Beam measurement and reporting accuracy enhancements

Abstract

Systems, apparatus, equipment, and methods, including computer programs encoded on a storage medium, define beam measurements and reporting, enabling prediction of an optimal beam using an ML model. The UE (102) receives (308), from the network entity (104), a configuration for a measurement report using a beam quality quantization process. The measurement report corresponds to at least one of a CSI report, an L1-RSRP report, or an L1-SINR report, each of which is based on a beam measurement using one or more CSI-RSs as a CMR. The UE (102) receives (312) one or more CSI-RSs for beam measurement from the network entity (104), and sends (316) a measurement report to the network entity (104). Measurement reporting is based on beam measurements and beam quality quantization processes.

Description

Technical Field

[0001] The present disclosure relates generally to wireless communications, and more particularly to enhancing beam measurement and reporting accuracy. Background Art

[0002] The 3rd Generation Partnership Project (3GPP) specifies a radio interface known as fifth generation (5G) New Radio (NR) (5G NR). The architecture of a 5G NR wireless communication system may include a 5G core (5GC) network, a 5G radio access network (5G-RAN), user equipment (UE), etc. Compared to other types of wireless communication systems, the 5G NR architecture may provide increased data rates, reduced latency, and / or increased capacity.

[0003] Wireless communication systems may generally be configured to provide various telecommunication services (e.g., telephony, video, data, messaging, broadcast, etc.) based on multiple access technologies such as orthogonal frequency division multiple access (OFDMA) technologies that support communication with multiple UEs. Improvements in mobile broadband have been useful for the continued development of such wireless communication technologies. For example, a machine learning (ML) model integrated into a mobile broadband application may be used to generate predictions for beams in a beam set without physically measuring each beam in the beam set. For example, a first measurement value determined for one or more measured beams in a beam set may be used to predict a second measurement value for the unmeasured beams without measuring one or more unmeasured beams in the beam set. However, low accuracy inputs to the ML model may cause the ML model to generate low accuracy outputs, which may degrade system performance. Summary of the invention

[0004] A simplified overview of one or more aspects is presented below to provide a basic understanding of such aspects. This overview is not an extensive review of all contemplated aspects. This overview neither identifies the key or important elements of all aspects, nor describes the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a preface to a more detailed description presented later.

[0005] A machine learning (ML) model may be implemented to predict the optimal N beams that may have the best quality among a beam set. The ML model may generate predictions without a user equipment (UE) actually measuring the beam quality of each beam in the beam set. For example, beam measurements such as layer 1 reference signal received power (L1-RSRP) measurements and / or layer 1 signal to interference plus noise ratio (L1-SINR) measurements of a subset of beams in the beam set may be input to the ML model to generate predictions for the optimal N beams. A first ML model predicts the optimal beam for the current UE location (e.g., valid if the UE is not moving), and a second ML model predicts the optimal beam if the UE is moving at a known / constant speed.

[0006] If the network performs an ML model training and inference process, and a subset of beams in a beam set measured and reported to the network by the UE corresponds to beams with reduced beam quality, the input to the ML model may have low accuracy. In other examples, the ML model may be located at the UE so that the UE can report the highest quality beams to the network. Inaccurate input to the ML model may cause the ML model to generate inaccurate output (e.g., inaccurate spatial domain beam predictions), which may degrade the performance of the UE and network entities such as a base station or a radio unit of a base station.

[0007] The above and other deficiencies are mitigated by improving the UE's beam measurement and reporting accuracy based on increasing the coverage of beam measurement reference signals (e.g., channel state information reference signals (CSI-RS)), reducing interference and noise at the UE receiver, and / or implementing a high-resolution quantization process to reduce quantization errors in beam reports. Improving beam measurement and reporting accuracy can support improved spatial domain beam prediction of ML models. Better beam prediction improves beam selection for communications between UEs and network entities, thereby improving overall system performance.

[0008] According to some aspects, a UE receives a configuration for a measurement report using a beam quality quantization process from a network entity. "Beam quality quantization process" refers to a process for determining the report content of each bit associated with the measured beam quality. For example, if the UE reports L1-RSRP via 7 bits and the L1-RSRP measured by the UE is -120 dBm, the UE can determine how to quantize / report 120 dBm of L1-RSRP in 7 bits. The measurement report corresponds to at least one of the following: a channel state information (CSI) report, an L1-RSRP report, or an L1-SINR report, each of which is based on a beam measurement using one or more CSI-RS as a channel measurement resource (CMR). The UE receives one or more CSI-RS for beam measurement from the network entity and sends a measurement report to the network entity. The measurement report is based on beam measurement and a beam quality quantization process.

[0009] According to some aspects, the network entity sends a configuration for measurement reporting as described above to the UE. The network entity further sends one or more CSI-RS used as CMRs to the UE, and receives a measurement report based on a beam quality quantization process and one or more CSI-RS from the UE based on a beam quality quantization process for CSI-RS measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A diagram of a wireless communication system including multiple UEs and network entities communicating through one or more cells is shown.

[0011] Figure 2 is a diagram showing the ML-based spatial domain beam prediction process.

[0012] Figure 3 A signaling diagram for beam reporting based on channel state information (CSI) reporting configuration is shown.

[0013] Figure 4 A signaling diagram for Layer 1 Reference Signal Received Power (L1-RSRP) / Layer 1 Signal to Interference plus Noise Ratio (L1-SINR) reporting is shown.

[0014] Figure 5 A signaling diagram for beam reporting associated with a reported beam satisfying a first threshold criterion is shown.

[0015] FIG. 6A to FIG. 6B A diagram showing a differential aperiodic time slot offset configuration and an absolute aperiodic time slot offset configuration.

[0016] FIG. 7A to FIG. 7B A diagram showing channel state information reference signal (CSI-RS) transmission based on a configured number of repetitions is shown.

[0017] Figure 8 is a flow chart of a method of wireless communication at a UE.

[0018] Fig. 9 is a flow chart of a method of wireless communication at a network entity.

[0019] Fig.10 is a diagram showing a hardware implementation of an example UE apparatus.

[0020] Fig.11 is a diagram illustrating a hardware implementation of one or more example network entities. DETAILED DESCRIPTION

[0021] Figure 1 A diagram of a wireless communication system 100 associated with a plurality of cells 190a-e is shown. The wireless communication system includes UEs 102a-d and base stations 104a-c, some of which (e.g., 104c) include a converged base station architecture and other base stations (e.g., 104a-104b) include a decomposed base station architecture. The converged base station architecture includes a radio unit (RU) 106, a distributed unit (DU) 108, and a centralized unit (CU) 110, which are configured to utilize a radio protocol stack physically or logically integrated within a single radio access network (RAN) node. The decomposed base station architecture utilizes a protocol stack physically or logically distributed between two or more units (e.g., RU 106, DU 108, CU 110). For example, CU 110 is implemented within a RAN node, and one or more DUs 108 may be co-located with CU 110, or alternatively, may be geographically or virtually distributed in one or more other RAN nodes. DU 108 may be implemented to communicate with one or more RU 106. Each of RU 106, DU 108, and CU 110 may be implemented as a virtual unit, such as a virtual radio unit (VRU), a virtual distributed unit (VDU), or a virtual central unit (VCU). Base station 104 and / or units of base station 104 such as RU 106, DU 108, or CU 110 may be referred to as a transmission reception point (TRP).

[0022] The operation and / or network design of the base station 104 can be based on the aggregated nature of base station functions. For example, a decomposed base station architecture is utilized in an integrated access backhaul (IAB) network, an open radio access network (O-RAN) network, or a virtualized radio access network (vRAN), which may also be referred to as a cloud radio access network (C-RAN). Decomposition may include distributing functions between two or more units located at various physical locations, and virtually distributing the functions of at least one unit, which can achieve flexibility in network design. Various units of a decomposed base station architecture or a decomposed RAN architecture may be configured to communicate with at least one other unit in wired or wireless communication. For example, CU 110a communicates with DU 108a-108b via a corresponding midhaul link 162 based on an F1 interface. DU 108a-108b may communicate with RU 106a and RU 106b-106c via corresponding fronthaul links 160, respectively. RU 106a-106c can communicate with corresponding UE 102a-102c and 102s via one or more radio frequency (RF) access links based on Uu interface. In an example, multiple RU 106 and / or base station 104 can provide services for UE 102 at the same time, such as the access link of RU 106a of cell 190a and the UE 102a of cell 190e served by base station 104c of cell 190e at the same time.

[0023] One or more CUs 110, such as CU 110a or CU 110d, may communicate directly with the core network 120 via a backhaul link 164. For example, CU 110d communicates with the core network 120 via a backhaul link 164 based on a next generation (NG) interface. One or more CUs 110 may also communicate indirectly with the core network 120 through one or more decomposed base station units, such as a near real-time RAN intelligent controller (RIC) 128 via an E2 link and a service management and orchestration (SMO) framework 116 that may be associated with a non-real-time RIC 118. The near real-time RIC 128 may communicate with the SMO framework 116 and / or the non-real-time RIC 118 via an A1 link. The SMO framework 116 and / or the non-real-time RIC 118 may also communicate with an open cloud (O-cloud) 130 via an O2 link. One or more CUs 110 may further communicate with each other via a backhaul link 164 based on an Xn interface. For example, the CU 110d of the base station 104c communicates with the CU 110a of the base station 104b via the backhaul link 164 based on the Xn interface. Similarly, the base station 104c of the cell 190e can communicate with the CU 110a of the base station 104b via the backhaul link 164 based on the Xn interface.

[0024] The RU 106, DU 108, and CU 110, as well as the near real-time RIC 128, the non-real-time RIC 118, and / or the SMO framework 116, may include (or may be coupled to) one or more interfaces configured to send or receive information / signals via a wired or wireless transmission medium. The base station 104 or any of the one or more decomposed base station units may be configured to communicate with one or more other base stations 104 or one or more other decomposed base station units via a wired or wireless transmission medium. In an example, a processor, memory, and / or controller associated with executable instructions of the interface may be configured to provide communication between the base station 104 and / or one or more decomposed base station units via a wired or wireless transmission medium. For example, the wired interface may be configured to send or receive information / signals via a wired transmission medium, such as a fronthaul link 160 between the RU 106d and a baseband unit (BBU) 112 for the cell 190d, or more specifically, a fronthaul link 160 between the RU 106d and the DU 108d. The BBU 112 includes the DU 108d and the CU 110d, which may also have a wired interface configured between the DU 108d and the CU 110d to send or receive information / signals between the DU 108d and the CU 110d based on the midhaul link 162. In a further example, a wireless interface, which may include a receiver, transmitter, or transceiver (such as an RF transceiver), may be configured to send or receive information / signals via a wireless transmission medium, such as information transmitted between RU 106a of cell 190a and base station 104c of cell 190e via cross-cell communication beams of RU 106a and base station 104c.

[0025] One or more high-level control functions (such as functions related to radio resource control (RRC), packet data convergence protocol (PDCP), service data adaptation protocol (SDAP), etc.) can be hosted at CU 110. Each control function can be associated with an interface for transmitting signals based on one or more other control functions hosted at CU 110. User plane functions (such as central unit-user plane (CU-UP) functions), control plane functions (such as central unit-control plane (CU-CP) functions), or a combination thereof can be implemented based on CU 110. For example, CU 110 may include one or more CU-UP processes and / or one or more CU-CP processes. When implemented in an O-RAN configuration, the CU-UP function can be based on bidirectional communication with the CU-CP function via an interface (such as an E1 interface (not shown)).

