Sensor-assisted antenna and beam selection for wireless communications

Abstract

The present disclosure relates to sensor-assisted antenna and beam selection for wireless communications. A wireless device is configured to select a beam and / or antenna based on a detected position and / or orientation of the device relative to a remote device. The device obtains motion data indicating a change in the position or orientation of the wireless device. The device determines its pose relative to the remote device. The device accesses, for each of a plurality of poses of the device relative to the remote device, coverage associated with an antenna for communicating with the remote device and / or a beam for communicating with the remote device. The device selects a particular antenna and / or a particular beam for communicating with the remote device; and causes data to be transmitted to or received from the remote device via the particular antenna and / or the particular beam.

Description

[0001] Priority claim

[0002] This application claims priority under 35 U.S.C. §119(e) to U.S. patent application serial number 63 / 135,503, filed on January 8, 2021, the entire contents of which are hereby incorporated by reference into this application. Technical Field

[0003] The present disclosure relates generally to wireless communications. Background Art

[0004] Wireless devices may include phased array antennas for transmitting and receiving signals to and from remote devices (e.g., in wireless networks). A phased array includes a computer-controlled antenna array that generates a radio beam that can be electronically directed in different directions without moving the antenna.

[0005] Beamforming or spatial filtering is a signal processing technique used in sensor arrays to transmit or receive directional signals. This is achieved by combining the elements in the antenna array in such a way that signals at specific angles experience constructive interference while other signals experience destructive interference. Beamforming can be used on both the transmitting and receiving sides (e.g., through phased array antennas) to achieve spatial selectivity. Beamforming allows mmWave devices to steer radio frequency (RF) energy in a specific direction, thereby overcoming mmWave propagation losses. The beams are typically fixed and designed a priori in a codebook, such as phase-amplitude combinations of antenna elements. Summary of the Invention

[0006] This application describes systems and methods for beam selection for sensor-assisted antennas and wireless networks. Typically, wireless networks include transmissions using the millimeter wave (mm wave) spectrum. For example, the mm wave spectrum can be used in fifth generation (5G) and / or long term evolution (LTE) networks for transmissions in mm wave frequency ranges (e.g., frequency range 2 (FR2), frequency range 3 (FR3), etc.) from base stations (e.g., next generation nodes (gNBs)) or to and from client devices (e.g., mobile devices described throughout this specification). Typically, FR2 transmissions are between 24.25 GHz and 52.6 GHz. Typically, mm wave high bandwidth (e.g., approximately 400 MHz) transmissions have relatively high propagation losses. For example, mm wave transmissions may have a loss of 20 dB relative to frequency bands below 6 GHz, such as those used for frequency range 1 (FR1) transmissions.

[0007] To overcome this loss, the mmWave-enabled devices described herein are configured to perform beamforming, beam management, and antenna selection based on sensor feedback from one or more sensors of the mmWave-enabled device. Beamforming enables a device to steer radio frequency (RF) energy in a specific direction. The transmitting device forms a beam by varying the amplitude and / or phase of one or more elements of a phased array antenna. Typically, the transmitting device generates a beam based on a predefined phase-amplitude combination for each antenna of the array to ensure that a relatively high-power narrow beam is transmitted in the desired direction relative to the phased array antenna. Beam management enables the device to identify the beam to be used for transmission in each of the uplink and downlink directions. Antenna selection enables mmWave-enabled devices (e.g., user equipment (UE)) to ensure high-speed connectivity by improving the wireless coverage of a given uplink or downlink transmission. Systems and methods for sensor-assisted antenna and beam selection are configured to use feedback from sensors on mmWave-enabled devices to optimize beamforming, beam management, and antenna selection, thereby mitigating propagation losses, improving the efficiency of beam determination with respect to time and / or resources, and improving link performance.

[0008] Sensors on mmWave-enabled devices are configured to provide data indicating how the device moves in the environment. The motion data from the sensors enables the device to estimate beamforming parameters and antenna selection for optimal connectivity based on previous data indicating strong signals. This allows the device to estimate the optimal parameters for determining antenna selection without having to perform a full scan of possible beams and antennas to test various combinations of beams and antennas for optimal performance. As a result, the device can quickly identify likely candidates for relatively high-performance connectivity without the bandwidth overhead of performing a scan of beam and antenna combinations.

[0009] The systems and methods described in this document can achieve one or more of the following advantages. The systems and methods are configured to immediately (or almost immediately) identify the best beam and antenna panel for a UE with relatively low scanning overhead. Typically, beam and antenna selection algorithms are configured to identify the best beam and antenna panel settings at runtime. However, beam selection and antenna selection can result in relatively high scanning transmission overhead. For example, a mmWave device may be equipped with multiple antenna panels (e.g., three or more). Each antenna supports dozens of beams. Therefore, scanning each available beam for each antenna panel may take tens of milliseconds, which adds excessive overhead to the network. This is particularly prohibitive for augmented reality / virtual reality (AR / VR) applications with 1 to 2 millisecond latency requirements. Frequent beam and antenna scanning is not optimally practical for wireless devices. Methods and systems for sensor-assisted antenna and beam selection enable beam and antenna selection using a reduced scanning frequency, thereby reducing network overhead (and thereby reducing communication latency).

[0010] Methods and systems for sensor-assisted antenna and beam selection enable a UE or other similar device to overcome changes in the UE's environment and allow for increased UE mobility (which may represent changes in the UE's environment). For example, a device using mmWave communications may frequently adjust beam and antenna selection in response to physical changes in the device's environment (e.g., a moving car or trees) or movement of the device. Changes in the environment may cause obstructions in the UE's communication path or changes in the location of a remote device (e.g., a node) communicating with the UE. This may cause the UE and / or node to frequently adjust its beam to achieve better performance of the communication link. Methods and systems for sensor-assisted antenna and beam selection enable mmWave devices in the environment to quickly (e.g., immediately or almost immediately) determine optimal beam selection and / or antenna selection (when applicable) to improve the performance of the communication link in response to these environmental changes and / or movement of one or both of the communicating devices.

[0011] One or more of the advantages described previously may be achieved by one or more embodiments.

[0012] In a general aspect, a method includes obtaining motion data from one or more motion sensors coupled to a wireless device, the motion data indicating a change in the position or orientation of the wireless device. The method includes determining a pose of the wireless device relative to a remote device based on the motion data. The method includes selecting, for each of a plurality of poses of the wireless device relative to the remote device, a specific antenna or a specific beam for communicating with the remote device based on a coverage map associated with: an antenna for communicating with the remote device; a beam for communicating with the remote device; or both an antenna and a beam configuration for communicating with the remote device. The method includes transmitting data to the remote device or receiving data from the remote device via the specific antenna or the specific beam.

[0013] In one embodiment, the method includes determining an initial pose of the wireless device relative to the remote device using angle of arrival (AoA) data, wherein the pose of the wireless device relative to the remote device is based on motion data indicating a change in position or orientation of the wireless device from the initial pose.

[0014] In one embodiment, the motion data indicates a change in position or orientation of the wireless device over a period of time. The method includes: determining that one or more metrics of a communication channel between the wireless device and a remote device fail to meet one or more corresponding thresholds; responsive to the determination, identifying an angle of arrival (AoA) value of a strongest signal from the remote device; and identifying, from a coverage area, a specific beam and a specific antenna associated with the AoA value in the coverage area.

[0015] In one embodiment, the one or more metrics include at least one of a signal-to-noise ratio (SNR) of a signal received from the remote device, a delay spread value of the signal, and a variance value of the AoA of the signal.

[0016] In one embodiment, the coverage range indicates that a particular antenna and a particular beam represent the highest gain for enabling transmission of data to a remote device or reception of additional data from a remote device.

[0017] In one embodiment, the one or more motion sensors include at least an accelerometer, a gyroscope, or both an accelerometer and a gyroscope.

[0018] In one embodiment, the wireless device and the remote device are configured for mm-wave communications using Frequency Range 2 (FR2).

[0019] In one embodiment, selecting a particular antenna and a particular beam for communicating with a remote device is performed with a delay of less than 2 milliseconds.

[0020] In one embodiment, the method includes periodically retrieving motion data to determine whether the wireless device is moving or stationary.

[0021] In one embodiment, the wireless device includes at least three antenna arrays, and wherein each antenna array includes at least 10 beam configurations.

[0022] In one embodiment, determining a pose of the wireless device relative to the remote device based on the motion data includes determining that one or more of translational motion or rotational motion of the wireless device exceeds a motion threshold; and accessing a coverage range in response to determining that the motion threshold is exceeded.

[0023] In one embodiment, the method includes comparing a change in the position or orientation of the wireless device to a threshold change value; and in response to the comparison, accessing a coverage area when the change exceeds the threshold.

[0024] In one embodiment, the method includes detecting that a signal strength received from a remote device is below a threshold signal strength; and in response to the detecting, obtaining activity data.

[0025] In one embodiment, the method includes selecting a specific antenna and / or a specific beam for communicating with the remote device based on coverage; and causing data to be transmitted to or received from the remote device via the specific antenna and the specific beam.

[0026] In a general aspect, a wireless device includes: at least one motion sensor; one or more antenna arrays, each antenna array configured for at least two beam configurations; one or more processors; and a non-transitory computer-readable storage medium storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations. In one embodiment, the operations include obtaining motion data from the at least one motion sensor, the motion data indicating a change in a position or orientation of the wireless device. In one embodiment, the operations include determining a pose of the wireless device relative to a remote device based on the motion data. In one embodiment, the operations include selecting, for each of a plurality of poses of the wireless device relative to the remote device, a particular antenna and a particular beam for communicating with the remote device based on coverage associated with: an antenna array in the one or more antenna arrays for communicating with the remote device; a beam for communicating with the remote device; or both an antenna and a beam for communicating with the remote device. In one embodiment, the operations include transmitting data to the remote device via the particular antenna and the particular beam.

