Methods and apparatuses for sensing in a communication network

Abstract

A method (300) performed by a first network node for managing sensing in a Radio Access Technology, RAT, communication network, the method comprising: obtaining (302) a sensing quality assessment for one or more sensing measurements performed by a first set of sensing units for providing sensing, wherein the first set comprises at least one RAT- independent sensing unit; and performing (304), based on the sensing quality assessment, an optimization procedure to determine a second set of sensing units for providing the sensing, wherein the optimization procedure seeks to optimize a number of RAT-dependent sensing units comprised in the second set subject to at least one constraint.

Description

[0001] METHODS AND APPARATUSES FOR SENSING IN A COMMUNICATION NETWORK

[0002] Technical Field

[0003] Embodiments described herein relate to methods and apparatuses for sensing in a radio access technology communication network.

[0004] Background

[0005] RAT-dependent sensing

[0006] The system architectures groups (SA1 and SA2) of the 3rd Generation Partnership Project (3GPP) have defined study items to identify use cases and architectural enhancements that will enable integrated sensing and communications (ISAC) in radio access technology (RAT) communication networks (also referred to as joint communication and sensing (JCAS)). According to ISAC, sensing capabilities are included in the communication network such that both communication and sensing functionalities are integrated into the same transmission / reception nodes. Further information can be found in “Feasibility Study on Integrated Sensing and Communication”, 3GPP Technical Report 22.837, Release 19; and 3GPP RP-223114, “Study on Integrated Sensing and Communication for NR Rel-19”, 3GPP Work Item Description.

[0007] ISAC can be used to sense passive objects. A passive object is an object which does not have any means to connect to the RAT. Thus, in general, a passive object is any object whose presence / position / speed is desired to be known by the network, but with which the network cannot communicate through a communication link.

[0008] In most cases, a passive object is either moving or can be expected to move over a period of time (e.g., it has the ability to move). Examples of passive objects are cars without a sim card, people without a mobile phone (e.g., vulnerable road users), animals, etc. At any given time, the passive object may not be moving, but it can change its position over some period of time (e.g., a person who is sitting or a sleeping animal). The passive object is therefore differentiated from other objects in the environment such as walls, building and other static objects belonging to the environment.

[0009] Sensing within a communication network can be performed with a monostatic, bi-static or multistatic configuration. Examples of these sensing configurations are illustrated in Figures 1A, 1 B and 1C where they are deployed using cellular base stations. A signal is transmitted, and an object is sensed by measuring a reflection of the signal off the object (in this example the object is a person).

[0010] A monostatic configuration is a sensing configuration in which the transmitter and the receiver are co-located in the same node. Fig. 1A depicts a monostatic configuration in which the transmitter sensing antenna array (denoted TX-s) and the receiver sensing antenna array (denoted RX-s) are co-located at the same base station.

[0011] A bi-static configuration is a sensing configuration in which the transmitter is located in a first node at a first location, and the receiver is located in a second node at a different location to the first. Fig. 1 B depicts a bi-static configuration in which the TX-s is located at a different base station to the RX-s.

[0012] A multi-static configuration is a sensing configuration in which several transmitters and several receivers are present and they are all located at different nodes. Fig. 1C depicts a multi-static configuration comprising multiple base stations providing multiple sites for TX-s and multiple sites for RX-s.

[0013] Figure 2 illustrates the New Radio (NR) architecture applicable to positioning of a device, e.g., a user equipment (UE) 206. Positioning functionality is provided by the location management function (LMF) 202. The LMF 202 is a location node in the core network that manages different location services for target UEs such as positioning (e.g., determining the geographic position of the UE based on downlink and uplink location measuring radio signals) and the delivery of assistance data to UEs. Interactions between the LMF 202 and the gNodeB 204 are supported by the NRPPa protocol. Interactions between the gNodeB 204 and a device (e.g., the UE 206) are supported via the Radio Resource Control (RRC) protocol.

[0014] NR supports the following Radio Access Technology positioning methods.

[0015] (i) Downlink Time Difference of Arrival

[0016] The downlink (DL) Time Difference of Arrival (TDOA) positioning method makes use of the DL Reference Signal Time Difference (RSTD) of downlink signals received from multiple Transmission Points (TPs) at the UE. The DL TDOA positioning method may optionally also make use of the DL Positioning Reference Signal (PRS) Reference Signal Received Power (RSRP) of downlink signals. The UE measures the DL RSTD (and optionally DL PRS RSRP) of the received signals using assistance data received from the positioning server, and the resulting measurements are used along with other configuration information to locate the UE in relation to the neighbouring TPs.

[0017] (ii) Multi-RTT

[0018] The Multi Round-Trip Time (Multi-RTT) positioning method makes use of the UE Rx-Tx measurements and DL PRS RSRP of downlink signals received from multiple Transmission and Reception Points (TRPs) and measured by the UE. It also makes use of the measured gNB Rx-Tx measurements and uplink (UL) Sounding Reference Signal (SRS) RSRP at multiple TRPs of uplink signals transmitted by the UE.

[0019] (iii) Uplink Time Difference of Arrival

[0020] The UL TDOA positioning method makes use of the UL TDOA (and optionally UL SRS-RSRP) at multiple Reception Points (RPs) of uplink signals transmitted by the UE. The RPs measure the UL TDOA (and optionally UL SRS-RSRP) of the received signals using assistance data received from the positioning server, and the resulting measurements are used along with other configuration information to estimate the location of the UE.

[0021] (iv) Downlink Angle of Departure

[0022] The DL Angle of Departure (AoD) positioning method makes use of the measured DL PRS RSRP of downlink signals received at the UE from multiple TPs. The UE measures the DL PRS RSRP of the received signals using assistance data received from the positioning server, and the resulting measurements are used along with other configuration information to locate the UE in relation to the neighbouring TPs.

[0023] (v) Uplink Angle of Arrival

[0024] The UL Angle of Arrival (AoA) positioning method makes use of the measured azimuth and zenith of arrival at multiple RPs of uplink signals transmitted by the UE. The RPs measure A- AoA and Z-AoA of the received signals using assistance data received from the positioning server, and the resulting measurements are used along with other configuration information to estimate the location of the UE.

[0025] (vi) NR Enhanced Cell ID

[0026] NR Enhanced Cell ID (NR-ECID) positioning refers to techniques which use additional UE measurements and / or NR radio resource and other measurements to improve the UE location estimate.

[0027] RAT-independent Sensing Sensing can also be performed in a RAT-independent manner. A RAT-independent sensor is a sensor which does not use RAT resources (e.g., 5G / 6G radio resources) but instead has its own independent technique to generate results that can be used for sensing (e.g., extracting the environment information).