[0026] The CU 110 may communicate with the DU 108 for network control and signal transmission. The DU 108 is a logical unit of the base station 104 that is configured to perform one or more base station functions. For example, the DU 108 may control the operation of one or more RUs 106. One or more of the following may be hosted at the DU 108: a radio link control (RLC) layer, a media access control (MAC) layer, or one or more higher physical (PHY) layers, such as forward error correction (FEC) modules for encoding / decoding, scrambling, modulation / demodulation, etc. The DU 108 may host such functions based on the functional division of the DU 108. The DU 108 may similarly host one or more lower PHY layers, where each lower layer or module may be implemented based on an interface for communicating with other layers and modules hosted at the DU 108, or based on a control function hosted at the CU 110.

[0027] The RU 106 may be configured to implement lower layer functions. For example, the RU 106 is controlled by the DU 108 and may correspond to a logical node hosting RF processing functions or lower layer PHY functions, such as performing fast Fourier transform (FFT), inverse FFT (iFFT), digital beamforming, physical random access channel (PRACH) extraction and filtering, etc. The functions of the RU 106 may be based on functional partitioning, such as lower layer functional partitioning.

[0028] RU 106 can send or receive over-the-air (OTA) communications with one or more UEs 102. For example, RU 106b of cell 190b communicates with UE 102b of cell 190b via a first communication beam set 132 of RU 106b and a second communication beam set 134b of UE 102b, which may correspond to inter-cell communication beams or cross-cell communication beams. For example, UE 102b of cell 190b can communicate with RU 106a of cell 190a via a third communication beam set 134a of UE 102b and a RU beam set 136 of RU 106a. Both real-time and non-real-time features of control plane and user plane communications of RU 106 can be controlled by associated DU 108. Therefore, DU 108 and CU 110 can be used in a cloud-based RAN architecture (such as a vRAN architecture), and SMO framework 116 can be used to support non-virtualized and virtualized RAN network elements. For non-virtualized network elements, the SMO framework 116 may support deployment of dedicated physical resources for RAN coverage, where the dedicated physical resources may be managed through an operation and maintenance interface (such as an O1 interface). For virtualized network elements, the SMO framework 116 may interact with a cloud computing platform (such as O-cloud 130) via an O2 link (e.g., a cloud computing platform interface) to manage the network elements. Virtualized network elements may include, but are not limited to, RU 106, DU 108, CU 110, near real-time RIC 128, and the like.

[0029] The SMO framework 116 may be configured to communicate directly with one or more RUs 106 using an O1 link. The non-real-time RIC 118 of the SMO framework 116 may also be configured to support the functionality of the SMO framework 116. For example, the non-real-time RIC 118 implements logic functions that are capable of controlling non-real-time RAN features and resources, features / applications of the near real-time RIC 128, and / or artificial intelligence / machine learning (AI / ML) processes. The non-real-time RIC 118 may communicate (or couple) with the near real-time RIC 128, such as through an A1 interface. The near real-time RIC 128 may implement logic functions that are capable of controlling near real-time RAN features and resources based on data collection and interaction through an E2 interface (such as an E2 interface between the near real-time RIC 128 and the CU 110a and the DU 108b).

[0030] The non-real-time RIC 118 may receive parameters or other information from an external server to generate an AI / ML model for deployment in the near-real-time RIC 128. For example, the non-real-time RIC 118 receives parameters or other information from the O-cloud 130 via the O2 link to deploy the AI / ML model to the real-time RIC 128 via the A1 link. The near-real-time RIC 128 may utilize parameters and / or other information received from the non-real-time RIC 118 or the SMO framework 116 via the A1 link to perform near-real-time functions. The near-real-time RIC 128 and the non-real-time RIC 118 may be configured to adjust the performance of the RAN. For example, the non-real-time RIC 118 monitors patterns and long-term trends to improve the performance of the RAN. The non-real-time RIC 118 may also deploy the AI / ML model through the SMO framework 116 for implementing corrective actions, such as initiating reconfiguration of the O1 link or instructing the management process of the A1 link.

[0031] Any combination of RU 106, DU 108, and CU 110, or any reference thereto alone, may correspond to base station 104. Thus, base station 104 may include at least one of RU 106, DU 108, or CU 110. Base station 104 provides UE 102 with access to core network 120. That is, base station 104 may relay communications between UE 102 and core network 120. Base station 104 may be associated with a macro cell of a high-power cellular base station and / or a small cell of a low-power cellular base station. For example, cell 190e corresponds to a macro cell, and cells 190a-190d may correspond to a small cell. Small cells include femto cells, pico cells, micro cells, and the like. A cell structure including at least one macro cell and at least one small cell may be referred to as a "heterogeneous network."

[0032] Transmissions from the UE 102 to the base station 104 / RU 106 are referred to as uplink (UL) transmissions, while transmissions from the base station 104 / RU 106 to the UE 102 are referred to as downlink (DL) transmissions. Uplink transmissions may also be referred to as reverse link transmissions, and downlink transmissions may also be referred to as forward link transmissions. For example, the RU 106 d utilizes an antenna of the base station 104 c of the cell 190 d to send downlink / forward link communications to the UE 102 d, or receive uplink / reverse link communications from the UE 102 d, based on a Uu interface associated with an access link between the UE 102 d and the base station 104 c / RU 106 d.

[0033] The communication link between UE 102 and base station 104 / RU 106 can be based on multiple-input multiple-output (MIMO) antenna technology, including spatial multiplexing, beamforming and / or transmit diversity. The communication link can be associated with one or more carriers. UE 102 and base station 104 / RU 106 can utilize Y MHz (e.g., 5 MHz, 10 MHz, 15 MHz, 20 MHz, 100 MHz, 400 MHz, 800 MHz, 1600 MHz, 2000 MHz, etc.) spectrum bandwidth allocated per carrier in carrier aggregation up to a total of Yx MHz, where x component carriers (CCs) are used for communication in each direction of the uplink direction and the downlink direction. The carriers may be adjacent to each other along the spectrum, or may not be adjacent to each other. In an example, uplink carriers and downlink carriers may be allocated in an asymmetric manner, and more or fewer carriers may be allocated for uplink or downlink. The component carrier may include a primary component carrier and one or more secondary component carriers. The primary component carrier may be associated with a primary cell (PCell) and the secondary component carrier may be associated with a secondary cell (SCell).

[0034] Some UEs 102 (such as UE 102a and UE 102s) can perform device-to-device (D2D) communication via a side link. For example, the side link communication / D2D link utilizes the spectrum of a wireless wide area network (WWAN) associated with uplink communication and downlink communication. The side link communication / D2D link can also use one or more side link channels, such as a physical side link broadcast channel (PSBCH), a physical side link discovery channel (PSDCH), a physical side link shared channel (PSSCH) and / or a physical side link control channel (PSCCH) to transmit information between UE 102a and 102s. Such side link / D2D communication can be performed by various wireless communication systems, such as wireless fidelity (Wi-Fi) systems, Bluetooth systems, long term evolution (LTE) systems, new radio (NR) systems, etc.

[0035] The electromagnetic spectrum is typically subdivided into different categories, bands, channels, etc. based on different frequencies / wavelengths associated with the electromagnetic spectrum. The fifth generation (5G) NR is typically associated with two operating frequency bands (FRs) referred to as frequency range 1 (FR1) and frequency range 2 (FR2). FR1 ranges from 410 MHz-7.125 GHz, and FR2 ranges from 24.25 GHz-71.0 GHz, which includes FR2-1 (24.25 GHz-52.6 GHz) and FR2-2 (52.6 GHz-71.0 GHz). Although a portion of FR1 is actually greater than 6 GHz, FR1 is typically referred to as the "sub-6 GHz" band. In contrast, FR2 is typically referred to as the "millimeter wave" (mmW) band. FR2 is different from the "extremely high frequency" (EHF) band, but is an approximate subset of that band, the EHF band ranges from 30 GHz- 300 GHz, and is sometimes also referred to as the "millimeter wave" band. Frequencies between FR1 and FR2 are generally referred to as "mid-band" frequencies. The operating frequency band of mid-band frequencies may be referred to as frequency range 3 (FR3), which ranges from 7.125 GHz to 24.25 GHz. The frequency band within FR3 may include the characteristics of FR1 and / or FR2. Therefore, the characteristics of FR1 and / or FR2 may be extended to mid-band frequencies. Higher operating frequency bands have been identified as extending 5G NR communications to 52.6 GHz above the upper limit associated with FR2. Three of these higher operating frequency bands include FR2-2 with a range of 52.6 GHz-71.0 GHz, FR4 with a range of 71.0 GHz-114.25 GHz, and FR5 with a range of 114.25 GHz-300 GHz. The upper limit of FR5 corresponds to the upper limit of the EHF frequency band. Therefore, unless otherwise expressly stated herein, the term "below 6 GHz" may refer to a frequency less than 6 GHz, a frequency within FR1, or a frequency that may include mid-band frequencies. Further, unless otherwise expressly stated herein, the term "millimeter wave" or mmW refers to frequencies that may include mid-band frequencies, frequencies that may be within FR2-1, FR4, FR2-2 and / or FR5, or frequencies that may be within the EHF band.

[0036] UE 102 and base station 104 / RU 106 may each include multiple antennas. Multiple antennas may correspond to antenna elements, antenna panels, and / or antenna arrays that may facilitate beamforming operations. For example, RU 106b transmits a downlink beamformed signal to UE 102b based on a first beam set 132 in one or more transmit directions of RU 106b. UE 102b may receive a downlink beamformed signal from RU 106b based on a second beam set 134b in one or more receive directions of UE 102b. In a further example, UE 102b may also transmit an uplink beamformed signal to RU 106b based on a second beam set 134b in one or more transmit directions of UE 102b. RU 106b may receive an uplink beamformed signal from UE 102b in one or more receive directions of RU 106b. UE 102b may perform beam training to determine the optimal receive and transmit directions for beamformed signals. The transmit and receive directions of the UE 102 and the base station 104 / RU 106 may be the same, or may be different. In a further example, a beamformed signal may be transmitted between the first base station 104c and the second base station 104b. For example, the RU 106a of the cell 190a may transmit a beamformed signal to the base station 104c of the cell 190e based on the RU beam set 136 in one or more transmit directions of the RU 106a. The base station 104c of the cell 190e may receive a beamformed signal from the RU 106a based on the base station beam set 138 in one or more receive directions of the base station 104c. Similarly, the base station 104c of the cell 190e may transmit a beamformed signal to the RU 106a based on the base station beam set 138 in one or more transmit directions of the base station 104c. The RU 106a may receive a beamformed signal from the base station 104c of the cell 190e based on the RU beam set 136 in one or more receive directions of the RU 106a.

[0037] The base station 104 may include and / or be referred to as a network entity. That is, a "network entity" may refer to a base station 104 or at least one unit of the base station 104, such as a RU 106, a DU 108, and / or a CU 110. The base station 104 may also include and / or be referred to as a next generation evolved node B (ng-eNB), a generation NB (gNB), an evolved NB (eNB), an access point, a base station transceiver, a radio base station, a radio transceiver, a transceiver function, a basic service set (BSS), an extended service set (ESS), a TRP, a network node, a network device, or other related terms. The base station 104 or an entity at the base station 104 may be implemented as an IAB node, a relay node, a side link node, an aggregated (integrated) base station with a RU 106 and a BBU including a DU 108 and a CU 110, or as a decomposed base station 104b including one or more of the RU 106, the DU 108, and / or the CU 110. The set of aggregated or decomposed base stations 104a-104b may be referred to as a next generation radio access network (NG-RAN). In some examples, UE 102b operates in dual connectivity (DC) with base station 104a and base station 104b. In this case, base station 104a may be a primary node and base station 104b may be a secondary node. In other examples, UE 102b operates in DC with DU 108a and DU 108b. In this case, DU 108a may be a primary node and DU 108b may be a secondary node.

