Near-field device detection

Abstract

Systems and methods related to near- / far-field detection in a wireless network and performing actions at a network node based thereon are disclosed. In one embodiment, a method performed by a network node of a wireless network for communicating with a device comprises determining whether the device is in a near-field or far-field of an antenna array of the network node, wherein the determining is based on one or more parameters comprising variation of Angle-of-Arrival (AOA) of one or more signals received from the device across two or more different sub-arrays of the antenna array of the network node. The method further comprises performing one or more actions according to a result of determining whether the device is in the near-field or far-field of the antenna array of the network node.

Description

NEAR-FIELD DEVICE DETECTIONTECHNICAL FIELD

[0001] The present disclosure relates to a wireless communication network and, more specifically, detecting whether a device is in a near-field of a serving network node in a wireless communications network.BACKGROUND

[0002] Multiple-Input Multiple-Output (MIMO) is one of the key physical layer technologies in the 3rdGeneration Partnership Project (3GPP) 5thGeneration (5G) Radio Access Technology (RAT), which is referred to as New Radio (NR). Here, a gNodeB (gNB) with many, e.g., 64, antennas provides large array gains and / or performs spatial multiplexing of many User Equipments (UEs) on the same time-frequency resources. Particularly, the received Signal-to-Noise Ratio (SNR) increases with the number of antennas. Hence, the spectral efficiency increases or, equivalently, the required power to satisfy a quality-of-service requirement decreases, as the number of antennas increases.

[0003] Due to the success of massive MIMO (mMIMO), it is expected that beyond 5G and 6thGeneration (6G) systems will make use of even larger antenna arrays. For instance, currently, NR- Advanced in Release 19 MIMO specifies support of Channel State Information (CSI) feedback for large arrays with up to 128 antenna ports. In such cases and / or when using high frequencies, the electromagnetic radiation field may need to be modeled by near-field spherical waves, which differs from the conventional planar- wave based radiation model. As a result, it may be required to consider the near-field MIMO communications in beyond 5G networks. For instance, enhancements related to near-field communications were suggested for possible study in 3GPP Release 19. Furthermore, in Release 19, 3GPP is studying channel modeling for scenarios with near-field communication (see Moderator's summary for REL-19 RANI topic IS AC & Exploring Study in New Spectrum (7-24GHz), 3GPP TSG-RAN Meeting #101, Sept. 2023). Hence, the field of near-field communication is relevant for 6G.

[0004] Implementing a very large number of antennas results in fundamental changes of the electromagnetic characteristics. Generally, the electromagnetic radiation field can be divided into far-field and near-field regions. Far-field refers to the propagation range at which the direction and channel gain are approximately the same from all elements in the array to the transmitting / receiving antenna. The amplitude depends only on the propagation distance to the center of the receiver and the phase variations only depend on the incident angle. Also, themismatch between the polarization of an antenna and of the incident wave is approximately the same for all antennas in the far-field. On the other hand, if the receive antenna is in the near-field of the transmitter, the propagation distances are so short that there are noticeable amplitude variations over the receiver aperture. Also, the incident wave is arriving from distinctly different angular directions to different elements, thus, e.g., one must model the polarization on an element- by-element basis.

[0005] Theoretically, the boundary between these two regions may be determined by the Fraunhofer distance, also called the Rayleigh distance, which is determined based on the maximum allowable phase error in the antenna array. Outside the Fraunhofer distance, it is the far-field region, where the electromagnetic field can be approximately modeled by planar waves. Within the Fraunhofer distance, the near-field propagation becomes dominant, where the electromagnetic field has to be accurately modeled by spherical waves. However, distance-based determination of the near-field UE is not accurate and requires assisting information about the device which may not be available at the network node.SUMMARY

[0006] Systems and methods related to near- / far-field detection in a wireless network and performing actions at a network node based thereon are disclosed. In one embodiment, a method performed by a network node of a wireless network for communicating with a device comprises determining whether the device is in a near-field or far-field of an antenna array of the network node, wherein the determining is based on one or more parameters comprising variation of Angle- of-Arrival (AOA) of one or more signals received from the device across two or more different sub-arrays of the antenna array of the network node. The method further comprises performing one or more actions according to a result of determining whether the device is in the near-field or far-field of the antenna array of the network node. In this manner, it is possible to determine whether the device is in the near-field or far-field of the antenna array of the network node without requiring knowledge of device’s position, antenna size, etc., and for the network node to serve the device with appropriate configurations.

[0007] In one embodiment, the one or more parameters further comprise a similarity metric between beam patterns for beamformers assuming planar and spherical wavefronts. In one embodiment, the beam patterns are calculated for the beamformers assuming spherical wavefronts corresponding to different distances from the antenna array of the network node. In one embodiment, the similarity metric is between two beam patterns and is based on a least squares difference between the two beam patterns. In one embodiment, the similarity metric is betweentwo beam patterns and is based on a difference in null depth between the two beam patterns. In one embodiment, the similarity metric is between two beam patterns and is based on a difference in maximum beamforming gain between the two beam patterns. In one embodiment, the similarity metric is between two beam patterns and is based on a difference in boresight beamforming gain between the beam patterns. In one embodiment, determining whether the device is in the near- field or far-field of the antenna array of the network node comprises determining, with respect to the device, the similarity metric between two or more beam patterns for two or more beamformers for downlink transmission to or uplink reception from the device, the two or more beamformers assuming spherical wavefronts corresponding to different distances from the antenna array of the network node.

[0008] In one embodiment, the one or more parameters further comprise a difference in Reference Signal Received Power (RSRP) measurements reported by the device that correspond to two different downlink reference signals transmitted from two different antenna elements in the antenna array of the network node in two symbols of a same time slot.

[0009] In one embodiment, the one or more parameters further comprise variation of phase, amplitude, and / or polarization across different antenna elements in the antenna array of the network node, with respect to an uplink reference signal received from the device at the different antenna elements.

[0010] In one embodiment, the one or more parameters further comprise linear deviation from a linear phase front over the antenna array.

[0011] In one embodiment, determining whether the device is in the near-field or far-field comprises determining that the device is in the near-field based on a metric defined by the variation of the AOA of the one or more signals across the different subarrays being larger than a predefined AoA variation threshold. In one embodiment, the metric is further defined by either or both of: a similarity metric between beam patterns for beamformers assuming planar and spherical wavefronts being larger than a predefined similarity metric difference threshold and a difference between the RSRP measurements is higher than a predefined RSRP difference threshold.

[0012] In one embodiment, determining whether the device is in the near-field or far-field is further based on whether the device is in Line of Sight (LOS) or Non-LOS (NLOS) of the antenna array of the network node.

[0013] In one embodiment, the one or more parameters comprise two or more parameters, and determining whether the device is in the near-field or far-field comprises determining whether the device is in the near-field or far-field based on the two or more parameters and associated priorities.

[0014] In one embodiment, the one or more parameters comprise two or more parameters, and determining whether the device is in the near-field or far-field comprises determining whether the device is in the near-field or far-field based on the two or more of the parameters and one or more priority rules for combination of near- / far-field detection results obtained based on the two or more parameters. In one embodiment, the two or more parameters comprise the variation of AoA, a similarity metric between beam patterns for beamformers assuming planar and spherical wavefronts, and a difference in RSRP measurements reported by the device that correspond to two different downlink reference signals transmitted from two different antenna elements in the antenna array of the network node in two symbols of a same time slot, and the one or more priority rules comprise: a rule that a near- / far-field detection result based on the similarity metric has higher priority compared to a near- / far-field detection result based on the variation of AoA, a rule that a near- / far-field detection result based on the similarity metric has higher priority compared to a near- / far-field detection result based on the difference in RSRP, and / or a rule that a near- / far-field detection result based on the variation in AoA has higher priority compared a near- / far-field detection result based on the difference in RSRP.

[0015] In one embodiment, performing the one or more actions comprises updating a set of precoders for transmission to the device, depending on whether the device is determined to be in the near-field or the far-field.

[0016] In one embodiment, performing the one or more actions comprises configuring the device based on a result of the determining whether the device is in the near-field or far-field of the antenna array of the network node. In one embodiment, configuring the device based on the result of the determining comprises: (A) informing the device about the result of the determining whether the device is in the near-field or far-field of the antenna array of the network node; (B) providing the device with a beam configuration that is based on the result of the determining whether the device is in the near-field or far-field of the antenna array of the network node; (C) providing the device with a power configuration that is based on the result of the determining whether the device is in the near-field or far-field of the antenna array of the network node; (D) providing the device with a codebook configuration that is based on the result of the determining whether the device is in the near-field or far-field of the antenna array of the network node; or (E) any combination of two or more of A-D. In another embodiment, the result of the determining whether the device is in the near-field or far-field of the antenna array of the network node is that the device is determined to be in the near-field, and configuring the device based on the result of the determining whether the device is in the near-field or far-field of the antenna array of the network node comprises providing the device with a codebook configuration that configures thedevice with a codebook that targets only near-field communication or a codebook configuration that configures the device with a codebook that jointly targets both far-field and near-field communication.

[0017] In one embodiment, the device is a user equipment, an intelligent reflecting surface, a network-controlled repeater, an integrated access and backhaul node, or a node in fixed wireless access network.

[0018] Corresponding embodiments of a network node are also disclosed. In one embodiment, a network node for a wireless network for communicating with a device is adapted to determine whether the device is in a near-field or far-field of an antenna array of the network node, wherein the determining is based on one or more parameters comprising variation of AO A of one or more signals received from the device across two or more different sub-arrays of the antenna array of the network node. The network node is further adapted to perform one or more actions according to a result of the determining.

