plane.

14. The method as claimed in claim 13, wherein based on the determination that the one or more UEs (104) are in the elevation plane, the method comprises: transmitting, in the first transmission period, the one or more resource(s) mapped to the full set of ports to the one or more UEs (104) for identifying, one or more first spatial domain (SD) basis vectors corresponding to the one or more first channel vectors; receiving, from the one or more UEs (104), a first CSI report comprising a vertical basis vector index and a horizontal basis vector index associated with the elevation plane and a corresponding azimuth plane; generating, a first precoding matrix based on the first CSI report; subsequently transmitting, in the second transmission period, a reduced subset of ports to track variations in the elevation plane; and receiving, from the one or more UEs (104), a second CSI feedback report comprising at least an updated vertical basis vector index indicating the variations in the elevation plane; and generating, a second precoding matrix based on the second CSI report.

15. The method as claimed in claim 10, wherein for determining the deployment scenario associated with one or more UEs (104), the method comprises: using, by the processor (202), a conventional approach or an AI based approach for determining UE distribution estimation or spatial flatness estimation either instantaneously or in a semi-static or in a static manner, wherein the processor (202) is configured to perform signalling and receive acknowledgement to identify the conventional approach or the AI based approach; configuring and transmitting, by the processor (202), one or more signals to the one or more UEs (104) indicating RRC signalling, MAC CE signalling or DCI signalling, and correspondingly receiving an acknowledgement from the one or more UEs (104).

16. The method as claimed in claim 10, wherein for determining granularity associated with the first transmission period and the second transmission period, the method comprises: using, by the processor (202), a first conventional approach or a first AI based approach for determining one or more channel variations due to user mobility, environmental changes, or network congestion, wherein the processor (202) is configured to perform signalling and receive acknowledgement to identify the first conventional approach or the first AI based approach; and configuring and transmitting, by the processor (202), one or more signals to the one or more UEs (104) indicating RRC signalling, MAC CE signalling or DCI signalling, and correspondingly receiving an acknowledgement from the one or more UEs (104).

17. The method as claimed in claim 10, based on a non-existence of spatial flatness associated with the deployment scenario, the method comprises: configuring, by the processor (202), the subset of ports to be mapped and sounded continuously or sparsely across horizontal and vertical dimensions in the second transmission period; configuring and transmitting, by the processor (202), one or more signals to the one or more UEs (104) indicating RRC signalling, MAC CE signalling or DCI signalling, and correspondingly receiving an acknowledgement from the one or more UEs (104); andsubsequently receiving, by the processor (202), from the one or more UEs (104), first information associated with the full set of ports derived from the second information associated with the subset of ports, wherein the first information is generated using a second conventional approach or a second AI based approach, wherein the processor (202) is configured to perform signalling and receive acknowledgement to identify the second conventional approach or the second AI based approach.

18. The method as claimed in claim 10, wherein for implementing a learning method, the method comprises using, by the processor (202), a signalling and an acknowledgement to indicate if a conventional or AI / ML technique is implemented.

19. A user equipment (UE) (104) for sending requests, the UE (104) comprising: one or more processors (222) communicatively coupled to a processor (202) associated with a system (108), wherein the one or more processors (222) are coupled with a memory (224), and wherein said memory (224) stores instructions which, when executed by the one or more processors (222), cause the one or more processors (222) to: transmit one or more CSI reports, for a first transmission period corresponding to one or more first channel vectors associated with the full set of ports and for a second transmission period corresponding to one or more second channel vectors associated with the subset of ports, wherein the subset of ports indicates a subset of the full set of ports, wherein the processor (202) is configured to: determine a channel sounding configuration and correspondingly configure one or more resource(s) to sound a set of ports for deployment scenario associated with the UE (104); transmit, to the UE (104), a first reference signal in a first transmission period with occasional sounding of a full set of ports from the set of ports and transmit a second reference signal in a second transmission period with frequent sounding of a subset of ports from the set of ports, wherein the first transmission period and the second transmission period are based on network conditions; receive one or more channel state information (CSI) reports from the UE (104) for the first transmission period corresponding to the one or more first channel vectorsassociated with the full set of ports and for the second transmission period corresponding to one or more second channel vectors associated with the subset of ports; and determine, from the received CSI reports, a precoding matrix for downlink data transmission.

20. A non-transitory computer readable medium comprising a processor with executable instructions, causing the processor to: determine a channel sounding configuration and correspondingly configure one or more resource(s) to sound a set of ports for deployment scenario associated with one or more UEs (104); transmit, to the one or more UEs (104), a first reference signal in a first transmission period with occasional sounding of a full set of ports from the set of ports and transmit a second reference signal in a second transmission period with frequent sounding of a subset of ports from the set of ports, wherein the first transmission period and the second transmission period are based on network conditions; receive one or more channel state information (CSI) reports from the one or more UEs (104) for a first transmission period corresponding to one or more first channel vectors associated with the full set of ports and for a second transmission period corresponding to one or more second channel vectors associated with the subset of ports, wherein the subset of ports indicates a subset of the full set of ports; and determine, from the received one or more CSI reports, a precoding matrix for downlink data transmission.

Images