[0027] In one embodiment, the operations include determining an initial pose of the wireless device relative to the remote device using angle of arrival (AoA) data, wherein the pose of the wireless device relative to the remote device is based on motion data indicating a change in position or orientation of the wireless device from the initial pose.

[0028] In one embodiment, the motion data indicates that the position or orientation of the wireless device has not changed over a period of time, and the operations further include: determining that one or more metrics of a communication channel between the wireless device and a remote device fail to satisfy one or more corresponding thresholds; in response to the determination, identifying an angle of arrival (AoA) value of the strongest signal from the remote device; and identifying, from a coverage area, a specific beam and a specific antenna associated with the AoA value in the coverage area.

[0029] In one embodiment, the one or more metrics include at least one of a signal-to-noise ratio (SNR) of the signal from the remote device, a delay spread value of the signal, and a variance value of the AoA of the signal.

[0030] In one embodiment, the coverage range indicates that a particular antenna and a particular beam represent the highest gain for enabling transmission of data to a remote device or reception of additional data from a remote device.

[0031] In one embodiment, the one or more motion sensors include at least an accelerometer, a gyroscope, or both an accelerometer and a gyroscope.

[0032] In one embodiment, the wireless device and the remote device are configured for mm-wave communications using Frequency Range 2 (FR2).

[0033] In one embodiment, the operations include comparing a change in the position or orientation of the wireless device to a threshold change value; and in response to the comparison, accessing coverage when the change exceeds the threshold.

[0034] In one embodiment, the operations include detecting that a signal strength received from a remote device is below a threshold signal strength; and in response to the detecting, obtaining activity data.

[0035] In one embodiment, these operations include selecting a particular antenna and / or a particular beam for communicating with the remote device based on coverage; and causing data to be transmitted to or received from the remote device via the particular antenna and the particular beam.

[0036] The details of one or more specific implementations are set forth in the following figures and description. The techniques described herein may be implemented by one or more wireless communication systems, components of wireless communication systems (e.g., stations, access points, user equipment, base stations, etc.), or other systems, devices, methods, or non-transitory computer-readable media. Additional features and advantages will be apparent from the detailed description and drawings, as well as from the claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 An exemplary wireless communication system according to various embodiments herein is shown.

[0038] Figure 2 An example of a platform or device configured for sensor-assisted antenna and beam selection according to some implementations of the present disclosure is shown.

[0039] Figure 3 An exemplary device configured for multi-user triggered based wireless communication according to some implementations of the present disclosure is shown.

[0040] Figures 4A to 4C Examples are shown for selecting coverage of one or more of antennas and beams according to some implementations of the present disclosure.

[0041] Figure 5 Examples of selecting one or more of an antenna and a beam based on sensor feedback are shown according to some implementations of the present disclosure.

[0042] Figure 6 Examples of selecting one or more of an antenna and a beam based on sensor feedback are shown according to some implementations of the present disclosure.

[0043] Figure 7 Example methods for configuring parameters of beam selection, beams, or both based on sensor feedback are shown, according to some implementations of the present disclosure.

[0044] Like reference symbols in the various drawings indicate like elements. DETAILED DESCRIPTION

[0045] The techniques described herein enable a wireless device to perform beam selection, antenna selection, or both beam and antenna selection in response to changes in the channel of a communication link. A device includes one or more sensors that provide motion data to the device. The device is configured to perform beamforming, select an antenna for transmission, or both perform beamforming and select an antenna for transmission in response to receiving the motion data. This enables the device to perform beamforming and antenna selection to improve communication performance using less bandwidth overhead and less latency than performing a full beam scan of the device's antennas.

[0046] Typically, beam and antenna selection is performed to improve communication bandwidth in the context of mmWave systems (e.g., using FR2 frequencies, FR3 frequencies, or other mmWave frequencies). mmWave communication links have relatively high propagation losses over long distances (e.g., over tens or hundreds of meters) relative to the losses of FR1 links. To mitigate propagation losses and improve the performance of the communication link, mmWave-enabled devices are configured to perform beamforming, beam management, and antenna selection based on sensor feedback from one or more sensors of the mmWave-enabled device.

[0047] Beamforming enables a device to steer radio frequency (RF) energy in a specific direction. Transmitting devices form a beam by varying the amplitude and / or phase of one or more elements of a phased array antenna. Typically, the transmitting device generates a beam based on a predefined phase-amplitude combination for each antenna in the array to ensure a relatively high-power, narrow beam is transmitted in the desired direction relative to the phased array antenna.

[0048] Beam management enables the device to identify the beam to use for transmission in each of the uplink and downlink directions. In one example, for 5G NR mmWave transmissions, a node (e.g., a gNB) periodically (e.g., between 5 milliseconds and 160 milliseconds (monitoring system) period) transmits a synchronization signal to identify the best transmit beam and the best receive beam. This includes an initial beam training step using multiple beams. In this first step, a wider beam width is used to cover a wide sweep range. The second step includes a beam refinement step. In this step, the UE sweeps a narrower beam over a narrower range than in the first step. This enables the UE to adjust in the desired beam direction. In the third step, the device is configured for beam refinement. In the beam refinement step, the user equipment (UE) tunes the receive angle of the beam, and the node transmits using a fixed beam. The UE measures different signal strengths until the optimal configuration of beams is found. In one example, for 802.11ad / ay mmWave transmissions, an access point (AP) and a wireless device (e.g., UE) train their respective beams during sector-level scanning (SLS) and beam refinement procedure (BRP), as defined in the 802.11 standard.

[0049] Antenna selection enables a device (e.g., a UE) to ensure high-speed connectivity by improving the wireless coverage for a given uplink or downlink transmission. In one example, blocking of the first antenna or antenna misalignment can result in reduced throughput relative to an ideal transmission environment. In this case, the UE is configured to select from multiple phased antenna arrays (also known as antenna panels).

[0050] An mmWave-enabled device includes one or more sensors configured to provide motion data. The motion data indicates how the device moves in an environment. The motion data from the sensors enables the device to estimate beamforming parameters and antenna selection for optimal connectivity based on previous data indicating strong signals. This allows the device to estimate optimal parameters for beamforming and antenna selection without having to perform a comprehensive scan of possible beams and antennas to test various beam and antenna combinations for optimal performance. Consequently, the device can quickly identify potential candidates for relatively high-performance connectivity without the bandwidth overhead of performing a scan of beam and antenna combinations. For example, if an mmWave-enabled device (e.g., a UE) is rotated 180 degrees, the system can estimate that the beamforming direction may be 180 degrees from the previous direction that determined optimal transmission performance. Additional examples of this method are described below with respect to the accompanying figures. The described system and method are compatible with any mmWave technology (e.g., 802.11ad / ay, 5G, etc.). The system is lightweight and configured to select beams, antennas, or both independently of any antenna or beam scanning.

[0051] Figure 1 An exemplary wireless communication system 100 is shown. For convenience and not limitation, the exemplary system 100 is described in the context of LTE and 5G NR communication standards defined by the 3rd Generation Partnership Project (3GPP) technical specifications. More specifically, the wireless communication system 100 is described in the context of a non-standalone (NSA) network that combines both LTE and NR, such as an E-UTRA (Evolved Universal Terrestrial Radio Access)-NR Dual Connectivity (EN-DC) network and a NE-DC network. However, the wireless communication system 100 may also be a standalone (SA) network that only combines NR. In addition, other types of communication standards are also possible, including future 3GPP systems (e.g., sixth generation (6G) systems), IEEE 802.16 protocols (e.g., WMAN, WiMAX, etc.), and the like.

[0052] System 100 includes UE 101a and UE 101b (collectively, "UE 101"). In this example, UE 101 is shown as a smartphone (eg, a handheld, touchscreen mobile computing device that can connect to one or more cellular networks). In other examples, any of the plurality of UEs 101 may include other mobile computing devices or non-mobile computing devices, such as consumer electronic devices, cellular phones, smart phones, feature phones, tablet computers, wearable computer devices, personal digital assistants (PDAs), pagers, wireless handheld devices, desktop computers, laptop computers, in-vehicle infotainment (IVI), in-car entertainment (ICE) devices, instrument clusters (ICs), heads-up display (HUD) devices, on-board diagnostic (OBD) devices, on-board mobility equipment (DME), mobile data terminals (MDTs), electronic engine management systems (EEMS), electronic / engine control units (ECUs), electronic / engine control modules (ECMs), embedded systems, microcontrollers, control modules, engine management systems (EMS), connected or “smart” appliances, machine type communication (MTC) devices, machine-to-machine (M2M) devices, Internet of Things (IoT) devices, or combinations thereof, etc.

[0053] In some examples, any of the plurality of UEs 101 may be an IoT UE, which may include a network access layer designed for low-power IoT applications utilizing short-term UE connections. The IoT UE may utilize technologies such as M2M or MTC to exchange data with an MTC server or device using, for example, a public land mobile network (PLMN), proximity services (ProSe), device-to-device (D2D) communications, sensor networks, IoT networks, or a combination thereof. M2M or MTC data exchanges may be machine-initiated data exchanges. The IoT network describes interconnected IoT UEs, which may include uniquely identifiable embedded computing devices (within the Internet infrastructure) with short-term connections. The IoT UE may execute background applications (e.g., keep-alive messages or status updates) to facilitate connectivity to the IoT network.

[0054] UE 101 is configured to connect (e.g., be communicatively coupled) to an access network (AN) or radio access network (RAN) 110. In some examples, RAN 110 can be a next-generation RAN (NG RAN), an evolved UMTS terrestrial radio access network (E-UTRAN), or a legacy RAN, such as a UMTS terrestrial radio access network (UTRAN) or a GSM EDGE radio access network (GERAN). As used herein, the term "NG RAN" can refer to the RAN 110 operating in a 5G NR system 100, while the term "E-UTRAN" can refer to the RAN 110 operating in an LTE or 4G system 100.