[0019] In one embodiment, a network node for a wireless network for communicating with a device comprises a communication interface comprising radio front-end circuitry and an antenna array, and processing circuitry associated with the communication interface. The processing circuitry is configured to cause the network node to determine whether the device is in a near-field or far-field of an antenna array of the network node, wherein the determining is based on one or more parameters comprising variation of AOA of one or more signals received from the device across two or more different sub-arrays of the antenna array of the network node. The processing circuitry is further configured to cause the network node to perform one or more actions according to a result of the determining.BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawing figures incorporated in and forming a part of this specification illustrate several aspects of the disclosure, and together with the description serve to explain the principles of the disclosure.

[0021] Figure 1 is a flowchart that illustrates a procedure performed by a network node in accordance with embodiments of the present disclosure;

[0022] Figures 2, 3, 4, 5, 6, 7, and 8 illustrate the operation of the network node to determine whether the device is in the near-field or far-field, in accordance with various embodiments of the present disclosure;

[0023] Figure 9 shows an example of a communication system in accordance with some embodiments of the present disclosure;

[0024] Figure 10 shows a User Equipment device (UE) in accordance with some embodiments of the present disclosure;

[0025] Figure 11 shows a network node in accordance with some embodiments of the present disclosure; and

[0026] Figure 12 is a block diagram illustrating a virtualization environment in which functions implemented by some embodiments may be virtualized in accordance with some embodiments of the present disclosure.DETAILED DESCRIPTION

[0027] The embodiments set forth below represent information to enable those skilled in the art to practice the embodiments and illustrate the best mode of practicing the embodiments. Upon reading the following description in light of the accompanying drawing figures, those skilled in the art will understand the concepts of the disclosure and will recognize applications of these concepts not particularly addressed herein. It should be understood that these concepts and applications fall within the scope of the disclosure.

[0028] Some of the embodiments contemplated herein will now be described more fully with reference to the accompanying drawings. Embodiments are provided by way of example to convey the scope of the subject matter to those skilled in the art.

[0029] There currently exist certain challenge(s) with existing Multiple-Input Multiple- Output (MIMO) technology, specifically as utilized in the existing 3rdGeneration Partnership Project (3GPP) 5thGeneration (5G) system. Existing MIMO networks, including that utilized in a 3GPP system, are mainly developed from far-field communication theories and techniques. However, with the increase in the number of antennas and / or carrier frequency in beyond 5G and 6thGeneration (6G) systems, the near-field region of the very large antenna arrays may expand by orders of magnitude and reach up to a few hundred meters. In such cases, the spherical wave model and the other near-field communication characteristics should be taken into account, as they may affect the beam management procedure, scheduling, etc. For this reason, there is a need for systems and methods for determining whether a device is in the near-field or far-field of a serving base station(s) (e.g., serving gNodeB(s) (gNB(s)) considering 3GPP New Radio (NR) terminology). Particularly, in order to adapt downlink (DL) and / or uplink (UL) communication based on whether a device is located in near-field or far-field, how to detect whether a device is in the near-field or far-field of a serving base station(s) is an open issue.

[0030] Note that United States Patent Application Publication 2024 / 0088980A1, entitled BEAM DETERMINATION IN HOLOGRPHIC MIMO SYSTEM, which is hereinafter referredto as “the ‘980 Publication”, teaches a method for near-field detection based on determining the position of the User Equipment (UE) and comparing the UE’s position with the Fraunhofer distance. However, this is not an accurate method for near-field detection and requires extra information about the UE and new signaling as suggested in the ‘980 Publication, which may not be available at the network.

[0031] In the description provided herein, the term “device” refers to a UE, Intelligent Reflecting Surface (IRS), Network-Controlled Repeater (NCR), Integrated Access and Backhaul (IAB) node, etc.

[0032] Certain aspects of the disclosure and their embodiments may provide solutions to aforementioned and / or other challenges. Systems and methods for detecting near-field devices with no need for information about the device’s position and / or its antenna size, etc. are disclosed herein. Also, embodiments of the systems and methods disclosed herein are well applicable in the Fixed Wireless Access (FWA) networks. Here, different techniques such as Angle-of-Arrival (AoA) estimation, similarity measurements associated with different beam patterns, and / or channel measurements associated with different sub-arrays are utilized to determine whether the device, e.g., the UE, the IRS, the NCR, the IAB, falls in the near-field or far-field of the serving base station(s) (e.g., serving gNB(s)). Then, based on such a determination, the device is configured appropriately.

[0033] Embodiments of the present disclosure provide a solution(s) for near- / far-field detection with no need for information about the device’s position and / or its antenna size, etc. As disclosed herein, a method performed by a network node (e.g., a base station such as, e.g., a gNB) includes the following steps: determining whether the device is in near- or far-field and performing one or more actions based on a result of the determining.

[0034] Embodiments are also disclosed that are related to different techniques for near- / far- field detection based on measurements on one or more reference signals associated with one or more network node antenna sub-arrays where, for instance, the AoA associated with different subarrays, the similarities between different beam patterns, etc. are used to determine whether the device is in near-field or not. Moreover, the actions performed by the network node in response to determining whether the device is in the near-field or far-field include, e.g., providing the device with appropriate codebook, beam, and / or power configurations. In this way, embodiments of the solution(s) disclosed herein enable appropriate communication with near-field devices with limited interference to the network.

[0035] Certain embodiments may provide one or more of the following technical advantage(s). Embodiments of the solution(s) disclosed herein makes it possible to determinewhether a device is in the near-field or far-field of its serving network node (e.g., serving base station such as, e.g., serving gNB). This, in turns, enables the network node to serve the device with appropriate configurations. As opposed to the method taught by the ‘980 Publication, which is based on UE position estimation and comparison of the UE’s position with Fraunhofer distance, near-field detection techniques are disclosed herein that do not require knowledge of the device’s position or knowledge of the device’s antenna size, etc. In some embodiments, the near- / far-field detection disclosed herein is performed based on measurements on downlink (DL) or uplink (UL) reference signals associated with one or more antenna sub-arrays of the network node, e.g., Reference Signal Received Power (RSRP) measurements on different reference signals transmitted by different sub-arrays, AoA measurements on different sub-arrays, and / or similarity measurements between beam patterns for beamformers assuming planar and spherical wavefronts, which enable accurate near-field detection. Such techniques require no information about the device position and / or the device antenna size, etc. As a result, with embodiments of the present disclosure, spectral efficiency is improved, and network interference can be reduced. In this way, embodiments of the solution(s) disclosed herein addresses one of the points of interest in 3GPP Release 20 as well as 6G.

[0036] Now, the description will turn to a more detailed description of embodiments of the present disclosure. As described above, the existing MIMO framework in 3GPP NR is designed based on the far-field assumption. This is based on the fact that, with current number of antennas and carrier frequencies, the near-field region is in the order of few meters and, as a result, far-field is an appropriate assumption. With beyond 5G, it is quite likely that the number of antennas at the network nodes (e.g., gNBs) and / or devices increases, and higher frequencies may be used. For instance, currently, 3GPP Release 19 specifies Channel State Information (CSI) feedback for large arrays with up to 128 CSI Reference Signal (CSI-RS) ports. In such cases, depending on the number of antennas / carrier frequency, the near-field range may increase to a few hundred meters. If a device in the near-field is configured with far-field transmission settings (e.g., configured with legacy codebook assuming linear phase front) or if a device in the near-field is served by the base station with far-field assumptions, performance loss can be expected. Thus, it is beneficial to determine if the device is in the near- or far-field of its serving network node, and act correspondingly based on this determination.

[0037] One option for near-field detection is to estimate the device’s position and compare it with the Fraunhofer distance, as disclosed in the ‘980 Publication. In general, there may be multiple techniques to determine the device position including, e.g., timing advance, path loss,and / or round-trip time determination. However, using the device’s position estimation may not be accurate or feasible for near-field detection due to, e.g. the following:• With a device in the near-field, the positioning accuracy may be low given that the existing positioning schemes are mainly designed based on the far-field assumption. This may be especially problematic in cases with high-mobility near-field devices.• Even if the device position is perfectly known by the network node, it is not trivial to determine if the device is in near-field or far-field. For example, the Fraunhofer distance depends on the size of the device antenna / panel, which is not known by the network node.

[0038] Systems and methods are disclosed herein that address the aforementioned issues. In particular, systems and methods are disclosed herein in which near-field (and / or far- field) device detection is performed with no need for information about the device’s position and / or its antenna size, etc. Note, however, that information about the UE’s position can be used as auxiliary information to further assist in the near- / far-field detection techniques disclosed herein.

[0039] In this regard, Figure 1 is a flowchart that illustrates a procedure performed by a network node in accordance with embodiments of the present disclosure. The network node is preferably a Radio Access Network (RAN) node such as, e.g., a base station (e.g., a gNB) in a RAN of a cellular communications system such as, e.g., a 5G Advanced or 6G system. As illustrated, the network node determines if a device, e.g., a UE, IRS, NCR, IAB, etc., is in the nearer far-field based on one or more parameters (step 100). As discussed below, the one or more parameters based on which the determination in step 100 made may include: (i) variation of AoA of one or more signals received from device across two or more different sub-arrays of the antenna array of the network node, (ii) a similarity metric between beam patters for beamformers assuming planar and spherical wavefronts, (iii) a difference in RSRP measurements reported by the device that correspond to two different downlink reference signals transmitted from two different antenna elements in the antenna array of the network node in two symbols of a same time slot, (iv) variation of phase, amplitude, and / or polarization across different antenna elements in the antenna array of the network node, with respect to an uplink reference signal received from the device at the different antenna elements (e.g., linear deviation from a linear phase front over the antenna array), or (v) any combination of two or more of (i)-(iv). The network node performs one or more actions based on a result of the determination made in step 100 (step 102). Details regarding steps 100 and 102 are provided below.