[0028] Examples of RAT-independent sensing are as follows.

[0029] (i) IMU

[0030] An inertial measurement unit (IMU) is an electronic device that measures and reports a body's specific force, angular rate, and sometimes the orientation of the body, using a combination of accelerometers, gyroscopes, and sometimes magnetometers. When the magnetometer is included, IMUs are referred to as IMMUs. IMUs are typically used to maneuver modern vehicles including motorcycles, missiles, aircraft (an attitude and heading reference system), including unmanned aerial vehicles (UAVs), among many others, and spacecraft, including satellites and landers. Recent developments allow for the production of IMU-enabled GPS devices. An IMU allows a GPS receiver to work when GPS-signals are unavailable, such as in tunnels, inside buildings, or when electronic interference is present.

[0031] (ii) LiDar camera

[0032] An acronym of "light detection and ranging"or "laser imaging, detection, and ranging") is a method for determining ranges by targeting an object or a surface with a laser and measuring the time for the reflected light to return to the receiver. LIDAR may operate in a fixed direction (e.g., vertical) or it may scan multiple directions, in which case it is known as LIDAR scanning or 3D laser scanning, a special combination of 3-D scanning and laser scanning. LIDAR has terrestrial, airborne, and mobile applications.

[0033] (iii) Radar

[0034] Radar is a radiolocation system that uses radio waves to determine the distance (ranging), angle (azimuth / elevation), and / or radial velocity of objects relative to the radar. For example, the radar may transmit a signal which is reflected from an object, and the position of the object may be determined based on the time the signal was transmitted and the time the signal was received. The object could, for example, be a passive object as described above, or an active object such as a UE. Radar represents a fundamentally important use of the electromagnetic spectrum. Radar sensors are used for a variety of purposes, including air traffic control, geophysical monitoring of Earth resources from space, automotive safety, mapping weather formations / severe weather tracking, and surveillance for defense and security. Radar can be performed by a standalone transmitter / receiver node (e.g., a network node or a UE) that is used only for sensing and not for communication (referred to as a radar sensor). The radar sensor uses different signals to the signals used within a RAT communication network for communication purposes. For example, pulse shaped radar signals and continuous wave radar signals are different to the sinusoidal reference signal used for communication.

[0035] The specific radar transmitter / receiver configurations can also be provided to active objects such as a target UE(s) or any assistant UE(s) to aid with sensing. For example, the active object may perform the measurements of the radar signal.

[0036] A monostatic radar configuration in which a base station uses 5G mmWave signals for sensing was considered in Barneto et al., in which estimation of range and velocity resolutions and selfinterference analysis are performed (see C. B. Barneto et al., “High-accuracy radio sensing in 5G new radio networks: Prospects and self-interference challenge,” in Proc. 53rd Asilomar Conf. Signals Syst. Comput., Pacific Grove, CA, USA, Nov. 2019, pp. 1159-1163; and C. B. Barneto et al., “Full-duplex OFDM radar with LTE and 5G NR waveforms: Challenges, solutions, and measurements,” IEEE Trans. Microw. Theory Techn., vol. 67, no. 10, pp. 4042- 4054, Oct. 2019). Target localization using bistatic and multistatic radar with 5G NR waveform has been studied using 5G based on measurements of time difference of arrival and angle of arrival with 5G NR waveforms (O. Kanhere, S. Goyal, M. Beluri and T. S. Rappaport, "Target Localization using Bistatic and Multistatic Radar with 5G NR Waveform," 2021 IEEE 93rd Vehicular Technology Conference (VTC2021 -Spring), 2021 , pp. 1-7).

[0037] Hybrid Positioning Methods

[0038] Hybrid positioning methods were introduced in Rel-15 in which motion sensor measurements are used in combination with other positioning methods to estimate the location of a UE. The motion sensors provide movement information comprising displacement results, estimated as an ordered series of points.

[0039] The motion sensor method makes use of different sensors such as accelerometers, gyros, or magnetometers, to calculate the displacement of the UE. The UE estimates a relative displacement based upon a reference position and / or reference time and sends a report comprising the determined relative displacement which can be used to determine the absolute position. This method may be used with other positioning methods for hybrid positioning. Hybrid positioning may also be achieved using barometric pressure sensors. The barometric pressure sensor positioning method makes use of barometric sensors to determine the vertical component of the position of the UE. The UE measures barometric pressure, optionally aided by assistance data, to calculate the vertical component of its location or to send measurements to the positioning server for position calculation. This method may then be combined with other positioning methods to determine the 3D position of the UE.

[0040] In 5G, the architecture and protocols support the provisioning of vehicle-based measurements to the network, more specifically to the LMF. The LMF in the current 3GPP architecture is a central LMF, which runs in a massive cloud platform and can be co-located with other core network entities, such as the Access and Mobility Management Function (AMF). Vehiclebased measurements such as displacement readings from inertial measurement unit (IMU) sensors and barometer pressure sensors for altitude computation can be used to perform hybrid positioning at the network side. The network may use other measurements or absolute positioning methods. This enables the LMF to exploit assumptions on device mobility and to achieve positioning enhancements through tracking.

[0041] Sensor fusion techniques

[0042] Sensor fusion is a process of combining information received from different sensors in order to estimate certain parameters, and most widely applied to the estimation of a position and a velocity of an object. Different sensor data fusion techniques are used such as Kalman filters, Bayesian filters, Probabilistic Data Association, Particle filters, Simultaneous localization and mapping (SLAM). Kalman filters are among the most popular techniques with some different variations depending on the considered system model. For example, unscented Kalman filters or extended Kalman filters are used for nonlinear system models.

[0043] Future generations of radio communications may introduce RAT-based sensing units (SUs) in the communication network for detecting passive objects and reporting sensing measurements (e.g., shape, location, velocity, etc.) to the network. This may be considered similar to TRPs for positioning reporting positioning measurements to the positioning server (i.e. , LMF).

[0044] However, since passive objects may move or change their characteristic properties over time (e.g., the velocity of a moving animal suddenly increases, or an elastic object is inflated, or there is a heat increase in the environment), the sensing units in the network would need to provide sensing measurement results in a dynamic way, in contrast to location services in which the object is a static connected object. For example, some Sils may need to be turned on to report more precise sensing measurements, while other Sils may not be usable in certain use cases. Furthermore, the change in the passive object’s characteristics may call for more or different types of sensors to be activated to improve the sensing result. Therefore, RAT- independent Sils may also be used, such as IMU, camera, LiDAR, radar etc.