[0038] The core network 120 may include an access and mobility management function (AMF) 121, a session management function (SMF) 122, a user plane function (UPF) 123, a unified data management (UDM) 124, a gateway mobile location center (GMLC) 125, and / or a location management function (LMF) 126. The core network 120 may also include one or more location servers (which may include the GMLC 125 and the LMF 126), as well as other functional entities. For example, the one or more location servers include one or more location / positioning servers, and in addition to one or more of a positioning determination entity (PDE), a serving mobile location center (SMLC), a mobile positioning center (MPC), etc., the one or more location / positioning servers may also include the GMLC 125 and the LMF 126.

[0039] AMF 121 is a control node that handles signaling between UE 102 and core network 120. AMF 121 supports registration management, connection management, mobility management, and other functions. SMF 122 supports session management and other functions. UPF 123 supports packet routing, packet forwarding, and other functions. UDM 124 supports the generation of authentication and key agreement (AKA) credentials, user identity handling, access authorization, and subscription management. GMLC 125 provides an interface for clients / applications (e.g., emergency services) to access UE positioning information. LMF 126 receives measurement and assistance information from NG-RAN and UE 102 via AMF 121 to calculate the positioning of UE 102. NG-RAN can use one or more positioning methods to determine the location of UE 102. Positioning UE 102 can involve signal measurements, positioning estimates, and optional speed calculations based on measurements. Signal measurements can be performed by UE 102 and / or serving base station 104 / RU 106.

[0040] The transmitted signal may also be based on one or more of a satellite positioning system (SPS) 114, such as a signal measured for positioning. In an example, the SPS 114 of the cell 190c may communicate with one or more UEs 102 (such as UE 102c) and one or more base stations 104 / RU 106 (such as RU 106c). The SPS 114 may correspond to one or more of a global navigation satellite system (GNSS), a global positioning system (GPS), a non-terrestrial network (NTN), or other satellite positioning / position systems. The SPS 114 may be associated with LTE signals, NR signals (e.g., based on round trip time (RTT) and / or multiple RTT), wireless local area network (WLAN) signals, ground beacon systems (TBS), sensor-based information, NR enhanced cell ID (NR E-CID) technology, downlink departure angle (DL-AoD), downlink arrival time difference (DL-TDOA), uplink arrival time difference (UL-TDOA), uplink arrival angle (UL-AoA), and / or other systems, signals, or sensors.

[0041] UE 102 may be configured as a cellular phone, a smart phone, a Session Initiation Protocol (SIP) phone, a laptop computer, a personal digital assistant (PDA), a satellite radio, a GPS, a multimedia device, a video device, a digital audio player (e.g., a Moving Picture Experts Group (MPEG) Audio Layer 3 (MP3) player), a camera, a game console, a tablet computer, a smart device, a wearable device, a vehicle, a utility meter, a gas pump, a home appliance, a healthcare device, a sensor / actuator, a display, or any other device with similar functionality. Some of UE 102 may be referred to as Internet of Things (IoT) devices, such as parking meters, gas pumps, home appliances, vehicles, healthcare equipment, etc. UE 102 may also be referred to as a station (STA), a mobile station, a subscriber station, a mobile unit, a subscriber unit, a wireless unit, a remote unit, a mobile device, a wireless device, a wireless communication device, a remote device, a mobile subscriber station, an access terminal, a mobile terminal, a wireless terminal, a remote terminal, a handheld device, a mobile client, a client, or other similar terms. The term UE may also apply to a roadside unit (RSU), which may communicate with other RSU UEs, non-RSU UEs, the base station 104, and / or entities at the base station 104, such as the RU 106.

[0042] Still refer to Figure 1 In certain aspects, UE 102 (which is any of UE 102a-e) may include a beam quality quantization component 140 configured to: receive from a network entity a configuration for a measurement report using a beam quality quantization process, the measurement report including at least one of: a channel state information (CSI) report, a layer 1 reference signal received power (L1-RSRP) report, or a layer 1 signal to interference plus noise ratio (L1-SINR) report, each of which is based on beam measurement using one or more channel state information reference signals (CSI-RS) as channel measurement resources (CMR); receive from the network entity one or more CSI-RS for beam measurement; and send to the network entity a measurement report based on the beam measurement and the beam quality quantization process. "Beam quality quantization process" refers to a process for determining report content for each bit associated with measured beam quality. For example, if the UE reports L1-RSRP via 7 bits, and the L1-RSRP measured by the UE is -120 dBm, the UE may determine how to quantize / report L1-RSRP of 120 dBm in 7 bits.

[0043] In certain aspects, the base station 104 (which is any of the base stations 104a-c or a network entity) may include a machine learning (ML) based beam prediction component 150, the beam prediction component configured to: send a configuration for a measurement report using a beam quality quantization process to a UE, the measurement report including at least one of the following: a CSI report, an L1-RSRP report, or an L1-SINR report, each of which is based on one or more CSI-RS used as a CMR; send the one or more CSI-RS used as a CMR to the UE; and receive a measurement report from the UE, the measurement report based on the beam quality quantization process and the one or more CSI-RS. Thus, Figure 1 A wireless communication system is shown, the components of which may be as follows Figure 2 To the operations shown in one or more of Figure 7. Further, although the following description may focus on 5G NR, the concepts described herein may be applicable to other similar areas, such as 5G-Advanced and future versions, LTE, LTE-advanced (LTE-A), and other wireless technologies such as 6G.

[0044] Figure 2 is an illustration 200 of an ML-based spatial domain beam prediction process. The vertical direction in illustration 200 indicates the vertical portion of an angle, and the horizontal direction in illustration 200 indicates the horizontal portion of an angle. The beam may be generated as a function based on f(vertical_angle, horizontal_angle).

[0045] The cell radius / coverage area of ​​a base station may be based on a link budget. "Link budget" refers to the accumulation of total gains and losses in the system, which provides a received signal level at a receiver such as a UE. The receiver may compare the received signal level to the receiver sensitivity to determine whether the channel provides at least a minimum signal strength for signals transmitted between the receiver and a transmitter (e.g., a UE and a base station).

[0046] In order to increase the link budget, the base station and the UE perform analog beamforming operations to select a transmitter-receiver pair that achieves increased signal strength. The base station and the UE both maintain multiple beams 210, 220 that can be used for beam pairs. Beam pairs that reduce coupling loss may result in increased coverage gain for the base station and the UE. "Coupling loss" refers to the reduction in path loss / power density between the first transmit (Tx) antenna of the base station and the second receive (Rx) antenna of the UE, and can be indicated in decibels (dB). The beam selection process for the base station and the UE to activate a beam pair from multiple beams 210, 220 may be associated with one or more beam measurements (e.g., measured beam 202), beam reports, or beam indications / predictions (e.g., predicted beam 204).

[0047] The first type of beam reporting may correspond to non-group-based beam reporting, where the base station may configure the UE to measure and report L1-RSRP) or L1-SINR for a set of downlink reference signals from the base station. The downlink reference signal may correspond to a synchronization signal block (SSB), a CSI-RS, etc. The UE may report L1-RSRP or L1-SINR for up to 4 SSBs or 4 CSI-RS in each beam reporting instance. The second type of beam reporting may correspond to group-based beam reporting, where the base station may configure the UE to measure and report L1-RSRP or L1-SINR for multiple groups of SSBs or CSI-RS. Each beam group may include 2 SSBs or 2 CSI-RS that the UE can receive simultaneously.

[0048] Beam indication techniques based on transmission configuration indicator (TCI) signaling may include joint beam indication or separate beam indication. "Joint beam indication" refers to a single / joint TCI state for updating beams 210, 220 for both downlink channels / signals and uplink channels / signals. For example, a base station may indicate a single / joint TCI state configured based on the DLorJointTCIState parameter in downlink TCI signaling to update beams 210, 220 for both downlink channels / signals and uplink channels / signals. For TCI signaling based on the joint TCI state, the base station may send SSB or CSI-RS to indicate a quasi-co-location (QCL) relationship between downlink channels / signals and a spatial relationship between uplink channels / signals. In a first aspect, the TCI update signaling sent may correspond to a joint beam indication for both downlink channels / signals and uplink channels / signals.

[0049] "Separate beam indication" refers to a first TCI state for updating a first beam of a downlink channel / signal and a second TCI state for updating a second beam of an uplink channel / signal. For example, a base station may indicate a first TCI state configured based on a DLorJointTCIState parameter in a downlink TCI signaling to update a first beam of a downlink channel / signal, and may indicate a second TCI state configured based on an UL-TCIState parameter in a further downlink TCI signaling to update a second beam of an uplink channel / signal. If the base station indicates a second TCI state (e.g., uplink TCI), the downlink reference signal may correspond to an SSB, a CSI-RS, etc. In an example in which the second TCI state indicates an uplink reference signal (e.g., uplink TCI), the uplink reference signal may correspond to a sounding reference signal (SRS), which may indicate a spatial relationship of an uplink channel / signal. In a second aspect, the sent TCI update signaling may correspond to a downlink channel / signal or an uplink channel / signal based on a separate beam indication technique.

[0050] The base station may configure the QCL type and / or source reference signal for QCL signaling. The QCL type of the downlink reference signal may be based on higher layer parameters, such as qcl-Type in the QCL-Info parameter. The first QCL type corresponding to type A may be associated with Doppler shift, Doppler spread, average delay and / or delay spread. The second QCL type corresponding to type B may be associated with Doppler shift and / or Doppler spread. The third QCL type corresponding to type C may be associated with Doppler shift and / or average delay. The fourth QCL type corresponding to type D may be associated with a spatial reception (Rx) parameter. The UE may use the same spatial transmission filter used when receiving a downlink reference signal from the base station or sending an uplink reference signal to indicate a spatial relationship. The sent TCI update signaling updates the TCI state of the channel of the component carrier (CC) that shares the TCI state indicated in the TCI update signaling. The CC may be associated with a cell included in the cell list. The cell list is configured via RRC signaling, which may indicate parameters such as a simultaneousTCI-UpdateList1 parameter, a simultaneousTCI-UpdateList2 parameter, a simultaneousTCI-UpdateList3 parameter, or a simultaneousTCI-UpdateList4 parameter.

[0051] The signaling transmitted between the base station and the UE may be dedicated signaling or non-dedicated signaling. "Dedicated signaling" refers to UE-specific signaling between the base station and the UE. For example, dedicated signaling may correspond to a physical downlink control channel (PDCCH), a PDSCH, a physical uplink control channel (PUCCH), or a physical uplink shared channel (PUSCH) associated with a list of cells that share the indicated TCI state. The PUSCH / PUCCH that is triggered at the UE by downlink control information (DCI), activated based on a media access control-control element (MAC-CE), or configured based on an uplink grant in RRC signaling from a base station is a dedicated signal.

[0052] "Non-dedicated signaling" refers to signaling between a base station and a non-specific UE. For example, non-dedicated signaling may correspond to a physical broadcast channel (PBCH), a PDCCH / PDSCH transmission from a base station for a non-specific UE, a non-periodic CSI-RS, or an SRS for codebook, non-codebook, or antenna switching. The PDCCH in a control resource set (CORESET) associated with a type 0 / 0A / 0B / 1 / 2 common search space and the PDSCH scheduled by such a PDCCH are non-dedicated signals. However, other PDCCH and PDSCH signaling may be dedicated signals. The search space type may be defined based on a standardized protocol.