[0055] To connect to the RAN 110, multiple UEs 101 utilize connections (or channels) 103 and 104, respectively, each of which may include a physical communication interface or layer, as described below. In this example, connections 103 and 104 are shown as air interfaces to achieve communication coupling and can be consistent with cellular communication protocols, such as the Global System for Mobile Communications (GSM) protocol, the Code Division Multiple Access (CDMA) network protocol, the Push-to-Talk (PTT) protocol, the Cellular PTT (POC) protocol, the Universal Mobile Telecommunications System (UMTS) protocol, the 3GPP LTE protocol, the 5G NR protocol, or a combination thereof, as well as other communication protocols. In some examples, multiple UEs 101 can use an interface 105 such as a ProSe interface to directly exchange communication data. The interface 105 may alternatively be referred to as a sidelink interface 105 and may include one or more logical channels, such as a physical sidelink control channel (PSCCH), a physical sidelink shared channel (PSSCH), a physical sidelink downlink channel (PSDCH), or a physical sidelink broadcast channel (PSBCH), or a combination thereof.

[0056] UE 101b is shown configured to access access point (AP) 106 (also referred to as "WLAN node 106," "WLAN 106," "WLAN termination 106," "WT 106," etc.) using connection 107. Connection 107 may include a local wireless connection, such as a connection consistent with any IEEE 802.11 protocol, wherein AP 106 may include Wireless Fidelity. Router. In this example, AP 106 is shown connected to the Internet without being connected to the core network of the wireless system, as described in further detail below. In various examples, UE 101b, RAN 110, and AP 106 can be configured to use LTE-WLAN aggregation (LWA) operation or LTE / WLAN radio level operation integrated with IPsec tunneling (LWIP). LWA operation may involve RAN nodes 111a, 111b configuring UE 101b in an RRC_CONNECTED state to utilize radio resources of LTE and WLAN. LWIP operation may involve UE 101b using IPsec protocol tunneling to use WLAN radio resources (e.g., connection 107) to authenticate and encrypt packets (e.g., IP packets) sent over connection 107. IPsec tunneling may include encapsulating the entire original IP packet and adding a new packet header, thereby protecting the original header of the IP packet.

[0057] The RAN 110 includes one or more AN nodes or RAN nodes 111a and 111b (collectively referred to as "RAN nodes 111") that enable connections 103 and 104. As used herein, the terms "access node," "access point," and the like may describe equipment that provides radio baseband functionality for data or voice connections, or both, between a network and one or more users. These access nodes may be referred to as base stations (BSs), gNodeBs, gNBs, eNodeBs, eNBs, NodeBs, RAN nodes, roadside units (RSUs), transmit receive points (TRxPs or TRPs), and the like, and may include ground stations (e.g., terrestrial access points) or satellite stations that provide coverage within a geographic area (e.g., a cell). As used herein, the terms "NG RAN nodes" and the like may refer to RAN nodes 111 (e.g., gNBs) operating in a 5G NR system 100, while the term "E-UTRAN nodes" and the like may refer to RAN nodes 111 (e.g., eNBs) operating in an LTE or 4G system 100. In some examples, multiple RAN nodes 111 may be implemented as one or more dedicated physical devices such as macrocell base stations or low-power (LP) base stations for providing femtocells, picocells, or other similar cells with smaller coverage areas, smaller user capacity, or higher bandwidth than macrocells.

[0058] In some examples, some or all of the multiple RAN nodes 111 may be implemented as one or more software entities running on a server computer as part of a virtual network that may be referred to as a cloud RAN (CRAN) or a virtual baseband unit pool (vBBUP). The CRAN or vBBUP may implement RAN functional splits such as a packet data convergence protocol (PDCP) split, where the radio resource control (RRC) and PDCP layers are operated by the CRAN / vBBUP, and other layer 2 (e.g., data link layer) protocol entities are operated by individual RAN nodes 111; a medium access control (MAC) / physical layer (PHY) split, where the RRC, PDCP, MAC, and radio link control (RLC) layers are operated by the CRAN / vBBUP, and the PHY layer is operated by individual RAN nodes 111; or a "lower PHY" split, where the RRC, PDCP, RLC, and MAC layers, as well as the upper portion of the PHY layer, are operated by the CRAN / vBBUP, and the lower portion of the PHY layer is operated by individual RAN nodes 111. The virtualization framework allows idle processor cores of the RAN node 111 to execute, for example, other virtualized applications. In some examples, a separate RAN node 111 may represent a separate processor core using individual F1 interfaces ( Figure 1 In some examples, the gNB-DU may include one or more remote radio heads or RFEMs (see, e.g., Figure 2 ), and the gNB-CU may be operated by a server (not shown) located in RAN 110 or by a server pool in a manner similar to CRAN / vBBUP. Additionally or alternatively, one or more of the RAN nodes 111 may be next-generation eNBs (ng-eNBs), including RAN nodes that provide E-UTRA user plane and control plane protocol terminations to UE 101 and connect to a 5G core network (e.g., core network 120) using a next-generation interface.

[0059] In vehicle-to-everything (V2X) scenarios, one or more of the RAN nodes 111 may be or function as an RSU. The term "roadside unit" or "RSU" refers to any traffic infrastructure entity used for V2X communications. An RSU may be implemented in or by a suitable RAN node or a stationary (or relatively stationary) UE. An RSU implemented in or by a UE may be referred to as a "UE-type RSU," an RSU implemented in or by an eNB may be referred to as an "eNB-type RSU," an RSU implemented in or by a gNB may be referred to as a "gNB-type RSU," and so on. In some examples, an RSU is a computing device coupled to RF circuitry located on the roadside that provides connectivity support to passing vehicle UEs 101 (vUEs 101). The RSU may also include internal data storage circuitry for storing intersection map geometry, traffic statistics, media, and applications or other software used to sense and control ongoing vehicular and pedestrian traffic. The RSU may operate on the 5.9 GHz Direct Short Range Communication (DSRC) band to provide extremely low latency communications required for high-speed events, such as collision avoidance, traffic warnings, and the like. Additionally or alternatively, the RSU may operate on the cellular V2X band to provide the aforementioned low latency communications as well as other cellular communication services. Additionally or alternatively, the RSU may operate as a Wi-Fi hotspot (2.4 GHz band) or provide connectivity to one or more cellular networks to provide uplink and downlink communications, or both. Some or all of the computing device and the RSU's RF circuitry may be encapsulated in a weatherproof enclosure suitable for outdoor installation, and may include a network interface controller to provide a wired connection (e.g., Ethernet) to a traffic signal controller or a backhaul network, or both.

[0060] Any one of the RAN nodes 111 may serve as the endpoint for the air interface protocol and may be the first point of contact for the UE 101. In some examples, any one of the multiple RAN nodes 111 may perform various logical functions of the RAN 110, including but not limited to functions of a radio network controller (RNC), such as radio bearer management, uplink and downlink dynamic radio resource management and data packet scheduling, and mobility management.

[0061] In some examples, multiple UEs 101 can be configured to communicate with each other or with any of multiple RAN nodes 111 using orthogonal frequency division multiplexing (OFDM) communication signals over a multi-carrier communication channel in accordance with various communication techniques, such as, but not limited to, OFDMA communication techniques (e.g., for downlink communication) or SC-FDMA communication techniques (e.g., for uplink and ProSe or sidelink communication), although the scope of the techniques described herein is not limited in this respect. The OFDM signal can include multiple orthogonal subcarriers.

[0062] In some examples, a downlink resource grid can be used for downlink transmissions from any of multiple RAN nodes 111 to multiple UEs 101, while uplink transmissions can utilize similar techniques. The grid can be a time-frequency grid, referred to as a resource grid or time-frequency resource grid, which represents the physical resources in the downlink during each time slot. This type of time-frequency plane representation is common for OFDM systems, making radio resource allocation intuitive. Each column and row of the resource grid corresponds to an OFDM symbol and an OFDM subcarrier, respectively. The duration of the resource grid in the time domain corresponds to a time slot in a radio frame. The smallest time-frequency unit in the resource grid is represented as a resource element. Each resource grid includes multiple resource blocks, which describe the mapping of certain physical channels to resource elements. Each resource block includes a collection of resource elements; in the frequency domain, this can represent the minimum amount of resources that can currently be allocated. Such resource blocks are used to transmit several different physical downlink channels.

[0063] In some examples, multiple UEs 101 and multiple RAN nodes 111 communicate (e.g., transmit and receive) data over a licensed medium (also referred to as a "licensed spectrum" or "licensed band") and an unlicensed shared medium (also referred to as an "unlicensed spectrum" and / or "unlicensed band"). The licensed spectrum may include channels operating in a frequency range of approximately 400 MHz to approximately 3.8 GHz, while the unlicensed spectrum may include a 5 GHz band. NR in unlicensed spectrum may be referred to as NR-U, and LTE in unlicensed spectrum may be referred to as LTE-U, License Assisted Access (LAA), or MulteFire.

[0064] Figure 2An example of a platform 300 (or "device 300") is shown. In some examples, computer platform 300 may be suitable for use as UE 101 or any other component or device discussed herein. Platform 300 may include any combination of the components shown in the examples. Components of platform 300 (or portions thereof) may be implemented as integrated circuits (ICs), discrete electronic devices, or other modules, logic, hardware, software, firmware, or combinations thereof that fit within computer platform 300, or as components that are otherwise incorporated within the chassis of a larger system. Figure 2 The block diagram is intended to show a high-level view of the components of platform 300. However, in some examples, platform 300 may include fewer, additional, or alternative components, or include Figure 2 Different arrangements of components are shown.

[0065] The data processing device 302 includes circuitry such as, but not limited to, one or more processors (or processor cores), cache memory, and one or more of: an LDO, an interrupt controller, a serial interface (such as SPI), an I2C or general programmable serial interface module, an RTC, a timer-counter (including an interval timer and a watchdog timer), general I / O, a memory card controller (such as an SD MMC or similar controller), a USB interface, a MIPI interface, and a JTAG test access port. The processor (or core) of the data processing device 302 may be coupled to or may include a memory / storage element and may be configured to execute instructions stored in the memory or storage device to enable various applications or operating systems to run on the system 300. In some examples, the memory or storage element may be an on-chip memory circuit, which may include any suitable volatile or non-volatile memory, such as DRAM, SRAM, EPROM, EEPROM, flash memory, solid-state memory, or a combination thereof.