[0045] Fusing data provided by RAT-independent sensors (e.g., onboard sensors) with data provided by RAT-dependent sensors (e.g., measurements on radio signals) incurs some computational complexity, depending on the frequency of the measurement updates, the amount of data provided by each measurement, and the algorithm(s) used to fuse such measurement data. It is currently unclear how a 5G or 6G system (as well as other future RAT systems) would behave when such sensor results are available and / or in situations where such results are missing. For instance, some use cases rely on a large set of sensors and data sources allowing acquisition of location awareness and positioning. However, depending on the situation and conditions such as weather and visibility, some sensors may fail, or may not work during a period of time.

[0046] Certain aspects of this disclosure may provide solutions to these or other challenges.

[0047] It is proposed herein to optimize (e.g., reduce) the use of RAT-dependent resources for sensing by prioritising the use of RAT-independent sensing resources. Furthermore, the RAT- dependent and RAT-independent sensing resources are managed in a centralised manner by assessing the quality of sensing measurement results.

[0048] According to a first aspect, there is provided a method performed by a first network node for managing sensing in a RAT communication network. The method comprises: obtaining a sensing quality assessment for one or more sensing measurements performed by a first set of sensing units for providing sensing, wherein the first set comprises at least one RAT- independent sensing unit; and performing, based on the sensing quality assessment, an optimization procedure to determine a second set of sensing units for providing the sensing, wherein the optimization procedure seeks to optimize a number of RAT-dependent sensing units comprised in the second set subject to at least one constraint.

[0049] According to a second aspect, there is provided a method performed by a second network node in a RAT communication network. The method comprises obtaining sensor information for a first set of sensing units for providing sensing. The first set comprises at least one RAT- independent sensing unit. The method further comprises determining, based on the obtained sensor information, a sensing quality assessment for one or more sensing measurements performed by the first set of sensing units.

[0050] According to a third aspect, there is provided a method performed by a RAN node in a RAT communication network. The method comprises receiving sensing information for a first sensing unit comprised in a first set of sensing units. The first set of sensing units comprises at least one RAT-independent sensing unit. The method further comprises transmitting the sensing information to a second network node; and after transmitting the sensing information, receiving a request to configure a second set of sensing units to perform sensing measurements. The method further comprises configuring, based on the request, the sensing units comprised in the second set of sensing units to perform sensing measurements.

[0051] According to a fourth aspect, there is provided a method performed by a first sensing unit in a RAT communication network. The method comprises: transmitting, to a first network node, one or more sensing capabilities of the first sensing unit; after transmitting the one or more sensing capabilities, receiving an indication to perform sensing measurements; and performing the sensing measurements.

[0052] According to a fifth aspect, there is provided a first network node comprising processing circuitry and a memory, the memory containing instructions executable by the processing circuitry whereby the first network node is operable to obtain a sensing quality assessment for one or more sensing measurements performed by a first set of sensing units for providing sensing. The first set comprises at least one RAT-independent sensing unit. The first network node is further operable to perform, based on the sensing quality assessment, an optimization procedure to determine a second set of sensing units for providing the sensing. The optimization procedure seeks to optimize a number of RAT-dependent sensing units comprised in the second set subject to at least one constraint.

[0053] According to a sixth aspect, there is provided a first network node adapted to obtain a sensing quality assessment for one or more sensing measurements performed by a first set of sensing units for providing sensing. The first set comprises at least one RAT-independent sensing unit. The first network node is further adapted to perform, based on the sensing quality assessment, an optimization procedure to determine a second set of sensing units for providing the sensing, The optimization procedure seeks to optimize a number of RAT-dependent sensing units comprised in the second set subject to at least one constraint. According to a seventh aspect, there is provided a second network node comprising processing circuitry and a memory, the memory containing instructions executable by the processing circuitry whereby the second network node is operable to obtain sensor information for a first set of sensing units for providing sensing. The first set comprises at least one RAT- independent sensing unit. The second network node is further operable to determine, based on the obtained sensor information, a sensing quality assessment for one or more sensing measurements performed by the first set of sensing units.

[0054] According to an eighth aspect, there is provided a second network node adapted to obtain sensor information for a first set of sensing units for providing sensing. The first set comprises at least one RAT-independent sensing unit. The second network node is further adapted to determine, based on the obtained sensor information, a sensing quality assessment for one or more sensing measurements performed by the first set of sensing units.

[0055] According to a ninth aspect, there is provided a RAN node comprising processing circuitry and a memory, the memory containing instructions executable by the processing circuitry whereby the RAN node is operable to receive sensing information for a first sensing unit comprised in a first set of sensing units. The first set of sensing units comprises at least one RAT- independent sensing unit. The RAN node is further operable to: transmit the sensing information to a second network node; after transmitting the sensing information, receive a request to configure a second set of sensing units to perform sensing measurements; and configure, based on the request, the sensing units comprised in the second set of sensing units to perform sensing measurements.

[0056] According to a tenth aspect, there is provided a RAN node adapted to receive sensing information for a first sensing unit comprised in a first set of sensing units. The first set of sensing units comprises at least one RAT-independent sensing unit. The RAN node is further adapted to transmit the sensing information to a second network node; after transmitting the sensing information, receive a request to configure a second set of sensing units to perform sensing measurements; and configure, based on the request, the sensing units comprised in the second set of sensing units to perform sensing measurements.

[0057] According to an eleventh aspect, there is provided a first sensing unit comprising processing circuitry and a memory, the memory containing instructions executable by the processing circuitry whereby the first sensing unit is operable to: transmit, to a first network node, one or more sensing capabilities of the first sensing unit; after transmitting the one or more sensing capabilities, receive an indication to perform sensing measurements; and perform the sensing measurements.

[0058] According to a twelfth aspect, there is provided a first sensing unit adapted to: transmit, to a first network node, one or more sensing capabilities of the first sensing unit; after transmitting the one or more sensing capabilities, receive an indication to perform sensing measurements; and perform the sensing measurements.

[0059] According to a thirteenth aspect, there is provided a computer program, comprising instructions which, when executed on at least one processor, cause the at least one processor to carry out a method according to any of the first, second, third, and / or fourth aspects.

[0060] These techniques ensure that, when adequate RAT-independent sensing resources are available, RAT-dependent resources are reserved for communication purposes. However, if the quality or quantity of the available RAT-independent sensing resources are inadequate, then this is compensated by using RAT-dependent sensing resources. Thus, the techniques disclosed herein provide for better resource utilization in the network, e.g., by reducing the sensing load on RAT-dependent resources whilst still maintaining a desired sensing quality.