[0040] In regard to step 100, any one or more of the following near- / far-field detection techniques may be used to determine if the device in in the near-field or far-field.

[0041] In one embodiment, the near- / far-field determination of step 100 is based on detecting phase, amplitude, and / or polarization variations in different antenna elements in an antenna array of the network node or in different sub-arrays of the antenna array of the network node. In a scenario in which the antenna elements are divided into different sub-arrays, the different antenna elements used for performing near- / far-field detection may include antenna elements in different sub-arrays, antenna elements in a same sub-array, or both antenna elements in different sub-arrays and antenna elements in a same sub-array.

[0042] Here, regarding e.g., the phase, one may consider the deviation from a linear phase front over the array. One can estimate phase deviation by measuring the phase of the elements of the antenna array from an uplink (UL) reference signal (RS) and then subtracting a linear phase front. If the maximum absolute value after the subtraction is greater than a predefined threshold (e.g., TT / 8 (or a fraction of TT / 8), the device is determined to be in the near-field. To improve accuracy of the phase deviation measurement, averaging over multiple measurements may be used. To further improve the phase deviation measurement, one can transform the channel estimates in frequency domain to delay domain via an Inverse Fast Fourier Transform (IFFT), filter out the first strong tap (corresponding to a potential Line of Sight (LOS) path), and then do the phase estimation for that tap. In a similar manner, amplitude variation and / or polarization variation may additionally or alternatively be considered.

[0043] In one embodiment, the detected amplitude, phase, and / or polarization variation is compared to a predetermined threshold variation and, if greater than the threshold, the device is determined to be in the near-field. The threshold(s) may be predetermined, e.g., via simulations or otherwise.

[0044] Figure 2 illustrates the operation of the network node to determine whether the device is in the near-field or far-field, in accordance with one embodiment of the present disclosure. As illustrated, the device transmits one or more UL reference signals (step 200). At the network node, the network node 202 receives the UL reference signal(s) separately via different antenna subarrays (step 202) and generates a measurement(s) of phase variation, amplitude variation, and / or polarization variation of the received UL reference signal(s) for the different antenna sub-arrays (step 204). The measurements are time-aligned or sufficiently close in time so that the channel does not change between the measurements. For example, measurements from different OFDM symbols within the same slot can be used. The network node determines whether the device is in the near-field or far-field based on the measurement(s) generated in step 204 (step 206). More specifically, the network node determines whether the amplitude variation, phase variation, and / or polarization variation across the different antenna elements is greater than a predefinedthreshold(s) (e.g., an amplitude variation threshold, a phase variation threshold, and / or a polarization variation threshold) and, if so, determines that the device is in the near-field (i.e., not in the far-field) and, otherwise, determines that the device is in the far-field (i.e., not in the near- field). Note that, if more than two antenna elements are used, in one embodiment, the device is determined to be in the near-field if the amplitude variation, phase variation, and / or polarization variation between any two antenna elements is greater than the predefined threshold(s). Alternatively, in another embodiment, the device is determined to be in the near field if the amplitude, phase, and or polarization variation across the antenna elements for all pairs of the antenna- sub arrays exceeds the predefined threshold(s). Also note that, if two or more of amplitude, phase, and polarization (e.g., both amplitude and phase, both phase and polarization, all three o amplitude, phase, and polarization) are considered, then, in one embodiment, the device is determined to be in the near-field if the variation in any of the two (or more) of the considered parameters is greater than the respective threshold (e.g., if amplitude and phase are considered, the device is determined to be in the near-field if either or both the amplitude variation exceeds a predefined amplitude variation or the phase variation exceeds a predefined phase variation). Alternatively, in another embodiment, the device is determined to be in the near field if variation across the antenna sub-arrays for all of the two (or more) considered parameters exceeds their respective predefined thresholds.

[0045] In another embodiment, the near / far-field determination of step 100 is based on RSRP measurements (e.g., Layer 1 (LI) RSRP measurements) reported by the device. For instance, as illustrated in the example of Figure 3, the network node may transmit two different downlink reference signals from two different antenna elements of the antenna array in two symbols of a same time slot (steps 300 and 302). If the antenna array is arranged into two or more sub-arrays, the two different antenna elements may be in the same sub-array or different sub-arrays. The device measures layer 1 RSRPs of the two downlink reference signals and reports the measured layer 1 RSRPs to the network node with respect to the two transmitted downlink reference signals (304). The device may report the measurements in one or more RSRP measurement reports. The network node determines whether the device is in the near-field or far-field (i.e., performs near- / far-field detection) by comparing the received RSRP measurements (step 306). For example, the network node may determine that the device is in the near-field if the difference between the two RSRP measurements is greater than a predefined RSRP difference threshold; otherwise, the network node determines that the device is in the far-field. For instance, if the difference between the two received RSRP values is above X dB, e.g., X=1 dB, the device is considered to be in near- field; otherwise, the device is determined to be in far-field. This is intuitive because, if the deviceis in the near-field of the network node, the device may receive considerably different signals from two different antenna elements of the network node.

[0046] In one alternative embodiment, the near- / far-field determination of step 100 is based on estimating angle-of-arrival (AOA) from the device using different sub-arrays of the network node’ s antenna array and detecting differences in the estimated AO As from the different subarrays. This is based on the fact that different sub-arrays of the array will have different angles to the device when the device is in the near-field. Thus, if the array is divided into sub-arrays and the AOA is estimated for different sub-arrays, one can determine if the different sub-arrays have different angles to the device. If so, the device can be determined to be in the near field. Here, the sub-arrays can be either non-overlapping and contiguous or overlapping. In this regard, Figure 4 illustrates the operation of the network node to determine whether the device is in the near-field or far-field in step 100 based on estimating AoA from the device using different antenna subarrays, in accordance with an example embodiment of the present disclosure. As illustrated, the device transmits one or more uplink reference signals (400), and the network node receives the uplink reference signal(s) from the device via two or more different antenna sub-arrays (step 402). The network node generates AoA measurements for the different antenna sub-arrays based on the received uplink reference signal(s) (step 404). The network node determines whether the device is in the near-field or far-field based on a variation of the AoA measurements across the different antenna sub-arrays (step 406). For example, the network node may determine that the device in the near-field if the variation (i.e., difference) between the AoA measurements between two different antenna sub-arrays is greater than a predefined AoA variation (e.g., X degrees, where X is a predetermined non-zero integer number); otherwise, the network node determines that the device is in the far-field. Note that, if more than two antenna sub-arrays are used, in one embodiment, the device is determined to be in the near-field if the AoA variation between any two antenna sub-arrays is greater than the predefined threshold. Alternatively, in another embodiment, the device is determined to be in the near field if the AoA variation across the antenna sub-arrays for all pairs of the antenna- sub arrays exceeds the predefined threshold.

[0047] In one embodiment, near- / far-field determination can be based on beamforming gain when applying beamforming weights with a linear phase progression. In this regard, Figure 5 illustrates the operation of the network node to determine whether the device is in the near-field or far-field in step 100 based on beamforming gain when applying beamforming weights with a linear phase progression, in accordance with an example embodiment of the present disclosure. As illustrated, the device transmits one or more UL reference signals (step 500). The network node receives the UL reference signal(s) and estimates a wireless channel for each antenna elementor each antenna sub-array (step 502). The network node applies different beamforming vectors on the estimated channel for each antenna element or antenna sub-array (step 504) and determines whether the device is in the near-field or far-field based on beamforming gains of the different beamforming vectors (step 506). More specifically, in one embodiment, the different beamforming vectors are linear phase front vectors (e.g., Discrete Fourier Transform (DFT) vectors) that correspond to different far-field directions. If the device is in the far-field (and in LOS), the beamforming vectors that correspond to the LOS direction will give a maximum beamforming gain (e.g., equal to the number of antenna elements). However, if the device is in the near-field, then none of the beamforming vectors will give the maximum beamforming gain. Thus, in step 506, the network node determines that the device is in the far-field if the beamforming gain for any of the beamforming vectors is greater than or equal to a predefined or configured beamforming gain threshold (e.g., a fraction of the maximum theoretical beamforming gain); otherwise, the network node determines that the device is in the near field.

[0048] In another embodiment, the beamforming vectors applied in step 504 are different near-field beamforming vectors, which are matched to a spherical wavefront. In this embodiment, in step 506, the network node determines that the device is in the near-field if the beamforming gain of any one of the near-field beamforming vectors is greater than or equal to a predefined or configured beamforming gain threshold (e.g., a fraction of the maximum theoretical beamforming gain); otherwise, the network node determines that the device is in the far-field.