[0053] The ML model 206 may be implemented at a base station or a UE to predict the best N beams (e.g., predicted beams 204) among the beam sets 220 that are likely to have the best beam quality. The ML model 206 may determine the predicted beams 204 if the UE measures the beam quality of each beam in the beam sets 210. For example, the UE measures the first beam set 202 among the beam sets 210. Beam measurements (such as L1-RSRP measurements and / or L1-SINR measurements) of a first subset of beams in the beam sets 210 may be input into the ML model 206 to generate a prediction of the best N beams (e.g., predicted beams 204) among the beam sets 220 that are most likely to have the highest beam quality among the beam sets 220. An example of generating ML-based spatial domain beam predictions includes inputting L1-RSRP measurement results of a first beam set (e.g., the four measured beams 202) into an ML model 206 to output a second predicted optimal beam set 204 (e.g., four predicted beams 204 different from the four measured beams 202) that may produce the highest beam quality among the beams in the beam set 220. The next beam measurement process can be based on the second predicted beam set 204.

[0054] The UE may measure and report the beam quality (e.g., L1-RSRP) of a first measured beam set 202 (e.g., 4 measured beams 202), which is used as an input to the ML model 206 when ML training and inference occur at the base station. If the beam quality of the 4 measured beams 202 is low, the L1-RSRP input to the ML model 206 may have low accuracy. Inaccurate input to the ML model 206 may cause the ML model 206 to generate inaccurate output (e.g., inaccurate spatial domain beam prediction), which may degrade the performance of the UE and the base station. That is, the measurement error associated with the L1-RSRP input to the ML model 206 may result in quantization error.

[0055] The beam prediction accuracy of the predicted best N beams (e.g., predicted beam 204) can be based on the L1-RSRP of the strongest beam among the best N predicted beams being greater than the L1-RSRP of the ideal beam minus a 1 dB margin. An example simulation of the spatial domain beam prediction accuracy is as follows:

[0056] The beam measurement and reporting accuracy may be improved based on increasing the coverage of a beam measurement reference signal (e.g., CSI-RS), reducing interference and noise at the UE receiver, and / or implementing a high resolution quantization process (e.g., high information bit ratio) to reduce quantization errors in beam reports. Improving beam measurement and reporting accuracy may support improved spatial domain beam prediction (e.g., predicted beam 204) of the ML model 206. Better prediction of the predicted beam 204 may improve beam pair selection between the UE and a network entity and provide improved system performance.

[0057] Figures 3 to 5 A signaling diagram for generating beam reports that can perform an ML-based spatial domain beam prediction process is shown. Figure 3A signaling diagram 300 for beam reporting based on CSI reporting configuration is shown. The UE 102 sends 306 to the network entity 104 a UE capability report indicating one or more UE capabilities for beam measurement and reporting to enable the network entity to perform ML-based spatial domain beam prediction at 318. The one or more UE capabilities may correspond to a maximum number of CSI-RS resources or symbols of CSI-RS resources or CSI-RS resource sets for the measurement configuration at 314 for preparing a beam report, a maximum number of CSI-RS resources or symbols of CSI-RS resources or CSI-RS resource sets in a time slot for measurement at 314 for preparing a beam report, and / or a maximum number of reported beams in a beam report. In some embodiments, the network entity 104 may receive an indication of one or more UE capabilities from a core network entity, such as the AMF 121 described in FIG. 100. The one or more UE capabilities may be counted per CC, per band, per band combination, or per UE. One or more UE capabilities may be reported to the network entity 104 per feature set, per frequency band, per frequency band combination, or per UE.

[0058] The UE 102 with the enhanced receiver may send 306 one or more additional UE capabilities to the network entity 104, the one or more additional UE capabilities indicating that the UE 102 supports the enhanced beam measurement and reporting technique. For example, the UE 102 may send 306 a UE capability report to the network entity 104 indicating a minimum processing delay for the UE 102 to measure 314 a beam quality (e.g., L1-RSRP / L1-SINR measurement) configured by the CSI report with the enhanced receiver. The UE 102 may also indicate in the UE capability report a maximum number of beam measurement reference signals (e.g., SSB / CSI-RS) available for the UE for beam measurement 314 with the enhanced receiver and / or a maximum number of beam measurement reference signals (e.g., SSB / CSI-RS) in a time slot for beam measurement 314 with the enhanced receiver. The one or more additional UE capabilities associated with the enhanced receiver may be counted per CC, per band, per band combination, or per UE. The one or more additional UE capabilities associated with the enhanced receiver may be reported per feature set, per frequency band, per frequency band combination, or per UE to the network entity 104. In some implementations, the UE 102 may report 306 two sets of UE capabilities for beam measurement and reporting, wherein a first set of UE capabilities is for beam measurement and reporting based on a receiver with a larger measurement error, and a second set of UE capabilities is for advanced beam measurement and reporting based on a receiver with a smaller measurement error.

[0059] The network entity 104 sends 308 first control signaling to the UE 102 to configure a CSI reporting configuration for ML-based beam prediction 318 at the network entity 104. The control signaling may be based on one or more UE capabilities that the network entity 104 receives 306 from the UE 102. In some embodiments, the network entity 104 may configure a CSI-RS list as CMRs for beam reporting sent 316 to the network entity 104 for ML-based spatial domain beam prediction 318 at the network entity 104. The network entity 104 may optionally include an indication of a quantization process for beam reporting in the first control signaling sent 308 to the UE 102.

[0060] The network entity 104 may send 308 the first control signaling using RRC signaling (e.g., CSI-ReportConfig). The RRC signaling may indicate to the UE 102 an RRC reconfiguration message or a system information block (SIB) from the network entity 104. The SIB may be a predefined SIB (e.g., SIB1) or a different SIB (e.g., SIB J, where J is greater than 21). The RRC parameters included in the first control signaling may indicate to the UE 102 that a high-resolution quantization process is used to quantize 314 the measured beam quality. The RRC signaling may indicate that the CMR corresponds to a CSI-RS resource set from the same port (e.g., a CSI-RS resource in a resource set configured with RRC parameter repetition). The CMR may be a CSI-RS resource of one or more symbols to increase the coverage of the CSI-RS, where the number of symbols is configured by the network entity 104 via RRC signaling. The CSI-RS of each symbol may be from the same port.

[0061] The RRC signaling may also include parameters such as indicating whether to report L1-RSRP, L1-RSRP and L1-SINR, or L1-RSRP and beam quality indicator (BQI) reporting quantity. The RRC signaling further includes parameters such as: a first threshold for determining whether the measured L1-SINR of the beam meets the threshold; a quantization process indicator (e.g., whether high-resolution quantization is enabled); a quantization mode (e.g., whether the beam report is based on the absolute value of one or more strongest beams or the absolute value and the difference of the remaining reported beams); and / or a high measurement accuracy flag for indicating whether the network entity 104 requires high measurement accuracy for beam measurement and reporting. High measurement accuracy can enable UE 102 to activate an enhanced receiver (e.g., a receiver with interference and noise suppression capabilities) of UE 102. The network entity 104 can configure UE 102 to report L1-RSRP and L1-SINR based on reportQuantity = cri-RSRP-SINR or RSRP-SINR. The network entity 104 may configure the UE to report L1-RSRP and BQI based on reportQuantity = cri-RSRP-BQI or RSRP-BQI. The network entity 104 may configure the first threshold based on sinrThreshold. The network entity 104 may enable high-resolution quantization based on highResQuantization. The network entity 104 may configure the quantization mode based on quantizationMode. The network entity 104 may configure a high measurement accuracy flag based on highAccuracy.

[0062] The UE 102 may receive 310 second control signaling from the network entity 104, the second control signaling triggering CSI reporting configuration for beam reporting for ML-based spatial domain beam prediction 318 at the network entity 104. The second control signaling may correspond to a MAC-CE or a DCI. For semi-persistent CSI reporting, the second control signaling may correspond to a MAC-CE. For aperiodic CSI reporting, the second control signaling may correspond to a DCI. The network entity 104 may optionally include an indication of a quantization process for beam reporting in the second control signaling sent 310 to the UE 102.

[0063] The second control signaling may include parameters similar to those described for the first control signaling. In an example, some of the parameters may be predefined parameters. For example, the first threshold of the measured L1-SINR of the beam may be predefined or configured to -10 dB. The parameter may also indicate that the quantization process indicator is enabled when the beam report is based on L1-RSRP+L1-SINR or L1-RSRP+BQI report. The parameter may further indicate that the quantization mode is based on the absolute mode when the beam report is based on L1-RSRP+L1-SINR or L1-RSRP+BQI report. The parameter may further indicate that the high measurement accuracy flag is enabled when the beam report is based on L1-RSRP+L1-SINR or L1-RSRP+BQI report. The network entity 104 may avoid configuring time domain measurement restrictions, such as timeRestrictionForChannelMeasurments and / or timeRestrictionForInterferenceMeasurements, so that the UE 102 does not activate the first layer filter for receiving periodic / semi-persistent CMR at different time instances, which may reduce the accuracy of the measurement 314.

[0064] The network entity 104 sends 312 a CSI-RS for beam measurement to the UE 102. In an example, the network entity 104 may send 314 one or more CSI-RS using a repetition-based process to increase the coverage of the CSI-RS. The network entity 104 may repeatedly send 312 N CSI-RS resources in a resource set from one or more same ports based on the network entity 104 configuring RRC parameters for the CSI-RS resource set. The network entity 104 may send 312 the N CSI-RS resources in N symbols within one or more time slots. The network entity 104 may avoid sending 312 the N CSI-RS resources in different bandwidths or different resource elements.

[0065] The UE 102 receives 312 a CSI-RS configured as a CMR and measures 314 a beam quality. The UE 102 also determines a quantization process for the beam quality measurement 314 of the CSI-RS and quantizes the beam quality 314 based on the quantization process. The UE 102 may measure L1-RSRP / L1-SINR based on N CSI-RS resources. The UE 102 may receive 312 CSI-RS resources based on a joint channel estimation.

[0066] For multi-slot transmission (e.g., M time slot transmission), the network entity 104 may configure a time slot index m for each CSI-RS resource within the M time slots using the first control signaling and / or the second control signaling. For an aperiodic CSI-RS resource set, the network entity 104 configures a time slot offset for the first time slot using the RRC parameter aperiodicTriggeringOffset, and configures a time slot offset for each CSI-RS resource based on aperiodicTriggeringOffset+m. The network entity 104 configures the time slot offset for each CSI-RS resource, so that when the time slot offset for each CSI-RS is configured by the network entity 104, the UE 102 may ignore the time slot offset configured for the CSI-RS resource set. The network entity 104 may configure a differential slot offset for CSI-RS resources within a resource set based on an RRC parameter aperiodicTriggeringOffsetWithinSet, where the slot offset for the CSI-RS resources corresponds to aperiodicTriggeringOffset+aperiodicTriggeringOffsetWithinSet.

[0067] The UE 102 sends 316 a beam report for the received CSI-RS to the network entity 104. The beam report is based on the measured / quantized 314 beam quality for the received CSI-RS. The UE 102 may send 316 the beam report to the network entity 104 via a PUCCH or PUSCH resource. The network entity 104 performs 318 ML-based spatial domain beam prediction based on the beam report (e.g., the measured / quantized 314 beam quality for the CSI-RS). The network entity 104 may perform 320 a beam management procedure with the UE 102 based on the beam prediction 318. Figure 3 Beam reporting based on CSI reporting configuration is shown. Figures 4 to 5 Describes the specific type of CSI reporting configuration.

[0068] Figure 4 A signaling diagram 400 for L1-RSRP / L1-SINR reporting is shown. Figure 3Elements 306, 310, 312, 314, and 320 are depicted. The network entity 104 sends 408 first control signaling to the UE 102 to configure a CSI reporting configuration for ML-based beam prediction 418 at the network entity 104. The network entity 104 configures one or more CSI-RS as CMRs for both L1-RSRP reports and L1-SINR reports sent 416 to the network entity 104 for ML-based spatial domain beam prediction 418 at the network entity 104. The network entity 104 may optionally include an indication of a quantization process for the beam reporting in the first control signaling sent 408 to the UE 102.