[0066] The processor of the data processing device 302 may include, for example, one or more processor cores, one or more application processors, one or more GPUs, one or more RISC processors, one or more ARM processors, one or more CISC processors, one or more DSPs, one or more FPGAs, one or more PLDs, one or more ASICs, one or more microprocessors or controllers, a multi-threaded processor, an ultra-low voltage processor, an embedded processor, some other known processing element, or any suitable combination thereof. In some examples, the data processing device 302 may include or may be a dedicated processor / controller for performing the techniques described herein.

[0067] As an example, the processor of the data processing device 302 may include an Apple A series processor. The processor of the data processing device 302 may also be one or more of the following: Architecture Core TM Processors such as Quark TM 、Atom TM , i3, i5, i7 or MCU class processors, or available from Santa Clara, CA company( Another such processor is from Intel Corporation, Santa Clara, CA; Advanced Micro Devices (AMD) Processor or Accelerated Processing Unit (APU); from Technologies, Inc.'s Snapdragon TM processors, Texas Instruments, Open Multimedia ApplicationsPlatform(OMAP) TM processors; MIPS-based designs from MIPS Technologies, Inc., such as the MIPS Warrior M-class, Warrior I-class, and Warrior P-class processors; ARM-based designs licensed from ARM Holdings, Ltd., such as the ARM Cortex-A, Cortex-R, and Cortex-M series processors; etc. In some implementations, the data processing device 302 may be part of a system on a chip (SoC), in which the data processing device 302 and other components are formed as a single integrated circuit.

[0068] Additionally or alternatively, the data processing device 302 may include circuitry such as, but not limited to, one or more field programmable devices (FPDs) such as FPGAs; programmable logic devices (PLDs) such as complex PLDs (CPLDs) or high-capacity PLDs (HCPLDs); ASICs such as structured ASICs; programmable SoCs (PSoCs); or combinations thereof. In some examples, the data processing device 302 may include logic blocks or logic fabrics, as well as other interconnected resources that can be programmed to perform various functions, such as the processes, methods, and functions described herein. In some examples, the data processing device 302 may include memory units (e.g., erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory, static memory (e.g., static random access memory (SRAM), or antifuse)) for storing the logic blocks, logic fabrics, data, or other data in a lookup table (LUT).

[0069] Baseband circuit 310310 can be implemented as, for example, a solder-in substrate including one or more integrated circuits, a single packaged integrated circuit soldered to a main circuit board, or a multi-chip module containing two or more integrated circuits.

[0070] The antenna beam panel 312 (also referred to as a radio front end module (RFEM)) may include a millimeter wave (mm wave) RFEM and one or more sub-mm wave radio frequency integrated circuits (RFICs). In some examples, the one or more sub-mm wave RFICs may be physically separate from the mm wave antenna beam panel 312. These RFICs may include connections to one or more antennas or antenna arrays, and the antenna beam panel 312 may be connected to multiple antennas. In some examples, both mm wave and sub-mm wave radio functionality may be implemented in the same physical antenna beam panel 312 that combines both mm wave antennas and sub-mm wave antennas. In some embodiments, the mm wave functionality implements the IEEE 802.11ad and 802.11ay standards.

[0071] Platform 300 may also include an interface circuit (not shown) for connecting external devices to platform 300. External devices connected to platform 300 using the interface circuit include sensor circuit 221 and electromechanical component (EMC) 222, as well as a removable memory device coupled to removable memory circuit 223.

[0072] Sensor circuitry 304 includes a device, module, or subsystem whose purpose is to detect events or changes in its environment and to send information about the detected events (e.g., sensor data) to one or more other devices, modules, or subsystems. Examples of such sensors include: an inertial measurement unit (IMU), such as an accelerometer, gyroscope, or magnetometer; a microelectromechanical system (MEMS) or nanoelectromechanical system (NEMS) including a three-axis accelerometer, a three-axis gyroscope, or a magnetometer; a liquid level sensor; a flow sensor; a temperature sensor (e.g., a thermistor); a pressure sensor; a barometric pressure sensor; a gravity meter; an altimeter; an image capture device (e.g., a camera or lensless aperture); a light detection and ranging (LiDAR) sensor; a proximity sensor (e.g., an infrared radiation detector, etc.), a depth sensor, an ambient light sensor, an ultrasonic transceiver; a microphone or other audio capture device, or a combination thereof, and the like.

[0073] System 300 includes one or more motion sensors 304. Sensors 304 are configured to generate motion data that indicates how the UE moves in an environment (e.g., relative to a remote device communicating with the UE). As previously described, sensors 304 may include one or more accelerometers, one or more gyroscopes, and / or other sensing elements. Figure 3 These sensors are described further below. As the pose of system 300 changes within the system environment, sensors 304 capture the motion of the system and send the motion data to motion detection module 306.

[0074] The data processing device 302 is configured to host a motion detection module 306 and a coverage module 308. The motion detection module 306 is configured to determine how the device is moving in the environment from the motion data of the sensor 304. The motion detection module 306 can determine the new position and orientation (e.g., pose) of the device relative to the previous pose of the device for which the optimal beam and antenna were selected. The updated pose can be provided to the coverage module 308.

[0075] The coverage module 308 is configured to select the beams and antennas of the panel 312 for transmitting or receiving data by the system 300 based on the updated pose provided by the motion detection module 306. The selection of the beams and antennas includes selecting a specific configuration of the phased antenna array to generate a directional beam from the array panel. In one example, the data processing device 302 continuously or nearly continuously performs the selection process as the device moves in the environment. In some embodiments, the data processing device 302 uses the coverage module 308 to perform the selection process when the motion detection module 306 detects motion. In some embodiments, the data processing device 302 uses the coverage module 308 to perform the selection process when performance drops below a threshold (e.g., when obstruction is detected).

[0076] Typically, the data processing device 302 is configured to identify antennas and beams in use that are performing poorly (e.g., below a performance threshold). For example, signal strength, bandwidth, or other link metrics (e.g., retrieved from baseband feedback from the baseband module 310) are associated with thresholds. When the value of the metric fails to meet the threshold, the data processing device 302 is configured to identify and select a different optimal antenna and beam for both transmission and reception without requiring scanning overhead (e.g., without scanning some or all available antenna panels and beams). In some embodiments, the data processing device 302 is configured to determine that the current antenna or beam (or both) will perform poorly in the future (e.g., within tens of milliseconds). The data processing device 302 is configured to predict such performance degradation and switch to an antenna, beam, or both that is not expected to experience similar performance degradation.

[0077] System 300 receives input from each of sensors 304 and baseband module 310. Baseband (BB) feedback may include signal-to-noise ratio (SNR), delay spread, angle of arrival (AoA), and similar link metrics. Data processing device 302 uses feedback data available from wireless baseband module 310 to infer the orientation of the dominant wireless path. The dominant wireless path comprises the path of a signal from a transmitter to a receiver. Data processing device 302 uses baseband module 310 feedback data to identify whether the antenna panel, beam, or both being used are optimal. Typically, if AoA data is not available to system 300, the AoA is estimated by data processing device 302.

[0078] In short, turn Figure 3 , devices 400 and 410 are shown by Figure 24. Examples of data collected by sensors 304 of device 400. For example, device 400 includes gyroscopes 402a, 402b, and 402c. Gyroscope 402 is configured to measure the rate at which device 400 rotates around a spatial axis, including pitch, roll, and yaw, and movement (e.g., in degrees or radians) of device 400. Similarly, accelerometers 412a, 412b, and 412c of device 410 are configured to measure changes in velocity of device 410 along the x, y, and z axes (e.g., translational motion). Devices 400 and 410 can be combined into a single device that includes both gyroscopes 402a-c and accelerometers 412a-c.

[0079] return Figure 2 , the motion detection module 306 receives the accelerometer motion data and identifies translational movement along each of the x, y, and z axes (e.g., in centimeters). The motion detection module 306 receives the gyroscope motion data and determines the rotation of the device about each of the x, y, and z axes. The result is an updated pose of the system 300 relative to the previous pose of the system. The initial pose of the system is determined relative to the remote device connected by the communication link. The initial pose can be determined based on AoA data (e.g., from the BB panel 310). In some specific implementations, if AoA data is not available, a one-time beam scan is performed to determine the AoA, as described subsequently. The motion detection module 306 sends the motion data to the coverage module 308 configured for antenna selection, beam selection, or both. The coverage module 308 determines whether the change in pose is significant enough to cause a beam or antenna panel switch to occur.

[0080] The coverage module 308 performs the selection of antennas, beams, or both based on data from the BB panel 310 and the updated pose provided by the motion detection module 306. Because the beam radiation patterns and antenna positions are predefined for a given device (e.g., a device of the system 300), the coverage module 308 includes coverage data. The coverage data includes the highest gain antenna panel and beam identification for each available device orientation and position.

[0081] The coverage module 308 generally selects a new antenna or beam based on two scenarios. The first scenario is a blocking scenario, where non-line-of-sight (NLOS) occurs between the system 300 and the remote device. The second scenario is a mobility scenario, where mobile device movement (e.g., movement of the system or remote device) causes misalignment of the antenna or beam, or both.

[0082] In a blocked scenario, the coverage module 308 detects that the connection is unstable. This may occur when one or more communication metrics (e.g., measured by the baseband feedback panel 310) fail to meet a threshold. Typically, a wireless channel is more stable in a LOS environment than in a blocked / NLOS environment. When the channel stability is low, an NLOS setting or scenario may exist, and beam or antenna switching (or both) may improve the channel stability. The data processing device 302 determines the channel stability using the following metrics. The data processing device 302 determines that the channel stability is low by measuring the SNR drop and contextualizing the drop using a standard deviation value associated with the SNR. Blockage typically results in a significant initial SNR drop and a subsequent high SNR deviation. The data processing device 302 determines that the channel stability is low by measuring the delay spread of the signal. The delay spread in an NLOS / blocked setting is typically higher than in an LOS setting. The data processing device 302 determines that the channel stability is low by measuring the AoA change. When the wireless LOS path between two devices is blocked, the AoA of the wireless dominant path typically changes. In one example, the strongest path of the beam may become a reflected path rather than a direct path to the remote device, as subsequently measured with respect to the signal. Figure 6 As stated.