[0061] The techniques disclosed herein further provide a centralised approach in which a network node is aware of which sensing units are involved in sensing and can dynamically manage the sensing resources responsive to changes in sensing demands and / or changes in the quality or availability of sensing resources.

[0062] Brief Description of the Drawings

[0063] For a better understanding of the embodiments of the present disclosure, and to show how it may be put into effect, reference will now be made, by way of example only, to the accompanying drawings, in which:

[0064] Fig. 1A is a schematic illustrating a monostatic radar sensing configuration;

[0065] Fig. 1 B is a schematic illustrating a bi-static radar sensing configuration;

[0066] Fig. 1C is a schematic illustrating a multi-static radar sensing configuration;

[0067] Fig. 2 is a schematic illustrating NR architecture applicable to positioning;

[0068] Fig. 3 is a flow chart illustrating a method performed by a first network node for managing sensing in a RAT communication network according to some embodiments; Fig. 4 is a flow chart illustrating a method performed by a second network node in a RAT communication network according to some embodiments;

[0069] Fig. 5 is a flow chart illustrating a method performed by a RAN node in a RAT communication network according to some embodiments;

[0070] Fig. 6 is a flow chart illustrating a method performed by a first sensing unit in a RAT communication network node according to some embodiments;

[0071] Fig. 7 is a signalling diagram illustrating techniques according to some embodiments;

[0072] Fig. 8 is a signalling diagram illustrating techniques according to some embodiments;

[0073] Fig. 9 is a signalling diagram illustrating techniques according to some embodiments;

[0074] Fig. 10A is a schematic illustrating techniques according to some embodiments;

[0075] Fig. 10B is a schematic illustrating techniques according to some embodiments;

[0076] Fig. 10C is a schematic illustrating techniques according to some embodiments;

[0077] Fig. 11 is a schematic illustrating techniques according to some embodiments;

[0078] Fig. 12 is a schematic illustrating an example of how an SeMF and an SPF could be incorporated into 3GPP positioning architecture according to some embodiments;

[0079] Fig. 13 is a schematic illustrating an example of the role of the SeMF according to some embodiments;

[0080] Fig. 14 is a schematic illustrating an example of the role of the SPF according to some embodiments;

[0081] Fig. 15 shows an example of a communication system in accordance with some embodiments;

[0082] Fig. 16 shows a network node in accordance with some embodiments;

[0083] Fig. 17 shows a network node in accordance with some embodiments;

[0084] Fig. 18 shows a UE in accordance with some embodiments;

[0085] Fig. 19 shows a communication diagram of a host communicating via a network node with a UE over a partially wireless connection in accordance with some embodiments;

[0086] Fig. 20 is a block diagram of a first network node in accordance with some embodiments;

[0087] Fig. 21 is a block diagram of a second network node in accordance with some embodiments;

[0088] Fig. 22 is a block diagram of a RAN node in accordance with some embodiments; and Fig. 23 is a block diagram of a first sensing unit in accordance with some embodiments.

[0089] Detailed Description

[0090] Generally, all terms used herein are to be interpreted according to their ordinary meaning in the relevant technical field, unless a different meaning is clearly given and / or is implied from the context in which it is used. All references to a / an / the element, apparatus, component, means, step, etc. are to be interpreted openly as referring to at least one instance of the element, apparatus, component, means, step, etc., unless explicitly stated otherwise. The steps of any methods disclosed herein do not have to be performed in the exact order disclosed, unless a step is explicitly described as following or preceding another step and / or where it is implicit that a step must follow or precede another step. Any feature of any of the embodiments disclosed herein may be applied to any other embodiment, wherever appropriate. Likewise, any advantage of any of the embodiments may apply to any other embodiments, and vice versa. Other objectives, features and advantages of the enclosed embodiments will be apparent from the following description.

[0091] The following sets forth specific details, such as particular embodiments or examples for purposes of explanation and not limitation. It will be appreciated by one skilled in the art that other examples may be employed apart from these specific details. In some instances, detailed descriptions of well-known methods, nodes, interfaces, circuits, and devices are omitted so as not obscure the description with unnecessary detail. Those skilled in the art will appreciate that the functions described may be implemented in one or more nodes using hardware circuitry (e.g., analog and / or discrete logic gates interconnected to perform a specialized function, ASICs, PLAs, etc.) and / or using software programs and data in conjunction with one or more digital microprocessors or general-purpose computers. Nodes that communicate using the air interface also have suitable radio communications circuitry. Moreover, where appropriate the technology can additionally be considered to be embodied entirely within any form of computer-readable memory, such as solid-state memory, magnetic disk, or optical disk containing an appropriate set of computer instructions that would cause a processor to carry out the techniques described herein.

[0092] Hardware implementation may include or encompass, without limitation, digital signal processor (DSP) hardware, a reduced instruction set processor, hardware (e.g., digital or analogue) circuitry including but not limited to application specific integrated circuit(s) (ASIC) and / or field programmable gate array(s) (FPGA(s)), and (where appropriate) state machines capable of performing such functions.

[0093] Particular embodiments are described more fully with reference to the accompanying drawings. Other embodiments, however, are contained within the scope of the subject matter disclosed herein. The disclosed subject matter should not be construed as limited to only the embodiments set forth herein; rather, these embodiments are provided by way of example to convey the scope of the subject matter to those skilled in the art. The steps of any methods disclosed herein do not have to be performed in the exact order disclosed, unless a step is explicitly described as following or preceding another step and / or where it is implicit that a step must follow or precede another step.

[0094] Herein, the term “RAT-independent sensor” (e.g., a RAT-independent radar sensor) refers to a sensor that performs sensing using RAT-independent signals. That is to say, the signals are used for sensing only, and not for communication. A radar sensor is an example of a RAT- independent sensor because it uses dedicated signals for sensing that are not used for communication of data. For example, pulse-shaped radar signals and continuous-wave radar signals are different to the sinusoidal reference signals used for communication purposes.

[0095] The term “RAT-dependent sensor” is a sensor that performs sensing using RAT-dependent signals, i.e., signals that are part of the RAT communication network / can be used for communication. The RAT-dependent sensor could be a UE or any other network node that is configured to communicate within a RAT communication network.

[0096] A network node that is configured to communicate within a RAT communication network is referred to herein as a Radio Access Network (RAN) node. A RAN node may include, for example, any one or more of: a base station, a gNB, a gNB-Centralized Unit (gNB-CU), a gNB- Distributed Unit (gNB-DU), a 6G base station, and a core network node.