[0069] The UE 102 sends 416 an L1-RSRP / L1-SINR report for the received CSI-RS to the network entity 104. The L1-RSRP / L1-SINR report is based on the measured / quantized 314 beam quality for the received CSI-RS. The network entity 104 may determine whether to perform 418 ML-based spatial domain beam prediction based on the reported L1-SINR. For example, if all L1-SINRs in the report are greater than a threshold, the network entity 104 performs 418 ML-based spatial domain beam prediction for the L1-RSRP / L1-SINR report. In other examples, when the L1-SINR of at least some of the reported beams is below a threshold, the network entity 104 may determine not to perform 418 ML-based spatial domain beam prediction. If the network entity 104 performs 418 beam prediction based on all L1-SINRs greater than the threshold, the network entity 104 may further perform 320 a beam management process with the UE 102 based on the beam prediction 318.

[0070] Figure 5 A signaling diagram 500 of a beam report associated with a reporting beam that meets a first threshold criterion is shown. Figure 3 Elements 306, 310, 312, 314, and 320 are depicted.

[0071] The network entity 104 sends 508 first control signaling to the UE 102 to configure a CSI reporting configuration for ML-based beam prediction 418 at the network entity 104. The network entity 104 configures one or more CSI-RS as CMR, and configures a threshold (e.g., -10 dB) for the beam report sent 516 to the network entity 104. The network entity 104 may optionally include an indication of a quantization process for the beam report in the first control signaling sent 508 to the UE 102.

[0072] In an implementation, the network entity 104 configures the UE 102 to send 516 a beam report for a received CSI-RS and an indicator of whether the L1-SINR for the reported beam meets a first threshold criterion (e.g., a threshold configured via first control signaling). The threshold may be a predefined threshold (e.g., L1-SINR is greater than -10 dB). The UE 102 may indicate the L1-RSRP of the configured beam in the beam report and include an indicator of whether the L1-SINR for all reported beams is greater than the threshold. If the received indicator that all L1-SINRs are greater than the threshold is positive, the network entity 104 may perform 518 ML-based spatial domain beam prediction for the configured beam based on the received L1-RSRP. Alternatively, if the received indicator is negative, the network entity 104 may switch to a non-ML-based beam management process.

[0073] In another implementation, if the L1-SINR of all reported beams is less than or equal to the threshold, the UE 102 does not send 516 a beam report for the received CSI-RS. That is, the UE 102 does not report the L1-RSRP of the configured beam. Therefore, the network entity 104 may perform 518 ML-based spatial domain beam prediction based on the beam report received 516 from the UE 102. Based on the network entity 104 performing 518 ML-based spatial domain beam prediction, the network entity 104 may further perform 320 a beam management process with the UE 102.

[0074] Thus, if the L1-SINR of the received CSI-RS is greater than the configured threshold, the UE 102 may report the L1-RSRP of the received CSI-RS and: send 516 an indicator of whether the L1-SINR of the received CSI-RS is greater than the threshold, or send 516 a beam report based on the L1-SINR of the received CSI-RS being greater than the threshold. If the L1-SINR of the received CSI-RS is less than or equal to the configured threshold, the UE 102 may indicate the L1-RSRP of the received CSI-RS and: send 516 an indication that the L1-SINR of at least one of the received CSI-RS is less than or equal to the threshold, or do not send 516 a beam report based on the L1-SINR of the received CSI-RS being less than or equal to the threshold. Figures 3 to 5 The reporting process for implementing beam prediction is described. FIG. 6A to FIG. 6B and 7A to Figure 7B The CSI-RS resource configuration used to implement the reporting process is described.

[0075] Fig. 6A Diagram 600 shows a differential aperiodic slot offset configuration. Figure 6B A diagram 650 is shown of an absolute aperiodic slot offset configuration.

[0076] The network entity may configure CSI-RS resource set 1 with repetition enabled and a slot offset equal to 4. When CSI-RS resource set 1 is aperiodic, the network entity sends a PDCCH to trigger CSI-RS resource set 1. In diagram 600 of differential aperiodic slot offset configuration, CSI resource set 1 corresponds to m = 0, and CSI resource set 2 corresponds to m = 2. Therefore, CSI-RS resource 1 in diagram 600 is configured at 0 slots after 4 slot offsets from the PDCCH triggering slot, and CSI-RS resource 2 is configured at 1 slot after 4 slot offsets from the PDCCH triggering slot.

[0077] In diagram 650 of the absolute aperiodic slot offset configuration, CSI resource set 1 corresponds to m = 6 and CSI resource set 2 corresponds to m = 7. Therefore, CSI-RS resource 1 in diagram 650 is configured at 6 absolute slots after the PDCCH triggering slot and CSI-RS resource 2 is configured at 7 absolute slots after the PDCCH triggering slot. The network entity may configure the absolute slot offset of the CSI-RS resources based on the RRC parameter aperiodicTriggeringOffsetPerResource.

[0078] The network entity sends CSI-RS resources for L1-RSRP / L1-SINR measurement in N symbols or N repetitions. The network entity may send CSI-RS of N symbols in one time slot or more than one time slot. The network entity may configure the number of symbols and / or the number of time slots of the CSI-RS resources via RRC signaling. The UE measures L1-RSRP / L1-SINR based on N symbols / repetitions of the CSI-RS resources. The UE may receive N symbols / repetitions of the CSI-RS resources based on joint channel estimation. In the example, the network entity configures the number of repetitions / symbols of the CSI-RS resources based on the RRC parameter nrofRepetitions configured in CSI-RS-ResourceMapping or in the CSI-RS resources (e.g., NZP-CSI-RS-Resource). The network entity repeats sending the CSI-RS in consecutive symbols according to the nrofRepetitions parameter.

[0079] FIG. 7A to FIG. 7BFigures 700 to 750 show CSI-RS transmissions based on the number of repetitions configured. Figure 700 shows that the CSI-RS is configured with 10 repetitions (e.g., on 3 subcarriers per resource block (RB)) starting at the eighth symbol. The 10 repetitions in Figure 700 occur on portions of 2 different time slots.

[0080] The network entity may also configure the number of repetitions within a slot separately and configure the number of slots based on the RRC parameters nrofRepetitionsWithinSlot and nrofSlots in the CSI-RS-ResourceMapping or CSI-RS resource (e.g., NZP-CSI-RS-Resource). The network entity may send the CSI-RS resource in consecutive symbols based on the nrofRepetitions parameter for repetitions within a slot and send the CSI-RS resource in multiple slots based on the nrofSlots parameter. Figure 750 shows a CSI-RS transmission with the number of repetitions parameter configured. The CSI-RS in Figure 750 is configured with 4 repetitions per slot, 2 slots per repetition, and a start time at the eighth symbol of each slot.

[0081] The UE may apply a high-resolution L1-RSRP quantization process to the reported L1-RSRP based on the indication in the first control signaling / second control signaling. The network entity may configure the range of the reported L1-RSRP and / or the step size of the L1-RSRP quantization performed using the high-resolution quantization process. The range of the reported L1-RSRP for the high-resolution quantization process may be predefined (e.g., -160 dBm to -20 dBm). The step size of the L1-RSRP for the high-resolution quantization process may also be predefined (e.g., 0.5 dB). The range of the differential L1-RSRP may be configured by the network entity through RRC signaling, or may be predefined (e.g., -40 dB to 0 dB). The step size of the differential L1-RSRP may also be configured by the network entity through RRC signaling, or may be predefined (e.g., 0.5 dB).

[0082] The UE may report both L1-RSRP and L1-SINR for the configured CMRs or a subset of the configured CMRs, and the UE may send beam reports in CSI part 1 or CSI part 2. The UE may report absolute L1-RSRP / L1-SINR for the configured CMRs. The reporting format for absolute reporting of N configured CMRs may correspond to reporting L1-RSRP for CMR 1 to CMR N, followed by reporting L1-SINR for CMR 1 to CMR N.

[0083] The UE may report the absolute L1-RSRP / L1-SINR of the CMR with the strongest L1-RSRP / L1-SINR, and for the remaining configured CMRs, report the differential L1-RSRP / L1-SINR with reference to the absolute L1-RSRP and L1-SINR. The reporting format for differential reporting of N configured CMRs may correspond to the following reporting order: CMR index k1 with the strongest L1-RSRP, L1-RSRP of CMR 1, ..., differential L1-RSRP of CMR k1-1, differential L1-RSRP of CMR k1+1, ..., differential L1-RSRP of CMR N, CMR index k2 with the strongest L1-SINR, L1-SINR of CMR 1, ..., differential L1-SINR of CMR k2-1, differential L1-SINR of CMR k2+1, ..., differential L1-SINR of CMR N.

[0084] The UE may report the CMR indexes of the M selected CMRs, where M < N; and the absolute L1-RSRP / L1-SINR of the M CMRs. The reporting format for absolute reporting of the M selected CMRs may correspond to reporting the CMR index x 1 To CMR index x M , then report CMR x 1 to CMR x M L1-RSRP, then reports CMR x 1 to CMR x M L1-SINR.

[0085] The UE may report the absolute L1-RSRP / L1-SINR of the CMR with the strongest L1-RSRP / L1-SINR, and for the remaining M-1 selected CMRs, report the differential L1-RSRP / L1-SINR with reference to the absolute L1-RSRP / L1-SINR. The reporting format for differential reporting of the M selected CMRs may correspond to the following reporting order: XMR index x1 to CMR index x M , followed by CMR x 1 L1-RSRP, followed by CMR x 2 Differential L1-RSRP to CMR x M The differential L1-RSRP, followed by CMR x 1 L1-SINR, followed by CMR x 2 The differential L1-SINR to CMR x M The differential L1-RSRP.

[0086] The UE may report the L1-RSRP and BQI of a configured CMR or a subset of configured CMRs. The UE reports the absolute / differential L1-RSRP of a beam with a positive BQI. The UE may also report the number of CMRs with a positive BQI. The UE may report the number of CMRs, CMR indexes, and L1-RSRPs in the same CSI part or in different CSI parts in a similar manner. The UE may indicate a bitmap of CMRs with a positive BQI and the absolute / differential L1-RSRP of CMRs with a positive BQI. The CMR may correspond to a CSI-RS resource or a CSI-RS resource set. The UE may report a CMR index based on a reported CSI-RS resource indicator or a CSI-RS resource set indicator. When the L1-SINR of the CMR is greater than a threshold, the UE may report a positive BQI for the CMR. Otherwise, the UE reports a negative BQI.

[0087] The UE reports the number of CMRs in CSI part 1 and reports the CMR index and absolute / differential L1-RSRP for beams with positive BQI in CSI part 2. The UE may indicate a bitmap of CMRs with positive BQI in CSI part 1 and report the absolute / differential L1-RSRP for CMRs with positive BQI in CSI part 2. The payload size of L1-RSRP in CSI part 2 is based on the number of positive BQIs reported in CSI part 1. The reporting format for absolute or differential L1-RSRP for Q CMRs with positive BQI may correspond to: Report CMR index x 1 To CMR index x Q , followed by the CMR index x 1 L1-RSRP, followed by CMR x 2 to CMR x Q The absolute or differential L1-RSRP.

[0088] The UE may report the absolute or differential L1-RSRP of the configured or selected CMRs, and report the BQI to indicate whether the L1-SINR of any of the reported CMRs is less than or equal to the threshold configured by the first control signaling. The UE may report the CMR, the absolute L1-RSRP of the configured N CMRs, and the BQI based on a reporting format corresponding to reporting the BQI, followed by reporting the L1-RSRP of CMR 1 to the L1-RSRP of CMR N. In another example, the UE may report the absolute L1-RSRP of the configured N CMRs, and the BQI based on a reporting format corresponding to reporting the BQI, followed by reporting the L1-RSRP of CMR 1 to the L1-RSRP of CMR N. 1 To CMR index x M , then report the CMR index x 1 L1-RSRP to CMR index x M The reporting format of reporting L1-RSRP and then reporting BQI is used to report the CMR indexes and absolute L1-RSRP and BQI of the selected M CMRs.