[0083] In some embodiments, the SNR or delay spread value may increase, and the AoA may change due to mobility rather than obstruction. System 300 is configured to distinguish between obstruction and mobility scenarios by examining motion data from sensor 304. When the sensor indicates that system 300 is static, it is determined to be a blocking scenario. In some embodiments, thresholds for SNR deviation, delay spread, or any other channel metric are determined by training a model before runtime (e.g., using a machine learning (ML) or similar model). For example, a machine learning model can be trained with data including various values ​​of the metric to classify a signal from a remote device as blocked or unblocked for each of various combinations of values. The machine learning model can be used to determine appropriate thresholds for each of the one or more metrics to ensure that the characterization of blocked or unblocked signals represents the correct scenario.

[0084] In a mobile scenario, the coverage module 308 is configured to determine a new antenna or beam (or both) for the system 300 based on the updated pose provided by the motion detection module 306. The change in pose is determined based on the known pose of the system 300 relative to the remote device. The known pose can be determined (e.g., once) using BB feedback data (such as the AoA of the signal). Typically, this can be determined based on the location in the antenna array where the highest received power exists. For example, the position associated with the highest power can be provided. The system typically associates the determined AoA with the peak beam of the remote transmitter. In other words, the estimated strongest lobe is located at the location of the determined AoA. Based on the motion data and the AoA, an updated pose is determined and a new position within the coverage area is selected, as described later. Based on the position within the coverage area, a specific antenna and beam of panel 312 is selected for transmitting and / or receiving data in the communication link with the remote device.

[0085] As previously described, the system 300 uses baseband feedback to identify the current orientation of the dominant / strongest wireless path to the remote device. When the direction of the wireless path remains the same and the device moves, the data processing device 302 uses the motion data to identify the extent of the motion (e.g., in degrees). The data processing device 302 is configured to reference the current dominant signal path orientation and motion to determine a new wireless path orientation and position (e.g., pose). The data processing device 302 uses coverage to identify the optimal antenna array panel and beam for the updated pose. In a mobility LOS scenario, the orientation of the dominant path remains the same, while the system 300 orientation changes. The data processing device 302 is configured to obtain (or estimate) the wireless dominant path Using the motion data, the coverage module 306 identifies that the system 300 has moved The coverage module 306 is configured to periodically (e.g., every 10 milliseconds (ms)) acquire gyroscope motion data (e.g., roll, pitch, and yaw). Δ represents the difference between the current pose and the previous pose value. When the dominant path orientation remains the same between these two iterations (a typical scenario), the dominant path corresponds to the device pose P' = P + Δ. When the updated device pose P' is aligned with an antenna panel or beam other than the antenna panel or beam in use, the coverage module 306 is configured to cause the system 300 to use the new antenna panel and beam 312.

[0086] To determine the initial system 300 pose (e.g., orientation and position) relative to the remote device, the data processing device 302 determines or estimates the AoA of the transmission from the remote device. In some implementations, the AoA is provided by the receive baseband hardware 310. In some implementations, the data processing device 302 estimates the AoA from a channel matrix of signal metrics. For example, the data processing device 302 considers the peak of the active beam to represent the orientation of the dominant channel path and, therefore, the current orientation in the beam coverage. When multiple peaks are found, the data processing device 302 uses the centroid of the peaks to estimate the AoA. The direction of the dominant radio path represents the orientation of the peak beam gain. As previously described, the AoA can be provided by the baseband module 310 or estimated from the channel matrix, such as by using a high-resolution direction finding algorithm (e.g., a multiple signal classification algorithm) based on the eigenvalue decomposition of the sensor covariance matrix observed at the phased array.

[0087] Figures 4A to 4C An example of coverage areas 500a, 500b, 500c (collectively, coverage areas 500) for selecting one or more of antennas and beams according to some implementations of the present disclosure is shown. Figure 2 The coverage module 308 is pre-loaded with coverage 500. Coverage 500 specifies a specific antenna for each specific AoA of the signal and a specific beam for that antenna to optimize the channel. For example, coverage 500 can be calculated before runtime to identify the best antenna and beam for the base station's antenna at different device orientations.

[0088] Coverage 500 is defined as a set of entries for each location. For example, a vector such as [phi, theta, best_antenna, best_beam] can represent the angle of each best antenna and best beam. Figure 4A The coverage 500a is shown only for angles θ and The optimal antenna array for , but a set of ranges is used for each other pose value and each beam of each antenna. Coverage module 308 can quickly (e.g., within 1 ms) reference the ranges and does not need to scan all available beams and antenna arrays of system 300. In coverage 500a, each angle θ and In one example, coverage 500 includes beam and antenna selection for both rotational and translational motion of motion data.

[0089] The coverage area 500 provides identification of the optimal antenna panels and beams based on the beam radiation patterns. The data processing device 302 uses this data in conjunction with a determination of the wireless multipath environment (e.g., the azimuth and elevation directions of the wireless paths) to identify which beams are best "aligned" with the wireless dominant path. Because the beam radiation patterns and antenna positions for a particular device (e.g., a mobile device) are known prior to runtime, the coverage area can be predefined to represent the highest gain antenna panels and beams for a given system 300 orientation relative to the remote device. As previously described, the data processing device 302 estimates or reads from hardware the AoA of the wireless dominant path and identifies from the coverage area 500 the antenna / beam that is best aligned with that AoA.

[0090] exist Figure 4A , coverage 500A shows a given value of θ and θ of a mobile device (eg, system 300) relative to a remote device (eg, a base station). Antenna selection (pitch and roll). Based on received or estimated AoA data, the initial orientation of the mobile device is found to be approximately = 90, corresponding to block 502. Here, antenna 3 is selected 508 as the best antenna. A similar coverage area (not shown) details the best beam for antenna 3 for this orientation.

[0091] Go to Figure 4B , coverage 500b shows the coverage of a mobile device (eg, system 300) relative to a remote device (eg, base station) for a given value of θ and (pitch and roll) antenna selection. Here, the system 300 has changed its orientation along Rotate to The value of θ and the other positions and orientations are static. The coverage area shifts from block 502 to block 504. Block 504 indicates (508) that antenna 1 is the best antenna for that orientation. A similar coverage area (not shown) details the best beam for antenna 1 for that orientation. Since the pose at 502 is known, the data processing device 302 does not need to estimate the AoA to select the best beam or antenna.

[0092] Go to Figure 4C , coverage 500c shows the coverage of a mobile device (eg, system 300) relative to a remote device (eg, base station) for a given value of θ and Here, the system 300 has changed its orientation and rotated along θ to a value of θ = 180, while The coverage area shifts from block 504 to block 506. Block 506 indicates (508) that either antenna 1 or antenna 3 may be the best antenna for that orientation. A similar coverage area (not shown) details the best beam for antenna 1 and the best beam for antenna 3 for that orientation.

[0093] Figure 5 An example of an environment 600 for selecting one or more of an antenna and a beam based on sensor feedback by a mobile device 602 is shown in accordance with some embodiments of the present disclosure. Figure 5 In exemplary environment 600, a mobile device (e.g., a mobile phone) is in a first orientation 610 relative to a remote device 604 (e.g., a gNB). Based on a full beam scan, device 602 identifies the optimal beam for antenna 2 for receiving signals. Mobile device 602 also determines the AoA. When mobile device 602 flips 180 degrees, it detects motion from a gyroscope coupled to the mobile device. Although the position is static, the orientation has changed, and thus mobile device 602 detects a motion scene rather than an obstructed scene. Based on the motion data, mobile device 602 determines an updated pose value. Using the coverage area, mobile device 602 determines that antenna 1 is now the optimal antenna and selects a beam from antenna 1 for the communication link with remote device 604. Mobile device 602 selects the new beam and antenna without performing another scan of the mobile device's antennas and beams. Mobile device 602 switches from antenna 2 to antenna 1 with low latency (e.g., less than 1 ms) and without the bandwidth overhead of beam scanning.

[0094] Figure 6An example environment 700 is shown for selecting one or more of an antenna and a beam by a mobile device 702 based on sensor feedback, according to some embodiments of the present disclosure. In this example, a mobile device (e.g., a UE) 702 is communicating with a remote device 708 (e.g., a gNB). Mobile device 702 is stationary. First beam 710a of antenna 2 is initially used to communicate with remote device 708 based on beam scanning. Despite no motion, mobile device 702 detects that the performance of the link is degraded. For example, there may be a drop in SNR, an increase in delay spread, or a change in AoA, as previously described. This may be the result of an obstruction 704, such as a person moving between mobile device 702 and remote device 708 during communication. As a result, the main lobe of the transmitted signal of remote device 708 is blocked. In response to detecting a change in the value of a communication metric and also in response to detecting no motion, mobile device 702 finds an alternative beam 710b based on a secondary lobe of the transmitted signal. The secondary lobe is reflected from an object 706 in the environment of device 702. The AoA indicates the strongest signal strength from different locations. Mobile device 702 associates the AoA of the strongest signal with a location in the coverage area and selects beam 710b of antenna 2 accordingly.