[0049] In one embodiment, whether the device is in the near- or far-field can be determined in step 100 according to a similarity metric between beam patterns for beamformers assuming planar and spherical wavefronts. Here, multiple beam patterns may be calculated for beamformers assuming spherical wavefronts corresponding to different distances. As non-limiting examples, the similarity metric between two beam patterns may be based on a least squares difference between the beam patterns or a difference in null depth between the beam patterns. Alternatively, the similarity metric between two beam patterns may be based on a difference in maximum beamforming gain between the beam patterns or a difference in boresight beamforming gain between the beam patterns. Here, for instance, if the difference in maximum beamforming gain between the beam patterns is above X%, e.g., X=5%, the device is determined to be in the near- field; otherwise, the device is determined to be in the far-field. In this regard, Figure 6 illustrates the operation of the network node to determine whether the device is in the near-field or far-field in step 100 based on a similarity metric between beam patterns for beamformers, in accordance with an example embodiment of the present disclosure. As illustrated, the network node determines, with respect to the device, a similarity metric between two (or more) beam patternsfor two (or more) beamformers for reception from the device, where the two or more beamformers assume spherical wavefronts and correspond to different distances from the antenna array of the network node (step 600). The network node then determines whether the device is in the near- field or far-field based on the similarity metric (step 602), as discussed above.

[0050] In another embodiment, the near- / far-field detection of step 100 can be performed based on the device being in Line-of-Sight (LOS) or Non-LOS (NLOS) of the antenna array of the network node. The LOS or NLOS condition of the device may be taken into consideration along with any one or more of the parameters described above to determine whether the device is in the near-field or in the far-field. With high probability, devices in the near-field are in LOS. Here, any technology for LOS detection may be used. For instance, the LOS can be detected by analyzing the channel impulse response, where one can use data only for the first tap when doing the detection of phase / amplitude variations, in order to filter out the LOS path. In this regard, Figure 7 is a flow chart that illustrates a procedure performed by the network node in step 100 for near- / far-field detection based on LOS / NLOS detection, in accordance with an example embodiment of the present disclosure. As illustrated, the network node determines whether the device is LOS or NLOS (step 700). Any LOS or NLOS detection technique may be used. The network node determines whether the device in the in the near-field or the far-field based on whether the device is determined in step 700 to be in the near-field or in the far-field (step 702). For example, the network node determines that the device is in the near-field if the device is LOS; otherwise, the network node determines that the device is in the far-field. As another example, if the device is NLOS, the network node determines that the device is in the far-field; otherwise, if the device is LOS, the network node uses one of the other methods described above to determine whether the device is in the near-field or far-field.

[0051] Figure 8 is a flow chart that illustrates a process performed by the network node in step 100 for near- / far-field detection based on the combination of multiple near- / far-field detection procedures (e.g., any two or more of the near- / far-field detection procedures described above, e.g., with respect to Figures 2 to 7), in accordance with an example embodiment of the present disclosure. In this embodiment, the network node performs the near- / far-field detection based on the combination of two or more of the near- / far-field detection procedures described above (step 800). Each of these procedures provides a corresponding result indicating whether that procedure determines that the device is in the near-field or in the far-field. If the results obtained via the different near- / far-field detection procedures contradict with each other, the network node performs a contradiction resolution procedure to make a final decision on whether the device is in the near-field or in the far-field (step 802). For example, in one embodiment, the contradictionresolution procedure considers priority rules to resolve the contradiction. For instance, the similarity-based near- / far-field detection procedure may have higher priority compared to the AoA-based near- / far-field detection procedure. In another example, the similarity-based near- / far- field detection procedure may have higher priority compared to the sub-array RSRP measurementbased near- / far-field detection procedure. In another example, the AoA-based near- / far-field detection procedure may have higher priority compared to sub-array RSRP measurement-based near- / far-field detection procedure. In one example, the result of the highest priority near- / far- field detection procedure is taken as the final decision.

[0052] In an alternative embodiment, the contradiction resolution may be performed based on the measurement values obtained in the different near- / far-field detection procedures. For instance, if the difference between the RSRP measurements associated with different sub-arrays is very high, e.g., above Y dB (Y= 2 dB, for instance), the network node may ignore the results obtained by the other near- / far-field detection procedures.

[0053] In step 102, the network node performs one or more appropriate actions based on the result of the near- / far-field detection in step 100. Here, one may consider actions transparent to the device, which only affect network node, or actions for proper device configuration.

[0054] In one embodiment, the network node update a set of analog or time-domain precoders, e.g., used at millimeter wave (mmWave) frequencies, depending whether, in step 100, the device is determined to be in near-field or in the far-field. This action is transparent to the device. To give a more concrete example, when the device is in the far-field, a Discrete Fourier Transform (DFT)- based analog precoder with linear phase front that points to the device direction is good for serving the device. However, when the device is in the near-field, an analog precoder that creates a focal point at the device would be more appropriate for serving the device. Then, the network node may adjust the beamforming weights according to the near- / far-field detection outcome.

[0055] In another embodiment, in step 102, the network node may configure the device based on the near- / far-field determination, where the configuration may comprise any one or more of the following actions: a. Informing the device about the result of the detection b. Providing the device with appropriate beam configuration c. Providing the device with power configuration d. Providing the device with appropriate codebook configuration

[0056] In accordance with embodiments of the present disclosure, the network node can determine whether the device is in the near- or far-field, with no need for information about thedevice position and / or its sizes, and can serve the device accordingly. This will improve the spectral efficiency and will reduce the network interference.

[0057] Figure 9 shows an example of a communication system 900 in which embodiments of the present disclosure may be implemented. The network node described above may be, for example, one of the network nodes 910A and 91 OB of Figure 9, and the device described above may be, for example, one of the UEs 912A or 912B of Figure 9. However, embodiments of the present disclosure are not limited thereto.

[0058] In the example, the communication system 900 includes a telecommunication network 902 that includes an access network 904, such as a Radio Access Network (RAN), and a core network 906, which includes one or more core network nodes 908. The access network 904 includes one or more access network nodes, such as network nodes 910A and 910B (one or more of which may be generally referred to as network nodes 910), or any other similar Third Generation Partnership Project (3GPP) access nodes or non-3GPP Access Points (APs). Moreover, as will be appreciated by those of skill in the art, a network node is not necessarily limited to an implementation in which a radio portion and a baseband portion are supplied and integrated by a single vendor. Thus, it will be understood that network nodes include disaggregated implementations or portions thereof. For example, in some embodiments, the telecommunication network 902 includes one or more Open-RAN (ORAN) network nodes. An ORAN network node is a node in the telecommunication network 902 that supports an ORAN specification (e.g., a specification published by the O-RAN Alliance, or any similar organization) and may operate alone or together with other nodes to implement one or more functionalities of any node in the telecommunication network 902, including one or more network nodes 910 and / or core network nodes 908.

[0059] Examples of an ORAN network node include an Open Radio Unit (O-RU), an Open Distributed Unit (O-DU), an Open Central Unit (O-CU), including an O-CU Control Plane (O- CU-CP) or an O-CU User Plane (O-CU-UP), a RAN intelligent controller (near-real time or non- real time) hosting software or software plug-ins, such as a near-real time control application (e.g., xApp) or a non-real time control application (e.g., rApp), or any combination thereof (the adjective “open” designating support of an ORAN specification). The network node may support a specification by, for example, supporting an interface defined by the ORAN specification, such as an Al, Fl, Wl, El, E2, X2, Xn interface, an open fronthaul user plane interface, or an open fronthaul management plane interface. Moreover, an ORAN access node may be a logical node in a physical node. Furthermore, an ORAN network node may be implemented in a virtualization environment (described further below) in which one or more network functions are virtualized.For example, the virtualization environment may include an O-Cloud computing platform orchestrated by a Service Management and Orchestration Framework via an 0-2 interface defined by the 0-RAN Alliance or comparable technologies. The network nodes 910 facilitate direct or indirect connection of User Equipment (UE), such as by connecting UEs 912A, 912B, 912C, and 912D (one or more of which may be generally referred to as UEs 912) to the core network 906 over one or more wireless connections.

[0060] Example wireless communications over a wireless connection include transmitting and / or receiving wireless signals using electromagnetic waves, radio waves, infrared waves, and / or other types of signals suitable for conveying information without the use of wires, cables, or other material conductors. Moreover, in different embodiments, the communication system 900 may include any number of wired or wireless networks, network nodes, UEs, and / or any other components or systems that may facilitate or participate in the communication of data and / or signals whether via wired or wireless connections. The communication system 900 may include and / or interface with any type of communication, telecommunication, data, cellular, radio network, and / or other similar type of system.

[0061] The UEs 912 may be any of a wide variety of communication devices, including wireless devices arranged, configured, and / or operable to communicate wirelessly with the network nodes 910 and other communication devices. Similarly, the network nodes 910 are arranged, capable, configured, and / or operable to communicate directly or indirectly with the UEs 912 and / or with other network nodes or equipment in the telecommunication network 902 to enable and / or provide network access, such as wireless network access, and / or to perform other functions, such as administration in the telecommunication network 902.

[0062] In the depicted example, the core network 906 connects the network nodes 910 to one or more hosts, such as host 916. These connections may be direct or indirect via one or more intermediary networks or devices. In other examples, network nodes may be directly coupled to hosts. The core network 906 includes one more core network nodes (e.g., core network node 908) that are structured with hardware and software components. Features of these components may be substantially similar to those described with respect to the UEs, network nodes, and / or hosts, such that the descriptions thereof are generally applicable to the corresponding components of the core network node 908. Example core network nodes include functions of one or more of a Mobile Switching Center (MSC), Mobility Management Entity (MME), Home Subscriber Server (HSS), Access and Mobility Management Function (AMF), Session Management Function (SMF), Authentication Server Function (AUSF), Subscription Identifier De-Concealing Function (SIDF),Unified Data Management (UDM), Security Edge Protection Proxy (SEPP), Network Exposure Function (NEF), and / or a User Plane Function (UPF).