[0089] In some examples, such as when the UE sends beam reports using different scrambling identifiers (IDs) for different BQI states, the UE may implicitly report the BQI. The network entity may configure different scrambling IDs associated with different BQIs via RRC signaling. Alternatively, the UE may send beam reports using different resources for different BQIs. The network entity configures different resources (e.g., PUCCH resources) for beam reports associated with different BQIs via RRC signaling. When the L1-SINR of the reported CMR is greater than a threshold, the UE may also report the L1-RSRP of the configured CMR or a subset of the configured CMR. Otherwise, the UE may not report the L1-RSRP. Figures 2 to 7B Techniques for implementing ML-based beam prediction are shown. Figures 8 to 9 Shown is a method for implementing Figures 2 to 7B Specifically, Figure 8 UE 102 is shown Figures 2 to 7B Implementation of one or more aspects. Fig. 9 The network entity 104 is shown Figures 2 to 7B Implementation of one or more aspects.

[0090] Figure 8 A flowchart 800 of a method of wireless communication at a UE is shown. Figure 1 , Figures 3 to 5 and Fig.10 The method may be performed by UE 102, UE equipment 1002, etc., which may include memory 1026', 1006', 1016 and may correspond to the entire UE 102 or the entire UE equipment 1002, or components of the UE 102 or UE equipment 1002 (such as a wireless baseband processor 1026 and / or an application processor 1006).

[0091] UE 102 sends 806 a UE capability report to the network entity indicating the UE's ability to send spatial domain beam prediction reports for the ML model. Figures 3 to 5 , the UE 102 sends 306 to the network entity 104 a UE capability report for beam measurement and for reporting on ML-based spatial domain beam prediction at the network entity 104 .

[0092] The UE 102 receives 808 from a network entity a configuration for a measurement report using a beam quality quantization procedure—the measurement report corresponding to at least one of: a CSI report, an L1-RSRP report, or an L1-SINR report, each of which is based on beam measurement using one or more CSI-RS as a CMR. Figure 3 and Figure 5 , the UE 102 receives 308, 508 a first control signaling from the network entity 104, the first control signaling indicating a CSI reporting configuration for transmission of a beam report for ML-based beam prediction. Figure 4 , the UE 102 receives 408 a first control signaling from the network entity 104, the first control signaling indicating a CSI reporting configuration for transmission of L1-RSRP / L1-SINR reports for ML-based beam prediction.

[0093] UE 102 receives 810 control signaling from a network entity that triggers a measurement report. Figures 3 to 5 , the UE 102 receives 310 a second control signaling from the network entity 104, the second control signaling triggering a CSI reporting configuration for a measurement report for ML-based beam prediction.

[0094] UE 102 receives 812 one or more CSI-RS for beam measurement from a network entity. Figures 3 to 5 , the UE 102 receives 312 a CSI-RS for beam measurement from the network entity 104.

[0095] UE 102 sends 816 a measurement report to the network entity - the measurement report is based on the beam measurement and beam quality quantification process. Figure 3 and Figure 5 , the UE 102 sends 316, 516 beam measurements of the received CSI-RS to the network entity 104. Figure 4 , the UE 102 sends 416 to the network entity 104 an L1-RSRP / L1-SINR report for the received CSI-RS. Figure 8 A method from the UE side of a wireless communication link is described, while Fig. 9 A method from the network side of a wireless communication link is described.

[0096] Fig. 9 900 is a flow chart of a method of wireless communication at a network entity. Figure 1 , Figures 3 to 5 and Fig.11, the method may be performed by one or more network entities 104, which may correspond to a base station or a unit of a base station, such as RU 106, DU 108, CU 110, RU processor 1106, DU processor 1126, CU processor 1146, etc. One or more network entities 104 may include a memory 1106' / 1126' / 1146', which may correspond to the entirety of one or more network entities 104, or a component of one or more network entities 104, such as RU processor 1106, DU processor 1126 or CU processor 1146.

[0097] The network entity 104 receives 906 a UE capability report from the UE, the report indicating the UE's ability to send a spatial domain beam prediction report for the ML model. Figures 3 to 5 , the network entity 104 receives 306 from the UE 102 a UE capability report for beam measurement and for reporting on ML-based spatial domain beam prediction at the network entity 104 .

[0098] The network entity 104 sends 908 to the UE a configuration for a measurement report using a beam quality quantization procedure—the measurement report corresponding to at least one of: a CSI report, an L1-RSRP report, or an L1-SINR report, each of which is based on one or more CSI-RS used as CMRs. Figure 3 and Figure 5 , the network entity 104 sends 308, 508 first control signaling to the UE 102, the first control signaling indicating a CSI reporting configuration for transmission of beam reports for ML-based beam prediction. Figure 4 , the network entity 104 sends 408 a first control signaling to the UE 102, the first control signaling indicating a CSI reporting configuration for transmission of L1-RSRP / L1-SINR reports for ML-based beam prediction.

[0099] The network entity 104 sends 910 to the UE control signaling that triggers the measurement report—the control signaling indicating a second parameter that is different from the first parameter associated with the configuration. Figures 3 to 5 , the network entity 104 sends 310 a second control signaling to the UE 102, the second control signaling triggering a CSI reporting configuration for a measurement report for ML-based beam prediction.

[0100] The network entity 104 sends 912 one or more CSI-RSs to the UE for use as CMRs. Figures 3 to 5 , the network entity 104 sends 312 a CSI-RS for beam measurement to the UE 102.

[0101] The network entity 104 receives 916 a measurement report from the UE - the measurement report is based on the beam quality quantization process and one or more CSI-RS. Figure 3 and Figure 5 , the network entity 104 receives 316, 516 beam measurements of the received CSI-RS from the UE 102. Figure 4 , the network entity 104 receives 416 from the UE 102 a L1-RSRP / L1-SINR report of the received CSI-RS.

[0102] The network entity 104 communicates 920 with the UE based on the spatial domain beam prediction of the ML model - the information included in the measurement report is used as input to the ML model to generate the spatial domain beam prediction. Figures 3 to 5 , the network entity 104 communicates 320 with the UE 102 via a beam management process based on beam prediction 318, 418, 518. Fig.10 The described UE equipment 1002 may perform the method of flowchart 800. Fig.11 The method of flowchart 900 may be performed by one or more of the described network entities 104 .

[0103] Fig.10 1000 is a diagram illustrating an example of a hardware implementation of a UE device 1002. The UE device 1002 may be a UE 102, a component of a UE 102, or may implement UE functionality. The UE device 1002 may include an application processor 1006, which may have an on-chip memory 1006'. In an example, the application processor 1006 may be coupled to a secure digital (SD) card 1008 and / or a display 1010. The application processor 1006 may also be coupled to a sensor module 1012, a power supply 1014, an additional memory module 1016, a camera 1018, and / or other related components. For example, the sensor module 1012 may control a barometric pressure sensor / altimeter, a motion sensor (such as an inertial management unit (IMU)), a gyroscope, an accelerometer, a light detection and ranging (LIDAR) device, a radio-aided detection and ranging (RADAR) device, a sound navigation and ranging (SONAR) device, a magnetometer, an audio device, and / or other technologies for positioning.

[0104] The UE equipment 1002 may further include a wireless baseband processor 1026, which may be referred to as a modem. The wireless baseband processor 1026 may have an on-chip memory 1026'. Together with and similar to the application processor 1006, the wireless baseband processor 1026 may also be coupled to a sensor module 1012, a power supply 1014, an additional memory module 1016, a camera 1018, and / or other related components. The wireless baseband processor 1026 may additionally be coupled to one or more subscriber identity modules (SIM) cards 1020 and / or one or more transceivers 1030 (e.g., wireless RF transceivers).

[0105] Within one or more transceivers 1030, the UE equipment 1002 may include a Bluetooth module 1032, a WLAN module 1034, an SPS module 1036 (e.g., a GNSS module), and / or a cellular module 1038. The Bluetooth module 1032, the WLAN module 1034, the SPS module 1036, and the cellular module 1038 may each include an on-chip transceiver (TRX), or in some cases, only a transmitter (TX) or only a receiver (RX). The Bluetooth module 1032, the WLAN module 1034, the SPS module 1036, and the cellular module 1038 may each include a dedicated antenna and / or utilize an antenna 1040 to communicate with one or more other nodes. For example, the UE equipment 1002 can communicate with another UE 102 (e.g., sidelink communication) and / or communicate with a network entity 104 (e.g., uplink / downlink communication) via an antenna 1040 through a transceiver 1030, where the network entity 104 can correspond to a base station or a unit of a base station, such as a RU 106, a DU 108, or a CU 110.

[0106] The wireless baseband processor 1026 and the application processor 1006 may each include a computer-readable medium / memory 1026', 1006', respectively. Additional modules of the memory 1016 may also be considered as computer-readable media / memory. Each computer-readable medium / memory 1026', 1006', 1016 may be non-transitory. The wireless baseband processor 1026 and the application processor 1006 may each be responsible for general processing, including executing software stored on the computer-readable medium / memory 1026', 1006', 1016. The software, when executed by the wireless baseband processor 1026 / application processor 1006, enables the wireless baseband processor 1026 / application processor 1006 to perform various functions described herein. The computer-readable medium / memory may also be used to store data manipulated by the wireless baseband processor 1026 / application processor 1006 when executing the software. The wireless baseband processor 1026 / application processor 1006 may be a component of the UE 102. UE equipment 1002 may be a processor chip (eg, modem and / or applications) and include only a wireless baseband processor 1026 and / or an application processor 1006. In other examples, UE equipment 1002 may be the entire UE 102 and include additional modules of equipment 1002.

[0107] As discussed, the beam quality quantization component 140 is configured to: receive from a network entity a configuration for a measurement report using a beam quality quantization process, the measurement report including at least one of: a CSI report, an L1-RSRP report, or an L1-SINR report, each of which is based on beam measurement using one or more CSI-RS as a CMR; receive from the network entity one or more CSI-RS for beam measurement; and send to the network entity a measurement report, the measurement report based on beam measurement and beam quality quantization process. The beam quality quantization component 140 may be within the wireless baseband processor 1026, the application processor 1006, or both the wireless baseband processor 1026 and the application processor 1006. The beam quality quantization component 140 may be one or more hardware components specifically configured to perform the processing / algorithms, implemented by one or more processors configured to perform the processing / algorithms, stored in a computer-readable medium to be implemented by one or more processors, or a combination thereof.

[0108] UE equipment 1002 may include various components configured for various functions. In an example, UE equipment 1002, in particular, radio baseband processor 1026 and / or application processor 1006 include: a component for receiving a configuration for a measurement report using a beam quality quantization process from a network entity, the measurement report including at least one of the following: a CSI report, an L1-RSRP report, or an L1-SINR report, each of which is based on a beam measurement using one or more CSI-RS as a CMR; a component for receiving one or more CSI-RS for beam measurement from a network entity; and a component for sending a measurement report to a network entity, the measurement report being based on beam measurement and beam quality quantization process. UE equipment 1002 further includes a component for receiving control signaling triggering the measurement report from the network entity. The UE equipment 1002 further includes a component for sending a UE capability report to a network entity, the UE capability report indicating at least one of: a first capability of the UE to send reports for spatial domain beam prediction for an ML model; a first maximum number of CSI-RS resources, symbols of CSI-RS resources, or CSI-RS resource sets configured for reporting; a second maximum number of CSI-RS resources, symbols of CSI-RS resources, or CSI-RS resource sets for reporting in a time slot; a third maximum number of reported beams in a report; a second capability of the UE receiver for reporting; or a minimum processing delay based on the UE receiver performing beam measurements for the report.