[0095] Figure 7 Example methods for configuring parameters of beam selection, beams, or both based on sensor feedback according to some implementations of the present disclosure are shown. In some examples, Figures 1 to 6 An electronic device, network, system, chip or component, or a portion or specific implementation thereof, may be configured to perform method 800. Method 800 includes receiving a synchronization signal at a wireless device from a remote device. Method 800 includes, in response to receiving the synchronization signal, obtaining (804) motion data from one or more motion sensors coupled to the wireless device, the motion data indicating a change in the position or orientation of the wireless device. Method 800 includes determining (806) a pose of the wireless device relative to the remote device based on the motion data. Method 800 includes accessing (808) coverage associated with: an antenna for communicating with the remote device; a beam for communicating with the remote device; or both an antenna and beam configuration for communicating with the remote device for each of a plurality of poses of the wireless device relative to the remote device. Method 800 includes selecting (810) a particular antenna and / or a particular beam for communicating with the remote device. Method 800 includes causing (812) data to be transmitted to the remote device via the particular antenna and the particular beam.

[0096] In some embodiments, method 800 includes determining an initial pose of the wireless device relative to the remote device using angle of arrival (AoA) data. The pose of the wireless device relative to the remote device is based on motion data indicating a change in position or orientation of the wireless device from the initial pose.

[0097] In some embodiments, the motion data indicates a change in the position or orientation of the wireless device over a period of time. Method 800 includes determining that one or more metrics of a communication channel between the wireless device and a remote device fail to meet one or more corresponding thresholds. Method 800 includes, in response to the determination, identifying an angle of arrival (AoA) value of a strongest signal from the remote device. Method 800 includes identifying, from a coverage area, a specific beam and a specific antenna associated with the AoA value in the coverage area.

[0098] In some embodiments, the one or more metrics include at least one of a signal-to-noise ratio (SNR) of the synchronization signal, a delay spread value of the synchronization signal, and a variation value of the AoA of the synchronization signal.

[0099] In some embodiments, method 800 includes selecting the one or more respective thresholds by applying training data representing values ​​of the one or more metrics to a machine learning model. The machine learning model is configured to classify a synchronization signal as blocked or unblocked.

[0100] In some embodiments, the coverage range indicates that a particular antenna and a particular beam represent the highest gain for enabling transmission of data to a remote device or reception of additional data from a remote device.

[0101] In some embodiments, the one or more sensors include at least an accelerometer, a gyroscope, or both an accelerometer and a gyroscope.

[0102] In some embodiments, the wireless device and the remote device are configured for mm-wave communications using Frequency Range 2 (FR2).

[0103] In some embodiments, selecting a particular antenna and a particular beam for communicating with a remote device is performed with a delay of less than 2 milliseconds.

[0104] In some embodiments, method 800 includes periodically retrieving motion data to determine whether the wireless device is moving or stationary.

[0105] In some embodiments, the wireless device includes at least three antenna arrays, and wherein each antenna array includes at least 10 beam configurations.

[0106] In some embodiments, determining a pose of the wireless device relative to the remote device based on the motion data includes determining that one or more of translational motion or rotational motion of the wireless device exceeds a motion threshold. Method 800 includes accessing a coverage area in response to determining that the motion threshold is exceeded.

[0107] It is understood that the use of personally identifiable information should be subject to privacy policies and practices that are generally recognized to meet or exceed industry or government requirements for maintaining user privacy. Specifically, personally identifiable information data should be managed and processed to minimize the risk of unintentional or unauthorized access or use, and the nature of authorized use should be clearly stated to users.

[0108] The specific implementation of the subject matter and functional operations described in this specification may be implemented in digital electronic circuits, in tangibly embodied computer software or firmware, in computer hardware (including the structures disclosed in this specification and their structural equivalents), or in a combination of one or more thereof. The software implementation of the subject matter may be implemented as one or more computer programs. Each computer program may include one or more modules of computer program instructions encoded on a tangible, non-transitory computer-readable computer storage medium for execution by a data processing device or for controlling the operation of the data processing device. Alternatively or additionally, the program instructions may be encoded in / on an artificially generated propagation signal. In one example, the signal may be a machine-generated electrical, optical, or electromagnetic signal that is generated to encode information for transmission to a suitable receiver device for execution by a data processing device. The computer storage medium may be a combination of a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a computer storage medium.

[0109] The terms "data processing apparatus," "computer," and "computing device" (or equivalents as understood by those of ordinary skill in the art) refer to data processing hardware. For example, a data processing apparatus may encompass various apparatuses, devices, and machines for processing data, including, for example, a programmable processor, a computer, or multiple processors or computers. The apparatus may also include a dedicated logic circuit, including, for example, a central processing unit (CPU), a field programmable gate array (FPGA), or an application-specific integrated circuit (ASIC). In some specific implementations, the data processing apparatus or dedicated logic circuit (or a combination of data processing apparatus or dedicated logic circuit) may be based on hardware or software (or a combination of hardware and software). The apparatus may optionally include code that creates an execution environment for a computer program, such as code that constitutes a processor firmware, a protocol stack, a database management system, an operating system, or a combination of execution environments. The present disclosure contemplates the use of a data processing apparatus with or without a conventional operating system (e.g., LINUX, UNIX, WINDOWS, MAC OS, ANTROL, or IOS).

[0110] A computer program, which may also be referred to or described as a program, software, software application, module, software module, script, or code, may be written in any form of programming language. Programming languages ​​may include, for example, compiled languages, interpreted languages, declarative languages, or procedural languages. A program may be deployed in any form, including as a standalone program, module, component, subroutine, or unit for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. A program may be stored in a portion of a file that stores other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files that store one or more modules, subroutines, or code portions. A computer program may be deployed to execute on a single computer or on multiple computers located at, for example, a single site or distributed across multiple sites interconnected by a communication network. Although portions of the program shown in the various figures may be illustrated as separate modules that implement various features and functions through various objects, methods, or processes, the program may alternatively include multiple submodules, third-party services, components, and libraries. Conversely, the features and functions of various components may be combined into a single component as appropriate. The threshold used to perform the computational determination may be determined statically, dynamically, or both statically and dynamically.

[0111] The methods, processes, or logic flows described herein may be performed by one or more programmable computers executing one or more computer programs to perform functions by operating on input data and generating output. These methods, processes, and logic flows may also be performed by, and apparatus may be implemented as, special purpose logic circuitry (e.g., a CPU, FPGA, or ASIC).

[0112] The computer that is suitable for executing computer programs can be based on one or more of a general-purpose microprocessor and a special-purpose microprocessor and other types of CPU. The element of a computer is a CPU for executing instructions and one or more memory devices for storing instructions and data. Generally speaking, the CPU can receive instructions and data (and write data to the memory) from the memory. The computer may also include or be operably coupled to one or more mass storage devices for storing data. In some specific implementations, the computer may receive data from the mass storage device and transfer data to the mass storage device, and these mass storage devices include, for example, magnetic disks, magneto-optical disks or optical disks. In addition, the computer may be embedded in another device, such as a mobile phone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a global positioning system (GPS) receiver or a portable storage device such as a universal serial bus (USB) flash drive.

[0113] Computer-readable media (transitory or non-transitory, as the case may be) suitable for storing computer program instructions and data can include all forms of permanent / non-permanent and volatile / non-volatile memory, media and memory devices. Computer-readable media can include, for example, semiconductor memory devices such as random access memory (RAM), read-only memory (ROM), phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM) and flash memory devices. Computer-readable media can also include, for example, magnetic devices such as magnetic tapes, cassettes, cartridges and internal / removable disks. Computer-readable media can also include magneto-optical and optical memory devices and technologies, including, for example, digital video discs (DVDs), CDROMs, DVD+ / -Rs, DVD-RAMs, DVD-ROMs, HD-DVDs and BLURAYs. Memory can store a variety of objects or data, including caches, classes, frameworks, applications, modules, backup data, jobs, web pages, web page templates, data structures, database tables, repositories and dynamic information. The types of objects and data stored in memory may include parameters, variables, algorithms, instructions, rules, constraints, and references. Additionally, memory may include logs, policies, security or access data, and report files. The processor and memory may be supplemented by, or incorporated into, special-purpose logic circuitry.

[0114] Although this specification contains many specific implementation details, these details should not be construed as limitations on the scope of what is claimed, but rather as descriptions of features that may be unique to a particular implementation. Certain features described in this specification in the context of different implementations may also be implemented in combination in a single implementation. Conversely, various features described in the context of a single implementation may also be implemented in multiple implementations, either individually or in any suitable subcombination. Furthermore, although previously described features may be described as functioning in certain combinations and even initially claimed as such, one or more features in a claimed combination may, in some cases, be removed from that combination, and a claimed combination may involve subcombinations or variations of subcombinations.

[0115] Specific implementations of the subject matter have been described. Other implementations, modifications, and permutations of the described implementations are within the scope of the following claims and will be apparent to those skilled in the art. Although operations are shown in a particular order in the drawings or claims, this should not be construed as requiring that such operations be performed in the particular order shown or in a sequential order, or that all shown operations (some operations may be considered optional) be performed to achieve the desired result. In some cases, multitasking or parallel processing (or a combination of multitasking and parallel processing) may be advantageous and may be performed as appropriate.

[0116] In addition, the division or integration of various system modules and components in the previously described specific implementations should not be understood as requiring such division or integration in all specific implementations, and it should be understood that the program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

[0117] Therefore, the exemplary embodiments described above do not limit or restrict the present disclosure. Other changes, substitutions and modifications are also possible without departing from the scope of the present disclosure.

[0118] Example

[0119] Embodiment 1 includes a method comprising: obtaining motion data from one or more motion sensors coupled to a wireless device, the motion data indicating a change in a position or orientation of the wireless device; determining a posture of the wireless device relative to a remote device based on the motion data; selecting, for each of a plurality of postures of the wireless device relative to the remote device, a specific antenna or a specific beam for communicating with the remote device based on a coverage range associated with: an antenna for communicating with the remote device; a beam for communicating with the remote device; or both the antenna and the beam configuration for communicating with the remote device; and causing data to be transmitted to or received from the remote device via the specific antenna or the specific beam.

[0120] Embodiment 2 may include embodiment 1 and further include determining an initial pose of the wireless device relative to the remote device using angle of arrival (AoA) data, wherein the pose of the wireless device relative to the remote device is based on the motion data indicating a change in the position or the orientation of the wireless device from the initial pose.