[0063] The host 916 may be under the ownership or control of a service provider other than an operator or provider of the access network 904 and / or the telecommunication network 902, and may be operated by the service provider or on behalf of the service provider. The host 916 may host a variety of applications to provide one or more service. Examples of such applications include live and pre-recorded audio / video content, data collection services such as retrieving and compiling data on various ambient conditions detected by a plurality of UEs, analytics functionality, social media, functions for controlling or otherwise interacting with remote devices, functions for an alarm and surveillance center, or any other such function performed by a server.

[0064] As a whole, the communication system 900 of Figure 9 enables connectivity between the UEs, network nodes, and hosts. In that sense, the communication system 900 may be configured to operate according to predefined rules or procedures, such as specific standards that include, but are not limited to: Global System for Mobile Communications (GSM); Universal Mobile Telecommunications System (UMTS); Long Term Evolution (LTE), and / or other suitable Second, Third, Fourth, or Fifth Generation (2G, 3G, 4G, or 5G) standards, or any applicable future generation standard (e.g., Sixth Generation (6G)); Wireless Local Area Network (WLAN) standards, such as the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standards (WiFi); and / or any other appropriate wireless communication standard, such as the Worldwide Interoperability for Microwave Access (WiMax), Bluetooth, Z-Wave, Near Field Communication (NFC) ZigBee, LiFi, and / or any Low Power Wide Area Network (LPWAN) standards such as LoRa and Sigfox.

[0065] In some examples, the telecommunication network 902 is a cellular network that implements 3GPP standardized features. Accordingly, the telecommunication network 902 may support network slicing to provide different logical networks to different devices that are connected to the telecommunication network 902. For example, the telecommunication network 902 may provide Ultra Reliable Low Latency Communication (URLLC) services to some UEs, while providing enhanced Mobile Broadband (eMBB) services to other UEs, and / or massive Machine Type Communication (mMTC) / massive Internet of Things (loT) services to yet further UEs.

[0066] In some examples, the UEs 912 are configured to transmit and / or receive information without direct human interaction. For instance, a UE may be designed to transmit information to the access network 904 on a predetermined schedule, when triggered by an internal or external event, or in response to requests from the access network 904. Additionally, a UE may beconfigured for operating in single- or multi -Radio Access Technology (RAT) or multi -standard mode. For example, a UE may operate with any one or combination of WiFi, New Radio (NR), and LTE, i.e. being configured for Multi -Radio Dual Connectivity (MR-DC), such as Evolved UMTS Terrestrial RAN (E-UTRAN) NR - Dual Connectivity (EN-DC).

[0067] In the example, a hub 914 communicates with the access network 904 to facilitate indirect communication between one or more UEs (e.g., UE 912C and / or 912D) and network nodes (e.g., network node 910B). In some examples, the hub 914 may be a controller, router, content source and analytics, or any of the other communication devices described herein regarding UEs. For example, the hub 914 may be a broadband router enabling access to the core network 906 for the UEs. As another example, the hub 914 may be a controller that sends commands or instructions to one or more actuators in the UEs. Commands or instructions may be received from the UEs, network nodes 910, or by executable code, script, process, or other instructions in the hub 914. As another example, the hub 914 may be a data collector that acts as temporary storage for UE data and, in some embodiments, may perform analysis or other processing of the data. As another example, the hub 914 may be a content source. For example, for a UE that is a Virtual Reality (VR) headset, display, loudspeaker or other media delivery device, the hub 914 may retrieve VR assets, video, audio, or other media or data related to sensory information via a network node, which the hub 914 then provides to the UE either directly, after performing local processing, and / or after adding additional local content. In still another example, the hub 914 acts as a proxy server or orchestrator for the UEs, in particular if one or more of the UEs are low energy loT devices.

[0068] The hub 914 may have a constant / persistent or intermittent connection to the network node 910B. The hub 914 may also allow for a different communication scheme and / or schedule between the hub 914 and UEs (e.g., UE 912C and / or 912D), and between the hub 914 and the core network 906. In other examples, the hub 914 is connected to the core network 906 and / or one or more UEs via a wired connection. Moreover, the hub 914 may be configured to connect to a Machine-to-Machine (M2M) service provider over the access network 904 and / or to another UE over a direct connection. In some scenarios, UEs may establish a wireless connection with the network nodes 910 while still connected via the hub 914 via a wired or wireless connection. In some embodiments, the hub 914 may be a dedicated hub - that is, a hub whose primary function is to route communications to / from the UEs from / to the network node 910B. In other embodiments, the hub 914 may be a non-dedicated hub - that is, a device which is capable of operating to route communications between the UEs and the network node 910B, but which is additionally capable of operating as a communication start and / or end point for certain data channels.

[0069] Figure 10 shows a UE 1000 in accordance with some embodiments. As used herein, a UE refers to a device capable, configured, arranged, and / or operable to communicate wirelessly with network nodes and / or other UEs. Examples of a UE include, but are not limited to, a smart phone, mobile phone, cell phone, Voice over Internet Protocol (VoIP) phone, wireless local loop phone, desktop computer, Personal Digital Assistant (PDA), wireless camera, gaming console or device, music storage device, playback appliance, wearable terminal device, wireless endpoint, mobile station, tablet, laptop, Laptop Embedded Equipment (LEE), Laptop Mounted Equipment (LME), smart device, wireless Customer Premise Equipment (CPE), vehicle, vehicle-mounted or vehicle embedded / integrated wireless device, etc. Other examples include any UE identified by the 3 GPP, including a Narrowband Internet of Things (NB-IoT) UE, a Machine Type Communication (MTC) UE, and / or an enhanced MTC (eMTC) UE.

[0070] A UE may support Device-to-Device (D2D) communication, for example by implementing a 3 GPP standard for sidelink communication, Dedicated Short-Range Communication (DSRC), Vehi cl e-to- Vehicle (V2V), Vehicle-to-Infrastructure (V2I), or Vehicle- to-Everything (V2X). In other examples, a UE may not necessarily have a user in the sense of a human user who owns and / or operates the relevant device. Instead, a UE may represent a device that is intended for sale to, or operation by, a human user but which may not, or which may not initially, be associated with a specific human user (e.g., a smart sprinkler controller). Alternatively, a UE may represent a device that is not intended for sale to, or operation by, an end user but which may be associated with or operated for the benefit of a user (e.g., a smart power meter).

[0071] The UE 1000 includes processing circuitry 1002 that is operatively coupled via a bus 1004 to an input / output interface 1006, a power source 1008, memory 1010, a communication interface 1012, and / or any other component, or any combination thereof. Certain UEs may utilize all or a subset of the components shown in Figure 10. The level of integration between the components may vary from one UE to another UE. Further, certain UEs may contain multiple instances of a component, such as multiple processors, memories, transceivers, transmitters, receivers, etc.

[0072] The processing circuitry 1002 is configured to process instructions and data and may be configured to implement any sequential state machine operative to execute instructions stored as machine-readable computer programs in the memory 1010. The processing circuitry 1002 may be implemented as one or more hardware-implemented state machines (e.g., in discrete logic, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), etc.); programmable logic together with appropriate firmware; one or more stored computer programs,general purpose processors, such as a microprocessor or Digital Signal Processor (DSP), together with appropriate software; or any combination of the above. For example, the processing circuitry 1002 may include multiple Central Processing Units (CPUs).

[0073] In the example, the input / output interface 1006 may be configured to provide an interface or interfaces to an input device, output device, or one or more input and / or output devices. Examples of an output device include a speaker, a sound card, a video card, a display, a monitor, a printer, an actuator, an emitter, a smartcard, another output device, or any combination thereof. An input device may allow a user to capture information into the UE 1000. Examples of an input device include a touch-sensitive or presence-sensitive display, a camera (e.g., a digital camera, a digital video camera, a web camera, etc.), a microphone, a sensor, a mouse, a trackball, a directional pad, a trackpad, a scroll wheel, a smartcard, and the like. The presence-sensitive display may include a capacitive or resistive touch sensor to sense input from a user. A sensor may be, for instance, an accelerometer, a gyroscope, a tilt sensor, a force sensor, a magnetometer, an optical sensor, a proximity sensor, a biometric sensor, etc., or any combination thereof. An output device may use the same type of interface port as an input device. For example, a Universal Serial Bus (USB) port may be used to provide an input device and an output device.

[0074] In some embodiments, the power source 1008 is structured as a battery or battery pack. Other types of power sources, such as an external power source (e.g., an electricity outlet), photovoltaic device, or power cell, may be used. The power source 1008 may further include power circuitry for delivering power from the power source 1008 itself, and / or an external power source, to the various parts of the UE 1000 via input circuitry or an interface such as an electrical power cable. Delivering power may be, for example, for charging of the power source 1008. Power circuitry may perform any formatting, converting, or other modification to the power from the power source 1008 to make the power suitable for the respective components of the UE 1000 to which power is supplied.