[0097] The term “sensing” may refer to detecting or measuring spatial and / or movement information associated with an object. Spatial and / or movement information may comprise information relating to or comprising any one or more of the following properties of a target object: its position / location, its speed, its direction of travel, and its velocity, its acceleration. For example, the spatial and / or movement may comprise Doppler measurements, which can be used to determine the speed or velocity of a target object.

[0098] The terms “sensor” and “sensing unit” may be used interchangeably.

[0099] Sensing terminology is to be understood as follows:

[0100] • A sensing consumer is an entity that receives a sensing result. Usually, an application or network function that has requested the sensing also receives the results, but it may not be the case in every scenario.

[0101] • A sensing requester is an entity that requests sensing. This may be the same entity as the sensing consumer. • Sensing information can be any information describing sensing measurements, its metadata, partially processed data or sensing results.

[0102] • A RAT-dependent sensing unit is a radio unit or radio node capable of at least one of: transmitting radio signals for sensing, receiving radio signals for sensing, processing of radio signals for sensing, performing sensing measurements, etc. A sensing unit may be equipped with or connected to one or more internal or external antennas or antenna panels directly or via one or more external devices (e.g., Rx amplifier, Low Noise Amplifier, LNA, directional coupler, antenna sharing combiner or coupler, Rx filter, Tx filter, Rx / Tx filter, etc.) or may share antennas with other nodes (e.g., with BS or gNB, UE). The sharing may be, e.g., via antenna sharing combiner or coupler. A sensing unit may be a standalone node, may be integrated into a BS or another radio node (including UE), may be co-located with another radio node, or may be co-sited with another radio node sharing the radio facilities at the same site. Examples of sensing units include a standalone sensing unit, a transmission point (TP), a reception point (RP), a transmission and reception point (TRP), a functional block or unit for sensing, a base station (BS), a gNB, a radio network node, and a UE.

[0103] • A sensing client is an entity that interacts with a 3GPP defined node for the purpose of obtaining location information for a certain area, or for one or more UEs. The Sensing Client may reside in the UE. Similar to location service client (LCS), sensing client can be external or within a UE or an application which requires sensing result from an area or from a specific object. The object may be an object that can be connected (i.e., an active object e.g., with sim card cellular connectivity) or a passive object (without any connectivity, e.g., no sim card).

[0104] • A sensing server is an entity which is able to produce the sensing outcome (final result) based upon the obtained raw measurements or baseband processed results or from other external sensors.

[0105] It is proposed herein to determine which sensing units to activate (or deactivate) based on a sensing quality assessment. An optimisation procedure may be performed to determine, based on the sensing quality assessment, which sensors should be used for sensing (e.g., by prioritising the use of RAT-independent sensors) whilst still maintaining a desired sensing quality level.

[0106] In some embodiments, it is proposed to introduce a new control function (or new functionality to an existing control function), referred to herein as a sensing management function (SeMF), and a new aggregation and processing function (or new functionality to an existing network function), referred to herein as a sensing processing function (SPF). The SeMF and the SPF may be separate entities (e.g., network nodes), or they may be comprised in the same entity (e.g., network node).

[0107] Figure 3 is a flow chart illustrating a method 300 performed by a first network node for managing sensing in a RAT communication network. The first network node may comprise a core network node for managing sensing. The first network node may comprise an SeMF.

[0108] The method 300 comprises, at step 302, obtaining a sensing quality assessment for one or more sensing measurements performed by a first set of sensing units for providing sensing. The first set of sensing units comprises at least one RAT-independent sensing unit. The sensing provided by the first set of sensing units may comprise sensing one or more first objects, e.g., sensing a specified object, or sensing a list of objects in a specified sensing area. The one or more first objects may be passive object(s).

[0109] The method further comprises, at step 304, performing, based on the sensing quality assessment, an optimization procedure to determine a second set of sensing units for providing the sensing (e.g., the sensing of the one or more first objects). The optimization procedure seeks to optimize a number of RAT-dependent sensing units comprised in the second set of sensing units subject to at least one constraint.

[0110] Seeking to optimize a number of RAT-dependent sensing units may comprise seeking to minimize the number of RAT-dependent sensing units comprised in the second set subject to the at least one constraint.

[0111] The sensing quality assessment obtained in step 302 may comprise an indication of whether the at least one constraint is satisfied by the one or more sensing measurements performed by the first set of sensing units.

[0112] The at least one constraint may comprise one or both of: a sensing requirement and a communication requirement. The sensing requirement may comprise a constraint on one or more of: sensing quality; sensing measurement speed; RAT-dependent resources used for sensing; a localization error for a target object (e.g., the first object); network latency; a false alarm occurrence rate; and a missed detection occurrence rate. The communication requirement may comprise a constraint on a communication rate. For example, the constraint on the communication rate may be to prevent the use of too many RAT-dependent resources for sensing causing a corresponding reduction in resources available for communication such that the data rate within the network is negatively impacted.

[0113] Seeking to optimize a number of RAT-dependent sensing units may, in general, comprise prioritizing the use of RAT-independent sensing resources over the use of RAT-dependent sensing resources to preserve RAT-dependent resources for communication purposes. However, in some embodiments, one of RAT-dependent resources and RAT-independent resources may be prioritized over the other based on sensing measurement speed, e.g., if the sensing measurement response time is critical (short). For example, the at least one constraint may comprise a constraint on the sensing measurement speed, e.g., a minimum speed. Which of the RAT-dependent resources and RAT-independent resources are prioritised will, in this instance, depend on which of the RAT-dependent resources and the RAT-independent resources are faster. For example, if sensing measurement response time is critical, the first network node (e.g., the SeMF) may prioritise use of certain RAT-dependent resources for sensing over certain RAT-independent resources responsive to identifying that those RAT- dependent measurements are faster than the RAT-independent measurements. Alternatively, it may be identified that the RAT-independent measurements are faster than the RAT- dependent measurements. In these instances, when the sensing measurement response time is critical (and thus a constraint on sensing measurement speed is implemented), the first network node (e.g., the SeMF) may prioritise RAT-independent measurements over the RAT- dependent measurements.

[0114] Performing the optimization procedure to determine the second set of sensing units may comprise determining to activate a sensing function of a first RAT-dependent sensing unit responsive to the obtained sensing quality assessment failing to satisfy a first constraint. The first constraint may correspond to the at least one constraint above. For example, the sensing quality assessment may indicate that the first constraint is not satisfied.