[0121] Embodiment 3 includes any one of embodiments 1 to 2, wherein the motion data indicates that the position or the orientation of the wireless device has not changed over a period of time, and wherein the method further comprises: determining that one or more metrics of the communication channel between the wireless device and the remote device fail to satisfy one or more corresponding thresholds; in response to the determination, identifying an angle of arrival (AoA) value of the strongest signal from the remote device; and identifying, from the coverage area, the specific beam and the specific antenna associated with the AoA value in the coverage area.

[0122] Embodiment 4 may include any one of embodiments 1 to 3, wherein the one or more metrics include at least one of a signal-to-noise ratio (SNR) of a signal received from the remote device, a delay spread value of the signal, and a variation value of the AoA of the signal.

[0123] Embodiment 5 may include any of embodiments 1-4, wherein the coverage range indicates that the particular antenna and the particular beam represent a highest gain for enabling transmission of data to the remote device or reception of additional data from the remote device.

[0124] Embodiment 6 may include any of Embodiments 1 to 5, wherein the one or more motion sensors include at least an accelerometer, a gyroscope, or both the accelerometer and the gyroscope.

[0125] Embodiment 7 may include any of embodiments 1-6, wherein the wireless device and the remote device are configured for mm-wave communication using frequency range 2 (FR2).

[0126] Embodiment 8 may include any of embodiments 1-7, wherein selecting the particular antenna and the particular beam for communicating with the remote device is performed with a delay of less than 2 milliseconds.

[0127] Embodiment 9 may include any of embodiments 1-8, further comprising periodically retrieving motion data to determine whether the wireless device is moving or stationary.

[0128] Embodiment 10 may include any one of embodiments 1 to 9, wherein the wireless device includes at least three antenna arrays, and wherein each antenna array includes at least 10 beam configurations.

[0129] Embodiment 11 may include any one of embodiments 1 to 10, wherein determining the posture of the wireless device relative to the remote device based on the motion data includes: determining that one or more of the translational motion or rotational motion of the wireless device exceeds a motion threshold; and accessing the coverage range in response to determining that the motion threshold is exceeded.

[0130] Embodiment 12 may include any one of embodiments 1 to 11, further comprising: comparing the change in the position or the orientation of the wireless device to a threshold change value; and in response to the comparison, accessing the coverage range when the change exceeds the threshold.

[0131] Embodiment 13 may include any of embodiments 1 to 12, further comprising: detecting that a signal strength received from the remote device is below a threshold signal strength; and obtaining the activity data in response to the detecting.

[0132] Embodiment 14 may include any one of embodiments 1 to 13, and further include: selecting a specific antenna and / or a specific beam for communicating with the remote device based on the coverage range; and transmitting data to the remote device and receiving data from the remote device via the specific antenna or the specific beam.

[0133] Embodiment 15 includes a wireless device comprising: at least one motion sensor; one or more antenna arrays, each antenna array being configured for at least two beam configurations; one or more processors; and a non-transitory computer-readable storage medium storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: obtaining motion data from the at least one motion sensor, the motion data indicating a change in the position or orientation of the wireless device; determining a change in the posture of the wireless device relative to a remote device based on the motion data; selecting, for each of a plurality of postures of the wireless device relative to the remote device, a specific antenna and a specific beam for communicating with the remote device based on coverage associated with: an antenna array from the one or more antenna arrays for communicating with the remote device; a beam for communicating with the remote device; or both the antenna and the beam for communicating with the remote device; and causing data to be transmitted to the remote device via the specific antenna and the specific beam.

[0134] Embodiment 16 may include embodiment 15, wherein the operation further comprises determining an initial pose of the wireless device relative to the remote device using angle of arrival (AoA) data, wherein the pose of the wireless device relative to the remote device is based on the motion data indicating a change in the position or the orientation of the wireless device from the initial pose.

[0135] Embodiment 17 may include any one of embodiments 15 to 16, wherein the motion data indicates that the position or the orientation of the wireless device has not changed over a period of time, and wherein the operation further comprises: determining that one or more metrics of the communication channel between the wireless device and the remote device fail to satisfy one or more corresponding thresholds; in response to the determination, identifying an angle of arrival (AoA) value of the strongest signal from the remote device; and identifying, from the coverage area, the specific beam and the specific antenna associated with the AoA value in the coverage area.

[0136] Embodiment 18 may include any one of embodiments 15 to 17, wherein the one or more metrics include at least one of a signal-to-noise ratio (SNR) of a signal from the remote device, a delay spread value of the signal, and a variation value of the AoA of the signal.

[0137] Embodiment 19 may include any of Embodiments 15 to 18, wherein the coverage indication that the particular antenna and the particular beam represent a highest gain for enabling transmission of data to the remote device or reception of additional data from the remote device.

[0138] Embodiment 20 may include any one of Embodiments 15 to 19, wherein the one or more motion sensors include at least an accelerometer, a gyroscope, or both the accelerometer and the gyroscope.

[0139] Embodiment 21 may include any of Embodiments 15 to 20, wherein the wireless device and the remote device are configured for mm-wave communication using Frequency Range 2 (FR2).

[0140] Embodiment 22 may include any one of embodiments 15 to 21, the operation further comprising: comparing the change in the position or the orientation of the wireless device to a threshold change value; and in response to the comparison, accessing the coverage range when the change exceeds the threshold.

[0141] Embodiment 23 may include any of Embodiments 15 to 22, the operations further comprising: detecting that a signal strength received from the remote device is below a threshold signal strength; and obtaining the activity data in response to the detecting.

[0142] Embodiment 24 may include any one of embodiments 15 to 23, and the operation further includes: selecting a specific antenna and / or a specific beam for communicating with the remote device based on the coverage range; and transmitting data to the remote device and receiving data from the remote device through the specific antenna or the specific beam.

[0143] Embodiment 25 may include a processor for a user equipment (UE), the processor comprising: a circuit configured for communicating with a remote device; and a circuit for executing one or more instructions, which, when executed, cause the processor to perform operations including: obtaining motion data from one or more motion sensors coupled to a wireless device, the motion data indicating a change in a position or orientation of the wireless device; determining a posture of the wireless device relative to the remote device based on the motion data; selecting, for each of a plurality of postures of the wireless device relative to the remote device, a specific antenna or a specific beam for communicating with the remote device based on a coverage range associated with: an antenna for communicating with the remote device; a beam for communicating with the remote device; or both the antenna and the beam configuration for communicating with the remote device; and causing data to be transmitted to or received from the remote device via the specific antenna or the specific beam.

[0144] Embodiment 26 may include embodiment 25, the operation further comprising: determining an initial pose of the wireless device relative to the remote device using angle of arrival (AoA) data, wherein the pose of the wireless device relative to the remote device is based on the motion data indicating a change in the position or the orientation of the wireless device from the initial pose.

[0145] Embodiment 27 may include any of embodiments 25 to 26, wherein the motion data indicates that the position or the orientation of the wireless device has not changed over a period of time, and the operation further includes: determining that one or more metrics of the communication channel between the wireless device and the remote device fail to satisfy one or more corresponding thresholds; in response to the determination, identifying an angle of arrival (AoA) value of the strongest signal from the remote device; and identifying, from the coverage area, the specific beam and the specific antenna associated with the AoA value in the coverage area.

[0146] Embodiment 28 may include any one of embodiments 25 to 27, wherein the one or more metrics include at least one of a signal-to-noise ratio (SNR) of a signal received from the remote device, a delay spread value of the signal, and a variation value of the AoA of the signal.

[0147] Embodiment 29 may include any of Embodiments 25 to 28, wherein the coverage indication that the particular antenna and the particular beam represent a highest gain for enabling transmission of data to the remote device or reception of additional data from the remote device.

[0148] Embodiment 30 may include any one of Embodiments 25 to 29, wherein the one or more motion sensors include at least an accelerometer, a gyroscope, or both the accelerometer and the gyroscope.

[0149] Embodiment 31 may include any of Embodiments 25 to 30, wherein the wireless device and the remote device are configured for mm-wave communication using Frequency Range 2 (FR2).

[0150] Embodiment 32 may include any of Embodiments 25 to 31, wherein selecting the particular antenna and the particular beam for communicating with the remote device is performed with a delay of less than 2 milliseconds.

[0151] Embodiment 33 may include any of Embodiments 25 to 32, the operations further comprising periodically retrieving motion data to determine whether the wireless device is moving or stationary.

[0152] Embodiment 34 may include any of Embodiments 25 to 33, wherein the wireless device comprises at least three antenna arrays, and wherein each antenna array comprises at least 10 beam configurations.

[0153] Embodiment 35 may include any one of embodiments 25 to 34, wherein determining the posture of the wireless device relative to the remote device based on the motion data includes: determining that one or more of the translational motion or rotational motion of the wireless device exceeds a motion threshold; and accessing the coverage range in response to determining that the motion threshold is exceeded.

[0154] Embodiment 36 may include any one of embodiments 25 to 35, the operation further comprising: comparing the change in the position or the orientation of the wireless device with a threshold change value; and in response to the comparison, accessing the coverage range when the change exceeds the threshold.

[0155] Embodiment 37 may include any of Embodiments 25 to 36, the operations further comprising: detecting that a signal strength received from the remote device is below a threshold signal strength; and obtaining the activity data in response to the detecting.

[0156] Embodiment 38 may include any one of embodiments 25 to 37, and the operation further includes: selecting a specific antenna and / or a specific beam for communicating with the remote device based on the coverage range; and transmitting data to the remote device and receiving data from the remote device through the specific antenna or the specific beam.

[0157] Embodiment 39 may include signals as described in or related to any one of Embodiments 1 to 67, or portions or components thereof.

[0158] Embodiment 40 may include a datagram, information element, packet, frame, fragment, PDU or message, or a portion or component thereof, as described in or related to any of Embodiments 1 to 68 or otherwise described in this disclosure.