[0075] The memory 1010 may be or be configured to include memory such as Random Access Memory (RAM), Read Only Memory (ROM), Programmable ROM (PROM), Erasable PROM (EPROM), Electrically EPROM (EEPROM), magnetic disks, optical disks, hard disks, removable cartridges, flash drives, and so forth. In one example, the memory 1010 includes one or more application programs 1014, such as an operating system, web browser application, a widget, gadget engine, or other application, and corresponding data 1016. The memory 1010 may store, for use by the UE 1000, any of a variety of various operating systems or combinations of operating systems.

[0076] The memory 1010 may be configured to include a number of physical drive units, such as Redundant Array of Independent Disks (RAID), flash memory, USB flash drive, external hard disk drive, thumb drive, pen drive, key drive, High Density Digital Versatile Disc (HD-DVD) optical disc drive, internal hard disk drive, Blu-Ray optical disc drive, Holographic Digital Data Storage (HDDS) optical disc drive, external mini Dual In-line Memory Module (DIMM), Synchronous Dynamic RAM (SDRAM), external micro-DIMM SDRAM, smartcard memory such as a tamper resistant module in the form of a Universal Integrated Circuit Card (UICC) including one or more Subscriber Identity Modules (SIMs), such as a Universal SIM (USIM) and / or Internet Protocol Multimedia Services Identity Module (ISIM), other memory, or any combination thereof. The UICC may for example be an embedded UICC (eUICC), integrated UICC (iUICC) or a removable UICC commonly known as a ‘SIM card.’ The memory 1010 may allow the UE 1000 to access instructions, application programs, and the like stored on transitory or non-transitory memory media, to off-load data, or to upload data. An article of manufacture, such as one utilizing a communication system, may be tangibly embodied as or in the memory 1010, which may be or comprise a device-readable storage medium.

[0077] The processing circuitry 1002 may be configured to communicate with an access network or other network using the communication interface 1012. The communication interface 1012 may comprise one or more communication subsystems and may include or be communicatively coupled to an antenna 1022. The communication interface 1012 may include one or more transceivers used to communicate, such as by communicating with one or more remote transceivers of another device capable of wireless communication (e.g., another UE or a network node in an access network). Each transceiver may include a transmitter 1018 and / or a receiver 1020 appropriate to provide network communications (e.g., optical, electrical, frequency allocations, and so forth). Moreover, the transmitter 1018 and receiver 1020 may be coupled to one or more antennas (e.g., the antenna 1022) and may share circuit components, software, or firmware, or alternatively be implemented separately.

[0078] In the illustrated embodiment, communication functions of the communication interface 1012 may include cellular communication, WiFi communication, LPWAN communication, data communication, voice communication, multimedia communication, short- range communications such as Bluetooth, NFC, location-based communication such as the use of the Global Positioning System (GPS) to determine a location, another like communication function, or any combination thereof. Communications may be implemented according to one or more communication protocols and / or standards, such as IEEE 802.11, Code Division Multiplexing Access (CDMA), Wideband CDMA (WCDMA), GSM, LTE, NR, UMTS, WiMax,Ethernet, Transmission Control Protocol / Intemet Protocol (TCP / IP), Synchronous Optical Networking (SONET), Asynchronous Transfer Mode (ATM), Quick User Datagram Protocol Internet Connection (QUIC), Hypertext Transfer Protocol (HTTP), and so forth.

[0079] Regardless of the type of sensor, a UE may provide an output of data captured by its sensors, through its communication interface 1012, via a wireless connection to a network node. Data captured by sensors of a UE can be communicated through a wireless connection to a network node via another UE. The output may be periodic (e.g., once every 15 minutes if it reports the sensed temperature), random (e.g., to even out the load from reporting from several sensors), in response to a triggering event (e.g., when moisture is detected, an alert is sent), in response to a request (e.g., a user initiated request), or a continuous stream (e.g., a live video feed of a patient).

[0080] As another example, a UE comprises an actuator, a motor, or a switch related to a communication interface configured to receive wireless input from a network node via a wireless connection. In response to the received wireless input the states of the actuator, the motor, or the switch may change. For example, the UE may comprise a motor that adjusts the control surfaces or rotors of a drone in flight according to the received input or to a robotic arm performing a medical procedure according to the received input.

[0081] A UE, when in the form of an loT device, may be a device for use in one or more application domains, these domains comprising, but not limited to, city wearable technology, extended industrial application, and healthcare. Non-limiting examples of such an loT device are a device which is or which is embedded in: a connected refrigerator or freezer, a television, a connected lighting device, an electricity meter, a robot vacuum cleaner, a voice controlled smart speaker, a home security camera, a motion detector, a thermostat, a smoke detector, a door / window sensor, a flood / moisture sensor, an electrical door lock, a connected doorbell, an air conditioning system like a heat pump, an autonomous vehicle, a surveillance system, a weather monitoring device, a vehicle parking monitoring device, an electric vehicle charging station, a smart watch, a fitness tracker, a head-mounted display for Augmented Reality (AR) or VR, a wearable for tactile augmentation or sensory enhancement, a water sprinkler, an animal- or item-tracking device, a sensor for monitoring a plant or animal, an industrial robot, an Unmanned Aerial Vehicle (UAV), and any kind of medical device, like a heart rate monitor or a remote controlled surgical robot. A UE in the form of an loT device comprises circuitry and / or software in dependence of the intended application of the loT device in addition to other components as described in relation to the UE 1000 shown in Figure 10.

[0082] As yet another specific example, in an loT scenario, a UE may represent a machine or other device that performs monitoring and / or measurements and transmits the results of suchmonitoring and / or measurements to another UE and / or a network node. The UE may in this case be an M2M device, which may in a 3GPP context be referred to as an MTC device. As one particular example, the UE may implement the 3 GPP NB-IoT standard. In other scenarios, a UE may represent a vehicle, such as a car, a bus, a truck, a ship, an airplane, or other equipment that is capable of monitoring and / or reporting on its operational status or other functions associated with its operation.

[0083] In practice, any number of UEs may be used together with respect to a single use case. For example, a first UE might be or be integrated in a drone and provide the drone’s speed information (obtained through a speed sensor) to a second UE that is a remote controller operating the drone. When the user makes changes from the remote controller, the first UE may adjust the throttle on the drone (e.g., by controlling an actuator) to increase or decrease the drone’s speed. The first and / or the second UE can also include more than one of the functionalities described above. For example, a UE might comprise the sensor and the actuator and handle communication of data for both the speed sensor and the actuators.

[0084] Figure 11 shows a network node 1100 in accordance with some embodiments. As used herein, network node refers to equipment capable, configured, arranged, and / or operable to communicate directly or indirectly with a UE and / or with other network nodes or equipment in a telecommunication network. Examples of network nodes include, but are not limited to, APs (e.g., radio APs), Base Stations (BSs) (e.g., radio BSs, Node Bs, evolved Node Bs (eNBs), NR. Node Bs (gNBs)), and 0-RAN nodes or components of an 0-RAN node (e.g., 0-RU, 0-DU, O-CU).

[0085] Base stations may be categorized based on the amount of coverage they provide (or, stated differently, their transmit power level) and so, depending on the provided amount of coverage, may be referred to as femto base stations, pico base stations, micro base stations, or macro base stations. A base station may be a relay node or a relay donor node controlling a relay. A network node may also include one or more (or all) parts of a distributed radio base station such as centralized digital units, distributed units (e.g., in an 0-RAN access node), and / or Remote Radio Units (RRUs), sometimes referred to as Remote Radio Heads (RRHs). Such RRUs may or may not be integrated with an antenna as an antenna integrated radio. Parts of a distributed radio base station may also be referred to as nodes in a Distributed Antenna System (DAS).

[0086] Other examples of network nodes include multiple Transmission Point (multi-TRP) 5G access nodes, Multi -Standard Radio (MSR) equipment such as MSR BSs, network controllers such as Radio Network Controllers (RNCs) or BS Controllers (BSCs), Base Transceiver Stations (BTSs), transmission points, transmission nodes, Multi-Cell / Multicast Coordination Entities (MCEs), Operation and Maintenance (O&M) nodes, Operations Support System (OSS) nodes,Self-Organizing Network (SON) nodes, positioning nodes (e.g., Evolved Serving Mobile Location Centers (E-SMLCs)), and / or Minimization of Drive Tests (MDTs).

[0087] The network node 1100 includes processing circuitry 1102, memory 1104, a communication interface 1106, and a power source 1108. The network node 1100 may be composed of multiple physically separate components (e.g., a NodeB component and an RNC component, or a BTS component and a BSC component, etc.), which may each have their own respective components. In certain scenarios in which the network node 1100 comprises multiple separate components (e.g., BTS and BSC components), one or more of the separate components may be shared among several network nodes. For example, a single RNC may control multiple NodeBs. In such a scenario, each unique NodeB and RNC pair may in some instances be considered a single separate network node. In some embodiments, the network node 1100 may be configured to support multiple RATs. In such embodiments, some components may be duplicated (e.g., separate memory 1104 for different RATs) and some components may be reused (e.g., a same antenna 1110 may be shared by different RATs). The network node 1100 may also include multiple sets of the various illustrated components for different wireless technologies integrated into network node 1100, for example GSM, WCDMA, LTE, NR, WiFi, Zigbee, Z-wave, Long Range Wide Area Network (LoRaWAN), Radio Frequency Identification (RFID), or Bluetooth wireless technologies. These wireless technologies may be integrated into the same or different chip or set of chips and other components within the network node 1100.

[0088] The processing circuitry 1102 may comprise a combination of one or more of a microprocessor, controller, microcontroller, CPU, DSP, ASIC, FPGA, or any other suitable computing device, resource, or combination of hardware, software, and / or encoded logic operable to provide, either alone or in conjunction with other network node 1100 components, such as the memory 1104, to provide network node 1100 functionality.