[0115] Performing the optimization procedure to determine a second set of sensing units may comprise determining to deactivate a sensing function of a second RAT-dependent sensing unit responsive to the obtained sensing quality assessment satisfying a second constraint. The second constraint may correspond to the at least one constraint above. For example, the sensing quality assessment may indicate that the second constraint is satisfied.

[0116] Performing the optimization procedure may be further based on a sensing capability of one or more available sensing units. The optimization procedure may be based on the one or more first objects and / or the area comprising the one or more first objects. The method 300 may further comprise, after determining the second set of sensing units (in step 304), initiating implementation of the second set of sensing units for providing the sensing. Initiating implementation of the second set of sensing units may comprise requesting activation of one or more sensing units comprised in the second set of sensing units and / or deactivation of one or more sensing units comprised in the first set of sensing units. Thus, implementation of the second set of sensing units may comprise changing a sensing configuration from the first set to the second set.

[0117] The at least one RAT-independent sensing unit may comprise one or more of: a radar sensor; a lidar sensor; a camera sensor; a pressure sensor; a motion sensor; an inertial measurement unit; and a health sensor.

[0118] The RAT-dependent sensing units to be optimized may comprise one or more of: a RAT- dependent sensing unit configured to perform sensing using uplink traffic; a RAT-dependent sensing unit configured to perform sensing using downlink traffic; and a RAT-dependent sensing unit configured to perform sensing using sidelink traffic.

[0119] The step 302 of obtaining the sensing quality assessment for the one or more sensing measurements performed by the first set of sensing units may comprise receiving the sensing quality assessment from a second network node in the RAT communication network. For example, the second network node may be an SPF. The SPF may be located at a core network node, a RAN node, or a sensing unit. The sensing quality assessment may be received with corresponding sensor information for the first set of sensing units. The sensor information may comprise one or more sensing measurement results for the one or more sensing measurements performed by the first set of sensing units. For example, the sensing measurements may be from camera sensors, motion sensors, heat sensors, etc. The sensing measurement may comprise one or more of: raw samples, a radio measurement, a timing measurement, a velocity measurement, a temperature measurement, and a sensing event indication such as a weather change or motion pattern change. The sensing quality assessment may be received with an associated confidence level (e.g., a value between 1 and 100).

[0120] Alternatively, step 302 of obtaining the sensing quality assessment may comprise receiving sensor information from one or more sensing units comprised in the first set; and determining the sensing quality assessment based on the received sensor information. In some of these embodiments, an SPF is located at (or comprised in) the first network node, and these receiving and determining steps are performed by the SPF. For example, the SPF located at the first network node may be configured to perform the method 400 described with respect to Fig. 4 below (or any of the individual steps therein).

[0121] The method 300 may comprise, prior to obtaining (at step 302) the sensing quality assessment for the one or more sensing measurements performed by the first set of sensing units, obtaining sensing capabilities of at least the sensing units comprised in the first set. The method 300 may further comprise, prior to obtaining (at step 300) the sensing quality assessment for the one or more sensing measurements performed by the first set of sensing units, determining the first set of sensing units based on the obtained sensing capabilities of at least the sensing units comprised in the first set; and initiating activation of the sensing units comprised in the first set. Initiating activation of the sensing units comprised in the first set may comprise transmitting, to a RAN node, a request to configure the sensing units comprised in the first set to perform sensing measurements.

[0122] Thus, the method 300 provides for dynamic adaptations of the sensing configuration in sensing units, based on an SeMF receiving sensing quality assessments and requesting the sensing units to adjust their configuration, thereby enabling better resource utilization in the network.

[0123] Figure 4 is a flow chart illustrating a method 400 performed by second network node in a RAT communication network. The second network node may comprise an SPF. For example, the second network node may be a core network node. The core network node may be a separate entity from the first network node of Fig. 3 or it may be comprised in the same node (e.g., a core network node acting as an SeMF and an SPF). Alternatively, the second network node may comprise a RAN node or a sensing unit (e.g., a UE or a RAN node).

[0124] The method 400 comprises, at step 402, obtaining sensor information for a first set of sensing units for providing sensing. The first set comprises at least one RAT-independent sensing unit. The sensor information may comprise one or more sensing measurement results for the one or more sensing measurements performed by the first set of sensing units. Determining (404) the sensing quality assessment based on the obtained sensor information may comprise performing an information fusion of at least one obtained sensing measurement result from a RAT-independent sensing unit and at least one obtained sensing measurement result from a RAT-dependent sensing unit. The fusion may be performed using one or more of the following sensor fusion techniques: a Kalman filter, Bayesian filter, Probabilistic Data Association, Particle filter, and Simultaneous localization and mapping (SLAM). The fusion may use machine learning (artificial intelligence) techniques to fuse measurements from different sensors. The information fusion may produce a sensing parameter such as a location, angle, range or velocity of a target object.

[0125] The method 400 further comprises, at step 404, determining, based on the obtained sensor information, a sensing quality assessment for one or more sensing measurements performed by the first set of sensing units.

[0126] Determining (step 404) the sensing quality assessment for the one or more sensing measurements performed by the first set of sensing units may be further based on one or both of: a sensing requirement and a communication requirement. The sensing requirement may comprise a constraint on one or more of: a localization error for a target object; network latency; a false alarm occurrence rate; and a missed detection occurrence rate. The communication requirement may comprise a constraint on a communication rate. Thus, the sensing quality assessment may provide an indication of whether the one or more sensing measurements satisfy one or more of these requirements.

[0127] Determining the sensing quality assessment for the first set may further comprise determining a confidence level associated with the sensing quality assessment.

[0128] In some embodiments, step 402 of obtaining the sensor information may comprise performing at least one of the one or more sensing measurements. For example, the second network node (e.g., SPF) may be located at a sensing unit (e.g., a UE or a RAN node).

[0129] In alternative embodiments, step 402 of obtaining the sensor information may comprise receiving the sensor information. For example, the sensor information may be received from the sensing units comprised in the first set; a RAN node in the RAT communication network (e.g., a RAN node acting as an intermediary); or a network node that is hosting one or more of the sensing units comprised in the first set (e.g., a RAN node or a UE).

[0130] The method 400 may further comprise sending the sensing quality assessment for the one or more sensing measurements performed by the first set of sensing units to a first network node, e.g., a Sensing Management Function (SeMF).

[0131] Figure 5 is a flow chart illustrating a method 500 performed by a RAN node in a RAT communication network. The method 500 comprises receiving, at step 502, sensing information for a first sensing unit comprised in a first set of sensing units. The first set of sensing units comprise at least one RAT-independent sensing unit.