[0159] Embodiment 41 may include a signal encoded with data as described in or related to any of Embodiments 1 to 38 or otherwise described in this disclosure, or a portion or component thereof.

[0160] Embodiment 42 may include a signal encoded with a datagram, IE, packet, frame, segment, PDU, or message, or a portion or component thereof, as described in or related to any of Embodiments 1 to 38 or otherwise described in this disclosure.

[0161] Embodiment 43 may include an electromagnetic signal carrying computer-readable instructions, wherein execution of the computer-readable instructions by one or more processors will cause the one or more processors to perform a method, technique, or process, or portion thereof, as described or related to any one of Embodiments 1 to 38.

[0162] Embodiment 44 may include a computer program comprising instructions, wherein execution of the program by a processing element causes the processing element to perform a method, technique, or process, or portion thereof, as described or related to any one of Embodiments 1 to 38.

[0163] Embodiment 45 may include signals in a wireless network as shown and described herein.

[0164] Embodiment 46 may include a method of communicating in a wireless network as shown and described herein.

[0165] Embodiment 47 may include a system for providing wireless communications as shown and described herein.

[0166] Embodiment 48 may include an apparatus for providing wireless communications as shown and described herein.

Claims

1. A method for communication, comprising: Determine an initial pose of the wireless device relative to the remote device using the angle of arrival (AoA) data; obtaining motion data from one or more motion sensors coupled to the wireless device, the motion data indicating a change in position or orientation of the wireless device; determining a pose of the wireless device relative to the remote device based on the motion data, wherein the pose of the wireless device relative to the remote device is based on the motion data indicating a change in the position or the orientation of the wireless device from the initial pose; For each of a plurality of poses of the wireless device relative to the remote device, selecting a particular antenna or a particular beam for communicating with the remote device based on coverage associated with: an antenna for communicating with the remote device; a beam for communicating with the remote device; or both the antenna and beam configuration for communicating with the remote device; and Data is transmitted to or received from the remote device through the specific antenna or the specific beam.

2. The method of claim 1 , wherein the motion data indicates that the position or the orientation of the wireless device has not changed over a period of time, and wherein the method further comprises: determining that one or more metrics of a communication channel between the wireless device and the remote device fail to satisfy one or more corresponding thresholds; Responsive to the determining, identifying an angle of arrival (AoA) value for a strongest signal from the remote device; and The particular beam and the particular antenna associated with the AoA value in the coverage area are identified from the coverage area.

3. The method of claim 2, wherein the one or more metrics include at least one of a signal-to-noise ratio (SNR) of a signal received from the remote device, a delay spread value of the signal, and a variation value of the AoA of the signal. 4 . The method of claim 1 , wherein the coverage range indicates that the particular antenna and the particular beam represent the highest gain for enabling transmission of data to the remote device or reception of additional data from the remote device. The method of claim 1 , wherein the one or more motion sensors include at least an accelerometer, a gyroscope, or both the accelerometer and the gyroscope. 6 . The method of claim 1 , wherein the wireless device and the remote device are configured for mm-wave communication using frequency range 2FR2.

7. The method of claim 1, wherein selecting the particular antenna and the particular beam for communicating with the remote device is performed with a delay of less than 2 milliseconds.

8. The method of claim 1, further comprising periodically retrieving motion data to determine whether the wireless device is moving or stationary.

9. The method of claim 1, wherein the wireless device comprises at least three antenna arrays, and wherein each antenna array comprises at least 10 beam configurations.

10. The method of claim 1 , wherein determining the pose of the wireless device relative to the remote device based on the motion data comprises: determining that one or more of translational motion or rotational motion of the wireless device exceeds a motion threshold; as well as In response to determining that the motion threshold is exceeded, the coverage area is accessed.

11. The method according to claim 1 , further comprising: comparing the change in the position or the orientation of the wireless device to a threshold change value; as well as In response to the comparison, the coverage range is accessed when the change exceeds the threshold.

12. The method according to claim 1, further comprising: detecting that a signal strength received from the remote device is below a threshold signal strength; as well as In response to the detecting, the motion data is obtained.

13. The method according to claim 1, further comprising: selecting a particular antenna and / or a particular beam for communicating with the remote device based on the coverage area; as well as Data is transmitted to or received from the remote device through the specific antenna and the specific beam.

14. A wireless device comprising: at least one motion sensor; one or more antenna arrays, each antenna array configured for at least two beam configurations; one or more processors; and A non-transitory computer-readable storage medium storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: Determining an initial pose of the wireless device relative to a remote device using angle of arrival (AoA) data; obtaining motion data from the at least one motion sensor, the motion data indicating a change in position or orientation of the wireless device; determining a change in a pose of the wireless device relative to the remote device based on the motion data, wherein the pose of the wireless device relative to the remote device is based on the motion data indicating a change in the position or the orientation of the wireless device from the initial pose; For each of a plurality of poses of the wireless device relative to the remote device, selecting a particular antenna and a particular beam for communicating with the remote device based on coverage associated with: an antenna array of the one or more antenna arrays for communicating with the remote device; a beam for communicating with the remote device; or both the antenna and the beam for communicating with the remote device; and Data is caused to be transmitted to the remote device through the specific antenna and the specific beam.

15. The wireless device of claim 14, wherein the motion data indicates that the position or the orientation of the wireless device has not changed over a period of time, and wherein the operations further comprise: determining that one or more metrics of a communication channel between the wireless device and the remote device fail to satisfy one or more corresponding thresholds; Responsive to the determining, identifying an angle of arrival (AoA) value for a strongest signal from the remote device; and The particular beam and the particular antenna associated with the AoA value in the coverage area are identified from the coverage area.

16. The wireless device of claim 15, wherein the one or more metrics include at least one of a signal-to-noise ratio (SNR) of a signal from the remote device, a delay spread value of the signal, and a variation value of the AoA of the signal.

17. The wireless device of claim 14, wherein the coverage range indication that the particular antenna and the particular beam represent the highest gain for enabling transmission of data to the remote device or reception of additional data from the remote device.

18. The wireless device of claim 14, wherein the one or more motion sensors include at least an accelerometer, a gyroscope, or both the accelerometer and the gyroscope.

19. The wireless device of claim 14, wherein the wireless device and the remote device are configured for mm-wave communication using frequency range 2FR2.

20. The wireless device of claim 14, the operations further comprising: comparing the change in the position or the orientation of the wireless device to a threshold change value; as well as In response to the comparison, the coverage range is accessed when the change exceeds the threshold.

21. The wireless device of claim 14, the operations further comprising: detecting that a signal strength received from the remote device is below a threshold signal strength; as well as In response to the detecting, the motion data is obtained.

22. The wireless device of claim 14, the operations further comprising: selecting a particular antenna and / or a particular beam for communicating with the remote device based on the coverage area; as well as Data is transmitted to or received from the remote device through the specific antenna and the specific beam.

23. A processor for a wireless device, the processor comprising: circuitry configured to communicate with a remote device; and circuitry for executing one or more instructions that, when executed, cause the processor to perform operations comprising: Determining an initial pose of the wireless device relative to the remote device using angle of arrival (AoA) data; obtaining motion data from one or more motion sensors coupled to the wireless device, the motion data indicating a change in position or orientation of the wireless device; determining a pose of the wireless device relative to a remote device based on the motion data, wherein the pose of the wireless device relative to the remote device is based on the motion data indicating a change in the position or the orientation of the wireless device from the initial pose; For each of a plurality of poses of the wireless device relative to the remote device, selecting a particular antenna or a particular beam for communicating with the remote device based on coverage associated with: an antenna for communicating with the remote device; a beam for communicating with the remote device; or both the antenna and beam configuration for communicating with the remote device; and Data is transmitted to or received from the remote device through the specific antenna or the specific beam.

24. The processor of claim 23, wherein the motion data indicates that the position or the orientation of the wireless device has not changed over a period of time, and the operations further comprise: determining that one or more metrics of a communication channel between the wireless device and the remote device fail to satisfy one or more corresponding thresholds; Responsive to the determining, identifying an angle of arrival (AoA) value for a strongest signal from the remote device; and The particular beam and the particular antenna associated with the AoA value in the coverage area are identified from the coverage area.

25. The processor of claim 24, wherein the one or more metrics include at least one of a signal-to-noise ratio (SNR) of a signal received from the remote device, a delay spread value of the signal, and a variation value of the AoA of the signal.

26. The processor of claim 23, wherein the coverage range indicates that the particular antenna and the particular beam represent a highest gain for enabling transmission of data to the remote device or reception of additional data from the remote device.

27. The processor of claim 23, wherein the one or more motion sensors include at least an accelerometer, a gyroscope, or both the accelerometer and the gyroscope.

28. The processor of claim 23, wherein the wireless device and the remote device are configured for mm-wave communication using frequency range 2FR2.

29. The processor of claim 23, wherein selecting the particular antenna and the particular beam for communicating with the remote device is performed with a delay of less than 2 milliseconds.

30. The processor of claim 23, the operations further comprising periodically retrieving motion data to determine whether the wireless device is moving or stationary.

31. The processor of claim 23, wherein the wireless device comprises at least three antenna arrays, and wherein each antenna array comprises at least 10 beam configurations.

32. The processor of claim 23, wherein determining the pose of the wireless device relative to the remote device based on the motion data comprises: determining that one or more of translational motion or rotational motion of the wireless device exceeds a motion threshold; as well as In response to determining that the motion threshold is exceeded, the coverage area is accessed.

33. The processor of claim 23, the operations further comprising: comparing the change in the position or the orientation of the wireless device to a threshold change value; as well as In response to the comparison, the coverage range is accessed when the change exceeds the threshold.

34. The processor of claim 23, the operations further comprising: detecting that a signal strength received from the remote device is below a threshold signal strength; as well as In response to the detecting, the motion data is obtained.

35. The processor of claim 23, the operations further comprising: selecting a particular antenna and / or a particular beam for communicating with the remote device based on the coverage area; as well as Data is transmitted to or received from the remote device through the specific antenna and the specific beam.

Images