[0109] The component for receiving one or more CSI-RS for beam measurement is further configured to at least one of: receive repetitions of one or more CSI-RS from a network entity; or receive one or more CSI-RS on CSI resources of one or more same antenna ports from a network entity. The component for sending a measurement report is further configured to: send a first measurement value of L1-RSRP and a second measurement value of BQI for one or more CSI-RS. The component for sending a measurement report is further configured to: send a CMR index and at least one of a first measurement value of L1-RSRP for CMR, a second measurement value of BQI, or a third measurement value of L1-SINR. The component can be a beam quality quantization component 140 of the UE equipment 1002 configured to perform the functions described by the component.

[0110] Fig.111100 is a diagram illustrating an example of a hardware implementation of one or more network entities 104. One or more network entities 104 may be a base station, a component of a base station, or may implement base station functionality. One or more network entities 104 may include or may correspond to at least one of a RU 106, a DU 108, or a CU 110. The CU 110 may include a CU processor 1146, which may have an on-chip memory 1146'. In some aspects, the CU 110 may further include an additional memory module 1156 and / or a communication interface 1148, both of which may be coupled to the CU processor 1146. The CU 110 may communicate with the DU 108 via a midhaul link 162, such as an F1 interface between the communication interface 1148 of the CU 110 and the communication interface 1128 of the DU 108.

[0111] The DU 108 may include a DU processor 1126, which may have an on-chip memory 1126'. In some aspects, the DU 108 may further include an additional memory module 1136 and / or a communication interface 1128, both of which may be coupled to the DU processor 1126. The DU 108 may communicate with the RU 106 via a fronthaul link 160 between the communication interface 1128 of the DU 108 and the communication interface 1108 of the RU 106.

[0112] The RU 106 may include a RU processor 1106, which may have an on-chip memory 1106'. In some aspects, the RU 106 may further include an additional memory module 1116, a communication interface 1108, and one or more transceivers 1130, all of which may be coupled to the RU processor 1106. The RU 106 may further include an antenna 1140, which may be coupled to the one or more transceivers 1130, such that the RU 106 may communicate with the UE 102 via the antenna 1140 through the one or more transceivers 1130.

[0113] On-chip memory 1106 ', 1126 ', 1146 'and additional memory modules 1116, 1136, 1156 can each be considered as a computer-readable medium / memory. Each computer-readable medium / memory can be non-temporary. Each of the processors 1106, 1126, 1146 is responsible for general processing, including executing software stored on the computer-readable medium / memory. The software, when executed by the corresponding processor 1106, 1126, 1146, enables the processor 1106, 1126, 1146 to perform various functions described herein. The computer-readable medium / memory can also be used to store data manipulated by the processor 1106, 1126, 1146 when executing the software. In an example, the ML-based beam prediction component 150 may be located at one or more network entities 104, such as at the CU 110; at both the CU 110 and the DU 108; at each of the CU 110, DU 108, and RU 106; at the DU 108; at both the DU 108 and the RU 106; or at the RU 106.

[0114] As discussed, the ML-based beam prediction component 150 is configured to: send a configuration for a measurement report using a beam quality quantization process to the UE, the measurement report including at least one of the following: a CSI report, an L1-RSRP report, or an L1-SINR report, each of which is based on one or more CSI-RS used as a CMR; send one or more CSI-RS used as a CMR to the UE; and receive a measurement report from the UE, the measurement report based on the beam quality quantization process and the one or more CSI-RS. The ML-based beam prediction component 150 can be within one or more processors of one or more network entities 104, such as the RU processor 1106, the DU processor 1126, and / or the CU processor 1146. The ML-based beam prediction component 150 can be one or more hardware components specifically configured to perform the stated process / algorithm, implemented by one or more processors 1106, 1126, 1146 configured to perform the stated process / algorithm, stored in a computer-readable medium for implementation by one or more processors 1106, 1126, 1146, or a combination thereof.

[0115] The one or more network entities 104 may include various components configured for various functions. In an example, the one or more network entities 104 include: a configuration component for sending a measurement report for using a beam quality quantization process to a UE, the measurement report including at least one of the following: a CSI report, an L1-RSRP report, or an L1-SINR report, each of which is based on one or more CSI-RS used as a CMR; a component for sending one or more CSI-RS used as a CMR to the UE; and a component for receiving a measurement report from the UE, the measurement report being based on the beam quality quantization process and the one or more CSI-RS. The one or more network entities 104 further include a component for sending control signaling to the UE to trigger the measurement report, the control signaling indicating a second parameter, the second parameter being different from the first parameter associated with the configuration. The one or more networks 104 further include means for receiving a UE capability report from the UE, the UE capability report indicating at least one of: a first capability of the UE to send a report for spatial domain beam prediction for an ML model; a first maximum number of CSI-RS resources, symbols of CSI-RS resources, or CSI-RS resource sets configured for reporting; a second maximum number of CSI-RS resources, symbols of CSI-RS resources, or CSI-RS resource sets for reporting in a time slot; a third maximum number of reported beams in a report; a second capability of the UE receiver for reporting; or a minimum processing delay for performing beam measurements for the report based on the UE receiver. The one or more network entities 104 further include means for communicating with the UE based on spatial domain beam prediction for an ML model, wherein information included in the measurement report is used as input to the ML model to generate spatial domain beam predictions.

[0116] The means for transmitting one or more CSI-RS is further configured to at least one of: transmit repetitions of one or more CSI-RS to the UE; or transmit one or more CSI-RS on CSI resources associated with one or more same antenna ports of the UE to the UE. The means may be an ML-based beam prediction component 150 of one or more network entities 104 configured to perform the functions recited by the means.

[0117] The specific order or hierarchy of the boxes in the processes and flow charts disclosed herein is an illustration of an example method. Therefore, the specific order or hierarchy of the boxes in the processes and flow charts can be rearranged. Some boxes can also be merged or deleted. Dashed lines can indicate optional elements of the diagram. The attached method claims present elements of each box in an example order and are not limited to the specific order or hierarchy presented in the claims, processes and flow charts.

[0118] The description set forth herein describes various configurations in conjunction with the accompanying drawings, but does not represent the only configuration in which the concepts described in this section can be practiced. The detailed description includes specific details for providing a comprehensive explanation of each concept. However, these concepts can be practiced without using these specific details. In some cases, well-known structures and components are shown in block diagram form to avoid blurring such concepts.

[0119] Various aspects of wireless communication systems (such as telecommunication systems) are presented with reference to various equipment and methods. These equipment and methods are described in this section and illustrated in the accompanying drawings by various blocks, components, circuits, processes, call flows, systems, algorithms, etc. (collectively referred to as "elements"). These elements may be implemented using electronic hardware, computer software, or a combination thereof. Whether such elements are implemented as hardware or software depends on the specific application and design constraints imposed on the overall system.

[0120] Elements, or any part of elements or any combination of elements can be implemented as a "processing system" including one or more processors. Examples of processors include microprocessors, microcontrollers, graphics processing units (GPUs), central processing units (CPUs), application processors, digital signal processors (DSPs), reduced instruction set computing (RISC) processors, systems on chip (SoCs), baseband processors, field programmable gate arrays (FPGAs), programmable logic devices (PLDs), state machines, gating logic, discrete hardware circuits, and other similar hardware configured to perform various functions described throughout this disclosure. One or more processors in a processing system can execute software, which can be referred to as software, firmware, middleware, microcode, hardware description language, or other. Software should be broadly interpreted as meaning instructions, instruction sets, codes, code segments, program codes, programs, subroutines, software components, applications, software applications, software packages, routines, subroutines, objects, executables, execution threads, processing, functions, or any combination thereof.

[0121] If the functions described herein are implemented in software, the functions may be stored on a computer-readable medium (such as a non-transitory computer-readable storage medium) or encoded as one or more instructions or codes on the computer-readable medium. Computer-readable media include computer storage media and may include random access memory (RAM), read-only memory (ROM), electrically erasable programmable ROM (EEPROM), optical disk storage, magnetic disk storage, other magnetic storage devices, combinations of these types of computer-readable media, or any other medium that can be used to store computer-executable code in the form of computer-accessible instructions or data structures. The storage medium can be any available medium that is accessible to a computer.

[0122] The aspects, implementations, and / or use cases described herein may be implemented across many different platform types, devices, systems, shapes, sizes, and packaging arrangements. For example, the aspects, implementations, and / or use cases may be generated via integrated chip implementations and other non-module component-based devices such as end-user devices, vehicles, communication devices, computing devices, industrial equipment, retail / procurement devices, medical devices, artificial intelligence (AI)-enabled devices, machine learning (ML)-enabled devices, and the like. The aspects, implementations, and / or use cases may range from chip-level or modular components to non-modular or non-chip-level implementations, and further to aggregated, distributed, or original equipment manufacturer (OEM) devices or systems incorporating one or more of the techniques described herein.

[0123] Devices incorporating the various aspects and features described herein may also include additional components and features for implementing and practicing the various aspects and features claimed and described. For example, the transmission and reception of wireless signals necessarily include many components for analog and digital purposes, such as hardware components, antennas, RF chains, power amplifiers, modulators, buffers, processors, interleavers, adders / summers, etc. The techniques described herein may be practiced in a wide variety of devices, chip-level components, systems, distributed arrangements, aggregated or disaggregated components, end-user devices, etc., in various configurations.

[0124] The description herein is provided to enable those skilled in the art to practice the various aspects described herein. Various modifications to these aspects will be apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects. Therefore, the claims are not limited to the various aspects described herein, but should be interpreted in view of the full scope of the disclosure consistent with the language of the claims.

[0125] Unless explicitly stated, references to singular elements do not mean "one and only one", but "one or more". Terms such as "if", "when ..." and "at ..." do not imply an immediate temporal relationship or reaction. That is, phrases such as "when ..." do not imply an immediate action in response to the occurrence of an action or during the occurrence of an action, but simply mean that if a certain condition is met, a certain action will occur, but no specific or immediate time constraints are required for the occurrence of the action. Unless explicitly stated otherwise, the term "some" refers to one or more. Combinations such as "at least one of A, B or C" or "one or more of A, B or C" include any combination of A, B and / or C, such as A and B, A and C, B and C, or A and B and C, and may include multiple A, multiple B and / or multiple C, or may include only A, only B or only C. A set should be interpreted as a set of elements in which the number of elements is one or more.

[0126] Unless expressly indicated otherwise, ordinal terms such as "first" and "second" do not necessarily imply an order in time, sequence, value, etc., but are used to distinguish different instances of the term or phrase following each ordinal term.

[0127] The structural equivalents and functional equivalents of the elements of various aspects described in the entire disclosure known or later learned by those of ordinary skill in the art are expressly incorporated herein by reference and are covered by the claims. The words "module", "mechanism", "element", "device", etc. may not be substitutes for the word "component". Therefore, unless the claim element is clearly stated using the phrase "component for...", any claim element shall not be interpreted as a means plus function. As used herein, the phrase "based on" should not be interpreted as a reference to a closed information set, one or more conditions, one or more factors, etc. In other words, unless clearly stated differently, the phrase "based on A" (where "A" can be information, conditions, factors, etc.) should be interpreted as "at least based on A".

[0128] The following examples are merely illustrative and may be combined with other examples or teachings described herein without limitation.