[0132] The method 500 further comprises transmitting, at step 504, the sensing information to a second network node. The second network node may comprise an SPF. The SPF may be comprised in (or located at) a core network node; a RAN node; or a sensing unit.

[0133] The method 500 further comprises, after transmitting the sensing information, receiving, at step 506, a request to configure a second set of sensing units to perform sensing measurements; and configuring, at step 508, based on the request, the sensing units comprised in the second set of sensing units to perform sensing measurements.

[0134] Figure 6 is a flow chart illustrating a method 600 performed by a first sensing unit in a RAT communication network. The first sensing unit may comprise or be located at a UE or a RAN node.

[0135] The method 600 comprises at step 602 transmitting, to a first network node, one or more sensing capabilities of the first sensing unit. The first network node may be an SeMF.

[0136] The method 600 further comprises at step 604, after transmitting the one or more sensing capabilities, receiving an indication to perform sensing measurements; and at step 606 performing the sensing measurements.

[0137] The method may comprise transmitting sensor information for the first sensing unit to a RAN node in the RAT communication network. The sensor information may comprise a result of the sensing measurements.

[0138] Figure 7 is a signalling diagram illustrating sensing techniques according to some embodiments of the present disclosure. The signalling diagram illustrates signalling between one or more sensing units 702; a sensing management function 704; and a sensing processing function 706. The sensing unit(s) 702 comprise at least one RAT-independent sensing unit (such as a radar sensor), and optionally one or more RAT-dependent sensing units (such as a RAN node and / or a UE). Each of the at least one RAT-independent sensing unit(s) may be hosted in a RAN node or a UE. The sensing unit(s) 702 may be configured to perform the method 600 described with reference to Fig. 6. The SeMF 704 may be configured to perform the method 300 of Fig. 3, and the SPF 706 may be configured to perform the method 400 of Fig. 4.

[0139] According to the example illustrated in Fig. 7, the sensing unit(s) 702 transmit sensing measurement results to the SPF 706 in signal 708. Although not shown in Fig. 7, the sensing unit(s) 702 may be hosted by a RAN node or a UE. Furthermore, the measurement results may be sent via an intermediate RAN node. Thus, the SPF 706 obtains sensing results from at least one RAT-independent sensing unit. The SPF 706 may also receive sensing results from one or more RAT-dependent sensing units and fuse the measurement results from the RAT-independent sensing unit(s) with the measurement results from the RAT-dependent sensing unit(s). The information fusion may be performed using any sensor fusion technique, such as Kalman filters, Bayesian filters, Probabilistic Data Association, Particle filters, Simultaneous localization and mapping (SLAM), etc. The information fusion may produce a sensing parameter such as a location, angle, range or velocity of an object.

[0140] At step 710, the SPF 706 performs a quality assessment 710 based on the obtained sensing measurement results. The SPF quality assessment may be based on pre-configured levels that meet threshold levels of sensing quality (e.g., accuracy level). The SPF 706 may check that the quality of the sensing measurement results is at an acceptable level, e.g., that the results meet a sensing Quality of Service requested by a sensing client.

[0141] In signal 712, the SPF provides the quality assessment to the SeMF 704. The SeMF 704 determines, based on the quality assessment, whether sensing should continue, stop, or be further enhanced by activating more sensing units, e.g., to increase the level of accuracy. This is referred to herein as an optimization procedure. The SeMF 704 provides corresponding sensing configurations to the relevant sensing unit(s) in signal 714. For example, the SeMF 704 may determine that an improvement in sensing quality is required, and that RAT- dependent sensing units can help in improving the sensing measurement result. Thus, in signal 714, the SeMF 704 may trigger resource increase from those RAT-dependent sensing units (e.g., RAN nodes or lies) which have sensing capabilities. Alternatively, the SeMF 704 may determine that the sensing quality provided by RAT-independent sensing units is sufficient and therefore certain RAT-dependent sensing units are not required for sensing. Thus, in signal 714, the SeMF 704 may trigger a decrease in resource from those RAT-dependent sensing units (e.g., RAN nodes or lies).

[0142] The process of Fig. 7 may be repeated. In other words, after the sensing resource changes have been implemented in response to signal 714, updated measurement results may be transmitted to the SPF 706, and the SPF 706 may process these updated sensing measurement results. The SPF 706 can fuse the measurements obtained from RAT- dependent and RAT-independent sensing units and include a quality assessment to the report that is provided to SeMF 704. The SeMF 704 may also determine whether the sensing results are meaningful enough to be sent to the requesting client. The SeMF 704 may determine, based on the quality assessment, whether to increase or decrease certain sensing resources.

[0143] The SPF 706 may be part of a sensing unit or units 702. In such cases, the sensing unit(s) may process the measurements and provide the sensing measurement results together with the quality assessment of the sensing measurement results directly to the SeMF 704. The sensing unit, and collocated SPF, may be part of a UE or RAN node (e.g., gNB).

[0144] Although not shown in Fig. 7, the sensing unit(s) 702 may, prior to transmitting the measurement results in signal 708, transmit their sensing capabilities to the SeMF 704. For example, if a RAN node (or UE) is hosting a plurality of sensing units 702, the RAN node (or UE) may transmit the sensing capabilities of these sensing units 702. Upon receiving these sensing capabilities, the SeMF 704 may send a request to activate one or more of the sensing units 702 based on the sensing capabilities.

[0145] In some embodiments, the sensing units 702 to be activated may be selected based on targeted sensing measurements (e.g., shape, velocity, location, etc.).

[0146] In some embodiments, the sensing units 702 to be activated may be selected based on an area of interest. For example, the request sent by the SeMF 704 to activate one or more sensing units 702 may comprise a request to activate a list of sensing units in a specific sensing area (e.g., those in a specific cell identified by its cell ID). For example, each cell in a RAT communication network may have a number of sensing units deployed therein.

[0147] The SeMF 704 may indicate the type of sensor (e.g., camera sensor) to be activated in a given area or in a given list of cells. In that situation, all indicated cells will have to activate the sensors deployed therein of the indicated type (e.g., all camera sensors). The NG-RAN (or UE) may then configure the indicated sensing units in the indicated sensing area or cell(s) to start measuring sensing data according to the information received from SeMF 704. If the NG- RAN (or UE) hosts an SPF 706, then the NG-RAN (or UE) may set up the its integrated SPF 706 to start collecting sensing measurement results (i.e. , signal 708 of Fig. 7). After obtaining a first report of sensing measurement results (signal 708), the SPF 706 may apply its filtering algorithms to fuse measurement results from different sensors. The SPF 706 may then provide a quality assessment to the SeMF 704. If the SeMF 704 upon receiving the Quality assessment considers it is needed to improve the results, the SeMF may request (signal 714) the NG-RAN (or UE) to activate more sensing units in the indicated cell or list of cells, e.g., by sending an update message for the sensing measurement. Possibly, the SeMF 704 can recommend a sensing configuration to be adopted by the sensing units.