[0089] In some embodiments, the processing circuitry 1102 includes a System on a Chip (SOC). In some embodiments, the processing circuitry 1102 includes one or more of Radio Frequency (RF) transceiver circuitry 1112 and baseband processing circuitry 1114. In some embodiments, the RF transceiver circuitry 1112 and the baseband processing circuitry 1114 may be on separate chips (or sets of chips), boards, or units, such as radio units and digital units. In alternative embodiments, part or all of the RF transceiver circuitry 1112 and the baseband processing circuitry 1114 may be on the same chip or set of chips, boards, or units.

[0090] The memory 1104 may comprise any form of volatile or non-volatile computer- readable memory including, without limitation, persistent storage, solid state memory, remotely mounted memory, magnetic media, optical media, RAM, ROM, mass storage media (for example,a hard disk), removable storage media (for example, a flash drive, a Compact Disk (CD), or a Digital Video Disk (DVD)), and / or any other volatile or non-volatile, non-transitory device- readable, and / or computer-executable memory devices that store information, data, and / or instructions that may be used by the processing circuitry 1102. The memory 1104 may store any suitable instructions, data, or information, including a computer program, software, an application including one or more of logic, rules, code, tables, and / or other instructions capable of being executed by the processing circuitry 1102 and utilized by the network node 1100. The memory 1104 may be used to store any calculations made by the processing circuitry 1102 and / or any data received via the communication interface 1106. In some embodiments, the processing circuitry 1102 and the memory 1104 are integrated.

[0091] The communication interface 1106 is used in wired or wireless communication of signaling and / or data between a network node, access network, and / or UE. As illustrated, the communication interface 1106 comprises port(s) / terminal(s) 1116 to send and receive data, for example to and from a network over a wired connection. The communication interface 1106 also includes radio front-end circuitry 1118 that may be coupled to, or in certain embodiments a part of, the antenna 1110. The radio front-end circuitry 1118 comprises filters 1120 and amplifiers 1122. The radio front-end circuitry 1118 may be connected to the antenna 1110 and the processing circuitry 1102. The radio front-end circuitry 1118 may be configured to condition signals communicated between the antenna 1110 and the processing circuitry 1102. The radio front-end circuitry 1118 may receive digital data that is to be sent out to other network nodes or UEs via a wireless connection. The radio front-end circuitry 1118 may convert the digital data into a radio signal having the appropriate channel and bandwidth parameters using a combination of the filters 1120 and / or the amplifiers 1122. The radio signal may then be transmitted via the antenna 1110. Similarly, when receiving data, the antenna 1110 may collect radio signals which are then converted into digital data by the radio front-end circuitry 1118. The digital data may be passed to the processing circuitry 1102. In other embodiments, the communication interface 1106 may comprise different components and / or different combinations of components.

[0092] In certain alternative embodiments, the network node 1100 does not include separate radio front-end circuitry 1118; instead, the processing circuitry 1102 includes radio front-end circuitry and is connected to the antenna 1110. Similarly, in some embodiments, all or some of the RF transceiver circuitry 1112 is part of the communication interface 1106. In still other embodiments, the communication interface 1106 includes the one or more ports or terminals 1116, the radio front-end circuitry 1118, and the RF transceiver circuitry 1112 as part of a radio unit (notshown), and the communication interface 1106 communicates with the baseband processing circuitry 1114, which is part of a digital unit (not shown).

[0093] The antenna 1110 may include one or more antennas, or antenna arrays, configured to send and / or receive wireless signals. The antenna 1110 may be coupled to the radio front-end circuitry 1118 and may be any type of antenna capable of transmitting and receiving data and / or signals wirelessly. In certain embodiments, the antenna 1110 is separate from the network node 1100 and connectable to the network node 1100 through an interface or port.

[0094] The antenna 1110, the communication interface 1106, and / or the processing circuitry 1102 may be configured to perform any receiving operations and / or certain obtaining operations described herein as being performed by the network node 1100. Any information, data, and / or signals may be received from a UE, another network node, and / or any other network equipment. Similarly, the antenna 1110, the communication interface 1106, and / or the processing circuitry 1102 may be configured to perform any transmitting operations described herein as being performed by the network node 1100. Any information, data, and / or signals may be transmitted to a UE, another network node, and / or any other network equipment.

[0095] The power source 1108 provides power to the various components of the network node 1100 in a form suitable for the respective components (e.g., at a voltage and current level needed for each respective component). The power source 1108 may further comprise, or be coupled to, power management circuitry to supply the components of the network node 1100 with power for performing the functionality described herein. For example, the network node 1100 may be connectable to an external power source (e.g., the power grid or an electricity outlet) via input circuitry or an interface such as an electrical cable, whereby the external power source supplies power to power circuitry of the power source 1108. As a further example, the power source 1108 may comprise a source of power in the form of a battery or battery pack which is connected to, or integrated in, power circuitry. The battery may provide backup power should the external power source fail.

[0096] Embodiments of the network node 1100 may include additional components beyond those shown in Figure 11 for providing certain aspects of the network node’s functionality, including any of the functionality described herein and / or any functionality necessary to support the subject matter described herein. For example, the network node 1100 may include user interface equipment to allow input of information into the network node 1100 and to allow output of information from the network node 1100. This may allow a user to perform diagnostic, maintenance, repair, and other administrative functions for the network node 1100. In some embodiments providing a core network node, such as core network node 108 of FIG. 9, somecomponents, such as the radio front-end circuitry 1118 and the RF transceiver circuitry 1112 may be omitted.

[0097] Figure 12 is a block diagram illustrating a virtualization environment 1200 in which functions implemented by some embodiments may be virtualized. In the present context, virtualizing means creating virtual versions of apparatuses or devices which may include virtualizing hardware platforms, storage devices, and networking resources. As used herein, virtualization can be applied to any device described herein, or components thereof, and relates to an implementation in which at least a portion of the functionality is implemented as one or more virtual components. Some or all of the functions described herein may be implemented as virtual components executed by one or more Virtual Machines (VMs) implemented in one or more virtualization environments 1200 hosted by one or more of hardware nodes, such as a hardware computing device that operates as a network node, a UE, a core network node, or a host. Further, in embodiments in which the virtual node does not require radio connectivity (e.g., a core network node or host), then the node may be entirely virtualized. In some embodiments, the virtualization environment 1200 includes components defined by the O-RAN Alliance, such as an O-Cloud environment orchestrated by a Service Management and Orchestration Framework via an O-2 interface. Virtualization may facilitate distributed implementations of a network node, a UE, a core network node, or a host.

[0098] Applications 1202 (which may alternatively be called software instances, virtual appliances, network functions, virtual nodes, virtual network functions, etc.) are run in the virtualization environment 1200 to implement some of the features, functions, and / or benefits of some of the embodiments disclosed herein.

[0099] Hardware 1204 includes processing circuitry, memory that stores software and / or instructions executable by hardware processing circuitry, and / or other hardware devices as described herein, such as a network interface, an input / output interface, and so forth. Software may be executed by the processing circuitry to instantiate one or more virtualization layers 1206 (also referred to as hypervisors or Virtual Machine Monitors (VMMs)), provide VMs 1208A and 1208B (one or more of which may be generally referred to as VMs 1208), and / or perform any of the functions, features, and / or benefits described in relation with some embodiments described herein. The virtualization layer 1206 may present a virtual operating platform that appears like networking hardware to the VMs 1208.

[0100] The VMs 1208 comprise virtual processing, virtual memory, virtual networking, or interface and virtual storage, and may be run by a corresponding virtualization layer 1206. Different embodiments of the instance of a virtual appliance 1202 may be implemented on one ormore of VMs 1208, and the implementations may be made in different ways. Virtualization of the hardware is in some contexts referred to as Network Function Virtualization (NFV). NFV may be used to consolidate many network equipment types onto industry standard high volume server hardware, physical switches, and physical storage, which can be located in data centers and customer premise equipment.

[0101] In the context of NFV, a VM 1208 may be a software implementation of a physical machine that runs programs as if they were executing on a physical, non-virtualized machine. Each of the VMs 1208, and that part of the hardware 1204 that executes that VM, be it hardware dedicated to that VM and / or hardware shared by that VM with others of the VMs, forms separate virtual network elements. Still in the context of NFV, a virtual network function is responsible for handling specific network functions that run in one or more VMs 1208 on top of the hardware 1204 and corresponds to the application 1202.

[0102] The hardware 1204 may be implemented in a standalone network node with generic or specific components. The hardware 1204 may implement some functions via virtualization. Alternatively, the hardware 1204 may be part of a larger cluster of hardware (e.g., such as in a data center or CPE) where many hardware nodes work together and are managed via management and orchestration 1210, which, among others, oversees lifecycle management of the applications 1202. In some embodiments, the hardware 1204 is coupled to one or more radio units that each include one or more transmitters and one or more receivers that may be coupled to one or more antennas. Radio units may communicate directly with other hardware nodes via one or more appropriate network interfaces and may be used in combination with the virtual components to provide a virtual node with radio capabilities, such as a radio access node or a base station. In some embodiments, some signaling can be provided with the use of a control system 1212 which may alternatively be used for communication between hardware nodes and radio units.