[0129] Example 1 is a method of wireless communication at a UE, comprising: receiving a configuration for a measurement report using a beam quality quantization process from a network entity, the measurement report comprising at least one of the following: a CSI report, an L1-RSRP report, or an L1-SINR report, each of which is based on beam measurement using one or more CSI-RS as a CMR; receiving one or more CSI-RS for beam measurement from the network entity; and sending a measurement report to the network entity, the measurement report being based on the beam measurement and the beam quality quantization process.

[0130] Example 2 may be combined with Example 1 and further include receiving control signaling triggering the measurement report from a network entity.

[0131] Example 3 may be combined with Example 2 and include the control signaling indicating a second parameter for a beam quality quantization process, the second parameter being different from a first parameter associated with the configuration.

[0132] Example 4 can be combined with any one of Examples 1 to 3, and further includes: sending a UE capability report to a network entity, the UE capability report indicating at least one of: a first capability of the UE to send reports for spatial domain beam prediction for an ML model; a first maximum number of CSI-RS resources, symbols of CSI-RS resources, or CSI-RS resource sets; a second maximum number of CSI-RS resources, symbols of CSI-RS resources, or CSI-RS resource sets for reporting in a time slot; a third maximum number of predicted beams in a report; a second capability of the UE receiver for reporting; or a minimum processing delay between a beam measurement by the UE receiver and a report based on the beam measurement by the UE receiver.

[0133] Example 5 can be combined with any one of Examples 1 to 4 and includes a configuration indicating at least one of the following: a reporting quantity parameter for reporting at least one of L1-RSRP, L1-SINR or BQI; a first threshold for the quality of beam measurement; a first indicator of the beam quality quantization process; a second indicator of the reported quantization mode; a quantization mode corresponding to a first absolute value of a beam set or a second absolute value of a subset of beams in the beam set and a differential value of the remaining beams in the beam set; a measurement accuracy indicator associated with a UE receiver; a differential time slot offset for a CSI-RS resource; an absolute time slot offset based on a CSI-RS resource; a first total number of repetitions of one or more CSI-RS; or a second number of repetitions of one or more CSI-RS in one time slot or multiple time slots.

[0134] Example 6 can be combined with any of Examples 1 to 5, and includes receiving one or more CSI-RS for beam measurement including at least one of the following: receiving repetitions of one or more CSI-RS from a network entity; or receiving one or more CSI-RS on CSI resources of one or more same antenna ports from a network entity.

[0135] Example 7 may be combined with any of Examples 1-6, and includes sending the measurement report including sending a first measurement value of L1-RSRP and a second measurement value of BQI for one or more CSI-RSs.

[0136] Example 8 may be combined with any one of Examples 1 to 6, and includes sending the measurement report including sending a CMR index and at least one of a first measurement value of L1-RSRP for the CMR, a second measurement value of BQI, or a third measurement value of L1-SINR.

[0137] Example 9 may be combined with Example 8 and include that the CMR index corresponds to a CSI-RS resource indicator or a CSI-RS resource set indicator.

[0138] Example 10 can be combined with Example 8 and includes that when the L1-SINR of all beams in the reported beam set is less than a second threshold, the value of the BQI is positive, and wherein when the L1-SINR of at least one beam subset in the reported beam set is greater than the second threshold, the value of the BQI is negative.

[0139] Example 11 may be combined with Example 8 and include at least one of a CMR index, a first measurement value of L1-RSRP, or a second measurement value of BQI being transmitted in at least one of CSI part 1 or CSI part 2.

[0140] Example 12 can be combined with any one of Examples 1 to 11, and include that the configuration includes a parameter that increases a resolution of a beam quality quantization process.

[0141] Example 13 is a method of wireless communication at a network entity, comprising: sending a configuration for a measurement report using a beam quality quantization process to a UE, the configuration directing the UE to include at least one of the following in the measurement report: a CSI report, an L1-RSRP report, or an L1-SINR report, each of which is based on one or more CSI-RS used as a CMR; sending one or more CSI-RS to the UE; and receiving a measurement report from the UE, the measurement report being based on the beam quality quantization process and the one or more CSI-RS.

[0142] Example 14 may be combined with Example 13, and further comprises sending control signaling to the UE to trigger a measurement report, the control signaling indicating a second parameter for a beam quality quantization process, the second parameter being different from a first parameter associated with the configuration.

[0143] Example 15 can be combined with any one of Examples 13 to 14, and further includes: receiving a UE capability report from the UE, the UE capability report indicating at least one of: a first capability of the UE to send reports for spatial domain beam prediction for an ML model; a first maximum number of CSI-RS resources, symbols of CSI-RS resources, or CSI-RS resource sets; a second maximum number of CSI-RS resources, symbols of CSI-RS resources, or CSI-RS resource sets for reporting in a time slot; a third maximum number of reported beams in a report; a second capability of the UE receiver for reporting; or a minimum processing delay based on the UE receiver performing beam measurements for the reports.

[0144] Example 16 may be combined with any of Examples 13 to 15, and includes sending one or more CSI-RS including at least one of: sending repetitions of one or more CSI-RS to the UE; or sending one or more CSI-RS on CSI resources associated with one or more of the same antenna ports of the UE to the UE.

[0145] Example 17 can be combined with any one of Examples 13 to 16, and further includes communicating with the UE based on the spatial domain beam prediction of the ML model, wherein the information included in the measurement report is used as input to the ML model to generate the spatial domain beam prediction.

[0146] Example 18 may be combined with Example 17 and include inputting information into the ML model to generate a spatial domain beam prediction when at least one of the following: the value of the BQI is positive or the L1-SINR of all beams in the reported beam set is greater than a threshold.

[0147] Example 19 is an apparatus for wireless communication for implementing a method as described in any one of Examples 1 to 18.

[0148] Example 20 is an apparatus for wireless communication including components for implementing the method as described in any of Examples 1 to 18.

[0149] Example 21 is a non-transitory computer readable medium storing computer executable code, which, when executed by a processor, causes the processor to implement the method as described in any one of Examples 1-18.

Claims

1. A method of wireless communication at a user equipment (UE), include: Receiving (308, 408) from a network entity a configuration for measurement reporting using a beam quality quantization procedure, the measurement reporting comprising at least one of: Channel State Information (CSI) reporting, Layer 1 Reference Signal Received Power (L1-RSRP) reporting, or Layer 1 signal to interference plus noise ratio (L1-SINR) reporting Each of the above reports is based on beam measurements using one or more channel state information reference signals (CSI-RS); receiving (312) the one or more CSI-RS for the beam measurement from the network entity; as well as The measurement report is sent (316, 416) to the network entity, the measurement report being based on the beam measurement and the beam quality quantization process.

2. The method of claim 1, further comprising: include: Control signaling triggering the measurement report is received (310) from the network entity.

3. The method of claim 2, wherein the control signaling indicates a second parameter for the beam quality quantization process, the second parameter being different from a first parameter associated with the configuration.

4. The method according to any one of claims 1 to 3, further comprising: include: A UE capability report is sent (306) to the network entity, the UE capability report indicating at least one of: a first capability of the UE to send a report of spatial domain beam prediction for a machine learning (ML) model, a first maximum number of CSI-RS resources, symbols of CSI-RS resources, or CSI-RS resource sets, a second maximum number of the CSI-RS resources, the symbols of the CSI-RS resources or the CSI-RS resource sets used for the report in a time slot, the third maximum number of predicted beams in the report, a second capability of the UE receiver for said reporting, or A minimum processing delay between the beam measurement by the UE receiver and a report based on the beam measurement by the UE receiver.

5. The method of any one of claims 1 to 4, wherein the configuration indicates at least one of: a reporting quantity parameter for reporting at least one of L1-RSRP, L1-SINR, or a beam quality indicator (BQI), a first threshold value of the quality of the beam measurement, a first indicator of the beam quality quantification process, a second indicator of a quantization mode of the report, a measurement accuracy indicator associated with a UE receiver, Differential slot offset for CSI-RS resources, The absolute time slot offset for the CSI-RS resource, a first total number of repetitions of the one or more CSI-RSs, or A second repetition number of the one or more CSI-RS in one time slot or multiple time slots.

6. The method of any one of claims 1 to 5, wherein the receiving the one or more CSI-RS for the beam measurement comprises at least one of: receiving a repetition of the one or more CSI-RS from the network entity, or The one or more CSI-RSs on CSI resources of more than one antenna port are received from the network entity.

7. The method according to any one of claims 1 to 6, wherein the sending of the measurement report include: A first measurement value of the L1-RSRP and a second measurement value of the BQI for the one or more CSI-RSs are transmitted.

8. The method according to any one of claims 1 to 6, wherein the sending of the measurement report include: A CMR index and at least one of a first measurement value of the L1-RSRP, a second measurement value of the BQI, or a third measurement value of the L1-SINR for the CMR are transmitted.

9. The method of claim 8, wherein the CMR index corresponds to a CSI-RS resource indicator or a CSI-RS resource set indicator.

10. The method of claim 8, wherein the value of the BQI is positive when the L1-SINR of all beams in the reported beam set is less than a second threshold, and wherein the value of the BQI is negative when the L1-SINR of at least one beam subset in the reported beam set is greater than the second threshold.

11. The method of claim 8, wherein at least one of the CMR index, the first measurement value of the L1-RSRP, or the second measurement value of the BQI is transmitted in at least one of CSI part 1 or CSI part 2.

12. The method of any one of claims 1 to 11, wherein the configuration comprises parameters that increase the resolution of the beam quality quantization process.

13. A method of wireless communication at a network entity, include: A configuration for measurement reporting using a beam quality quantization procedure is sent (308, 408) to a user equipment (UE), the configuration directing the UE to include in the measurement report at least one of: Channel State Information (CSI) reporting, Layer 1 Reference Signal Received Power (L1-RSRP) reporting, or Layer 1 signal to interference plus noise ratio (L1-SINR) reporting Each of the above reports is based on one or more channel state information reference signals (CSI-RS); sending (312) the one or more CSI-RS to the UE; as well as The measurement report is received (316, 416) from the UE, the measurement report being based on the beam quality quantization process and the one or more CSI-RSs.

14. The method of claim 13, further comprising: include: Control signaling is sent (310) to the UE to trigger the measurement report, the control signaling indicating a second parameter of the beam quality quantization process, the second parameter being different from a first parameter associated with the configuration.

15. The method according to any one of claims 13 to 14, further comprising: include: A UE capability report is received (306) from the UE, the UE capability report indicating at least one of: a first capability of the UE to send a report of spatial domain beam prediction for a machine learning (ML) model, a first maximum number of CSI-RS resources, symbols of CSI-RS resources, or CSI-RS resource sets, a second maximum number of the CSI-RS resources, the symbols of the CSI-RS resources or the CSI-RS resource sets used for the report in a time slot, the third maximum number of reported beams in the report, a second capability of the UE receiver for said reporting, or Based on a minimum processing delay for the UE receiver to perform beam measurements for the report.

16. The method of any one of claims 13 to 15, wherein the sending the one or more CSI-RS comprises at least one of: sending a repetition of the one or more CSI-RS to the UE, or The one or more CSI-RS on CSI resources associated with more than one antenna port of the UE are transmitted to the UE.

17. The method of any one of claims 13 to 16, further comprising: include: The spatial domain beam prediction based on the ML model is communicated with the UE, wherein information included in the measurement report is used as an input to the ML model to generate the spatial domain beam prediction.

18. The method of claim 17, wherein the information is input to the ML model to generate the spatial domain beam prediction when at least one of the following: a beam quality indicator (BQI) value is positive or the L1-SINR of all beams in the reported beam set is greater than a threshold.

19. An apparatus for wireless communication, comprising a transceiver, a memory and a processor, the processor being coupled to the memory and the transceiver, the apparatus being configured to implement the method according to any one of claims 1 to 18.

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