[0103] Although the computing devices described herein (e.g., UEs, network nodes) may include the illustrated combination of hardware components, other embodiments may comprise computing devices with different combinations of components. It is to be understood that these computing devices may comprise any suitable combination of hardware and / or software needed to perform the tasks, features, functions, and methods disclosed herein. Determining, calculating, obtaining, or similar operations described herein may be performed by processing circuitry, which may process information by, for example, converting the obtained information into other information, comparing the obtained information or converted information to information stored in the network node, and / or performing one or more operations based on the obtained information or converted information, and as a result of said processing making a determination. Moreover,while components are depicted as single boxes located within a larger box, or nested within multiple boxes, in practice, computing devices may comprise multiple different physical components that make up a single illustrated component, and functionality may be partitioned between separate components. For example, a communication interface may be configured to include any of the components described herein, and / or the functionality of the components may be partitioned between the processing circuitry and the communication interface. In another example, non-computationally intensive functions of any of such components may be implemented in software or firmware and computationally intensive functions may be implemented in hardware.

[0104] In certain embodiments, some or all of the functionality described herein may be provided by processing circuitry executing instructions stored on in memory, which in certain embodiments may be a computer program product in the form of a non-transitory computer- readable storage medium. In alternative embodiments, some or all of the functionality may be provided by the processing circuitry without executing instructions stored on a separate or discrete device-readable storage medium, such as in a hard-wired manner. In any of those particular embodiments, whether executing instructions stored on a non-transitory computer-readable storage medium or not, the processing circuitry can be configured to perform the described functionality. The benefits provided by such functionality are not limited to the processing circuitry alone or to other components of the computing device, but are enjoyed by the computing device as a whole, and / or by end users and a wireless network generally.

[0105] Those skilled in the art will recognize improvements and modifications to the embodiments of the present disclosure. All such improvements and modifications are considered within the scope of the concepts disclosed herein.

Claims

CLAIMS1. A method performed by a network node of a wireless network for communicating with a device, the method comprising: determining (100) whether the device is in a near-field or far-field of an antenna array of the network node, wherein the determining is based on one or more parameters comprising variation of Angle-of-Arrival, AOA, of one or more signals received from the device across two or more different sub-arrays of the antenna array of the network node; and performing (102) one or more actions according to a result of the determining (100) whether the device is in the near-field or far-field of the antenna array of the network node.

2. The method of claim 1, wherein the one or more parameters further comprise a similarity metric between beam patterns for beamformers assuming planar and spherical wavefronts.

3. The method of claim 2, wherein the beam patterns are calculated for the beamformers assuming spherical wavefronts corresponding to different distances from the antenna array of the network node.

4. The method of claim 2, wherein the similarity metric is between two beam patterns and is based on a least squares difference between the two beam patterns.

5. The method of claim 2, wherein the similarity metric is between two beam patterns and is based on a difference in null depth between the two beam patterns.

6. The method of claim 2, wherein the similarity metric is between two beam patterns and is based on a difference in maximum beamforming gain between the two beam patterns.

7. The method of claim 2, wherein the similarity metric is between two beam patterns and is based on a difference in boresight beamforming gain between the beam patterns.

8. The method of any of claims 2 to 7, wherein determining (100; 602) whether the device is in the near-field or far-field of the antenna array of the network node comprises: determining (600), with respect to the device, the similarity metric between two or more beam patterns for two or more beamformers for downlink transmission to or uplink reception from the device, the two or more beamformers assuming spherical wavefronts corresponding to different distances from the antenna array of the network node.

9. The method of any of claims 1 to 8, wherein the one or more parameters further comprise a difference in Reference Signal Received Power, RSRP, measurements reported by the device that correspond to two different downlink reference signals transmitted from two different antenna elements in the antenna array of the network node in two symbols of a same time slot.

10. The method of any of claims 1 to 9, wherein the one or more parameters further comprise variation of phase, amplitude, and / or polarization across different antenna elements in the antenna array of the network node, with respect to an uplink reference signal received from the device at the different antenna elements.

11. The method of any of claims 1 to 9, wherein the one or more parameters further comprise linear deviation from a linear phase front over the antenna array.

12. The method of claim 1, wherein determining (100) whether the device is in the near-field or far-field comprises determining (100) that the device is in the near-field based on a metric defined by the variation of the AOA of the one or more signals across the different subarrays being larger than a predefined AoA variation threshold.

13. The method of claim 12, wherein the metric is further defined by either or both of:• a similarity metric between beam patterns for beamformers assuming planar and spherical wavefronts being larger than a predefined similarity metric difference threshold;• a difference between the Reference Signal Received Power, RSRP, measurements is higher than a predefined RSRP difference threshold.

14. The method of any of claims 1 to 13, wherein determining (100) whether the device is in the near-field or far-field cis further based on whether the device is in Line of Sight, LOS, or Non- LOS, NLOS, of the antenna array of the network node.

15. The method of any of claims 1 to 14, wherein the one or more parameters comprise two or more parameters, and determining (100) whether the device is in the near-field or far-field comprises determining (100) whether the device is in the near-field or far-field based on the two or more parameters and associated priorities.

16. The method of any of claims 1 to 14, wherein the one or more parameters comprise two or more parameters, and determining (100) whether the device is in the near-field or far-field comprises determining (100) whether the device is in the near-field or far-field based on the two or more of the parameters and one or more priority rules for combination of near- / far-field detection results obtained based on the two or more parameters.

17. The method of 16, wherein the two or more parameters comprise the variation of AoA, a similarity metric between beam patterns for beamformers assuming planar and spherical wavefronts, and a difference in RSRP measurements reported by the device that correspond to two different downlink reference signals transmitted from two different antenna elements in the antenna array of the network node in two symbols of a same time slot, and the one or more priority rules comprise: a. a rule that a near- / far-field detection result based on the similarity metric has higher priority compared to a near- / far-field detection result based on the variation of AoA; b. a rule that a near- / far-field detection result based on the similarity metric has higher priority compared to a near- / far-field detection result based on the difference in RSRP; c. a rule that a near- / far-field detection result based on the variation in AoA has higher priority compared a near- / far-field detection result based on the difference in RSRP; or d. any combination of two or more of a-c.

18. The method of any of claims 1 to 17, wherein performing (102) the one or more actions comprises updating a set of precoders for transmission to the device, depending on whether the device is determined to be in the near-field or the far-field.

19. The method of any of claims 1 to 17, wherein performing (102) the one or more actions comprises configuring the device based on a result of the determining whether the device is in the near-field or far-field of the antenna array of the network node.

20. The method of claim 19, wherein configuring the device based on the result of the determining (100) comprises:A. informing the device about the result of the determining whether the device is in the near-field or far-field of the antenna array of the network node ;B. providing the device with a beam configuration that is based on the result of the determining whether the device is in the near-field or far-field of the antenna array of the network node ;C. providing the device with a power configuration that is based on the result of the determining whether the device is in the near-field or far-field of the antenna array of the network node;D. providing the device with a codebook configuration that is based on the result of the determining whether the device is in the near-field or far-field of the antenna array of the network node;E. any combination of two or more of A-D.

21. The method of claim 19, wherein the result of the determining (100) whether the device is in the near-field or far-field of the antenna array of the network node is that the device is determined to be in the near-field, and configuring the device based on the result of the determining whether the device is in the near-field or far-field of the antenna array of the network node comprises providing the device with a codebook configuration that configures the device with a codebook that targets only near-field communication or a codebook configuration that configures the device with a codebook that jointly targets both far-field and near-field communication.

22. The method of any of claims 1 to 21, wherein the device is a user equipment, an intelligent reflecting surface, a network-controlled repeater, an integrated access and backhaul node, or a node in fixed wireless access network.

23. A network node for a wireless network for communicating with a device, the network node adapted to: determine (100) whether the device is in a near-field or far-field of an antenna array of the network node, wherein the determining is based on one or more parameters comprising variation of Angle-of-Arrival, AOA, of one or more signals received from the device across two or more different sub-arrays of the antenna array of the network node; and perform (102) one or more actions according to a result of the determining (100).

24. The network node of claim 23, further adapted to perform the method of any of claims 2to 22.

25. A network node (1100) for a wireless network for communicating with a device, the network node comprising: a communication interface (1106) comprising radio front-end circuitry (1118) and an antenna array (1110); and processing circuitry (1102) associated with the communication interface (1103), the processing circuitry (1102) configured to cause the network node (1100) to: determine (100) whether the device is in a near-field or far-field of an antenna array of the network node, wherein the determining is based on one or more parameters comprising variation of Angle-of-Arrival, AO A, of one or more signals received from the device across two or more different sub-arrays of the antenna array of the network node; and perform (102) one or more actions according to a result of the determining (100).

26. The network node (1100) of claim 25, wherein the processing circuitry (1102) is further configured to cause the network node (1100) to perform the method of any of claims 2 to 22.

27. A computer program comprising instructions which, when executed on at least one processor, cause the processor to carry out the method according to any of claims 1 to 22.

28. A carrier containing the computer program of claim 27, wherein the carrier is one of an electronic signal, an optical signal, a radio signal, or a computer readable storage medium.

29. A non-transitory computer-readable medium comprising instructions executable by processing circuitry of a network node for a wireless network, whereby the network node is operable to: determine (100) whether a device is in a near-field or far-field of an antenna array of the network node, wherein the determining is based on one or more parameters comprising variation of Angle-of-Arrival, AOA, of one or more signals received from the device across two or more different sub-arrays of the antenna array of the network node; and perform (102) one or more actions according to a result of the determining (100).

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