[0148] The SeMF 704 may, based on the SPF’s quality assessment, request (signal 714) the NG- RAN (or UE) to deactivate some sensing units in an indicated area (cell or list of cells), e.g., by sending an update message.

[0149] Figure 8 is a signalling diagram illustrating embodiments of the present disclosure in which the sensing processing function is located in the RAN network, e.g., hosted by a RAN node or a UE. Figure 8 is described for the case in which the SPF is hosted by a RAN node, but the RAN node can be replaced by a UE without loss of generality.

[0150] In signal 801 , the SeMF 860 transmits a sensing measurement request to the RAN node (gNB- CU 850) comprising a request to activate SU1 and SU2 in cell 1 and SU3 in cell 2.

[0151] At step 802, the RAN node performs the sensing configuration. The SPF 840 is set up by the gNB-CU 850 (steps 803 and 804) to receive the large amount of sensing data collected from the SUs 830.

[0152] At step 805, the SUs 830 perform the sensing measurements and transmits the measurements to the SPF 840 in signal 806. At step 807, the SPF 840 processes the raw data and applies a sensor fusion algorithm (e.g., filtering algorithm) to compute the measurement results and corresponding quality assessment.

[0153] In signal 808, the SPF 840 sends the measurement report and corresponding quality assessment to the SeMF 860. The SeMF 860 may decide to request the RAN to update the sensing configurations of the SUs 830, such as sensing beams to be reconfigured at one or more of the SUs 830.

[0154] In some embodiments, the SPF 840 may be collocated with the SUs 830 and update the SUs 830 directly. Figure 9 is a signalling diagram illustrating embodiments of the present disclosure in which one entity handles both the control of the Sils and the configuration of the sensing beams based on the quality assessment. For example, the SeMF and SPF may be collocated. Figure 9 is described for the case in which SPF is collocated with the SeM F in the core network. Thus, the process and sensor fusion process is handled by one central core entity.

[0155] Figure 9 depicts signalling between a first RAN node 930 with a first list of Sils, a second RAN node 940 with a second list of Sils, and a core network node 950 that performs the function of the SeMF and SPF described herein. The signalling diagram also depicts a passive object 920 from which sensing measurements are to be collected.

[0156] At step 901 , the RAN nodes 930, 940 exchange RAN sensing capabilities with the SeMF / SPF 950. The SeMF / SPF 950 transmits a sensing measurement request to the second RAN node (signal 902) and the first RAN node (signal 903) comprising a request to activate certain Sils in certain cells for sensing of the passive object 920. The RAN nodes 930, 940 perform the configuration and activation of the indicated Sils in steps 904 and 905.

[0157] At step 906, the RAN nodes 930, 940 collect sensing measurements for the passive object 920, e.g., one or more of the velocity, location, shape, movement, heat, etc. of the passive object 920.

[0158] In signals 907 and 908, the RAN nodes 930, 940 transmit feedback on the sensing measurements (e.g., sensing measurement results) to the SeMF / SPF 950.

[0159] At step 909, the SeMF / SPF 950 performs a quality assessment of the received feedback and determines, based on the quality assessment, which Sils to activate and / or which Sils to deactivate. The SeMF / SPF 950 then transmits signal 910 to the second RAN node and signal 911 to the first RAN node, where each signal comprises an updated request to activate certain Sll(s) in one or more cells and / or deactivate Sll(s) in other cell(s).

[0160] Figures 10A, 10B, and 10C are schematics that illustrate various embodiments of the present disclosure for the optimisation of network resources.

[0161] Figure 10B demonstrates how the techniques disclosed herein may be used to optimise uplink (UL) resources. Figure 10A depicts a base station (BS) 1002, a UE 1004, and a sensing target 1008. The UE 1004 is equipped with onboard sensor(s) 1006 (e.g., camera, lidar, etc.) that can sense the environment around the UE 1004 and can be used to improve sensing of a target (e.g., the sensing target 1008 shown in Fig. 10A). Thus, the RAT-dependent sensors (UE 1004) and the RAT-independent sensors (onboard sensor 1006) of Fig. 10A are located at the same node.

[0162] As already discussed, the sensing processing (i.e. , the functionality associated with the SPF) may be performed at a RAN node or UE (e.g., at gNB SPF or UE SPF). Figure 10A depicts a scenario in which the sensing processing is performed at the base station 1002. Thus, as shown in Figure 10A, the UE 1004 may use UL network resources to send communication signals to the BS 1002. The UE 1004 may also use UL network resources for transmitting sensing signals that are reflected off the sensing target 1008 (RAT-dependent sensing), i.e., the BS 1002 may act as the sensing receiver. Finally, the UE 1004 may use UL network resources to send sensor information (e.g., reporting of onboard sensor measurements / data) to the BS 1002. Thus, the UE 1004 is configured to share its transmitter / receiver resources between communication, sensing, and reporting of onboard sensor measurements / data.

[0163] According to the techniques described herein, these UL network resources may be saved by disabling the use of the UE’s RAT-dependent UL resources for sensing when the RAT- independent sensor measurement reports meet the needed sensing measurement quality. Thus, the Ues UL network resources (i.e., RAT-dependent resources) can instead be reserved for communication purposes.

[0164] In further embodiments, the use of the UE’s RAT-dependent UL resources for sensing may be configured based on a quality assessment. The quality assessment may be determined by the network (e.g., an SPF) based on the sensor information (e.g., RAT-independent sensor measurement reports) for the UE 1004. An SeMF may perform an optimization procedure based on the sensing quality assessment to determine which sensing units to activate / deactivate (i.e., which network resources to use for sensing).

[0165] For the scenario in which the SPF is located at (e.g., hosted by) the UE 1004, the UE 1004 may not send the measurement report to the network but may simply send an indication that the current measurements obtained from the RAT-independent sensors are adequate and hence the UL cellular resources can be disabled for sensing purposes (and thus reserved for communication purposes). However, if the RAT-independent measurement quality or confidence level deteriorates, then the UE 1004 may request that RAT-dependent resources are made available for sensing. Thus, an optimization procedure (e.g., the optimization procedure described in step 304 of Fig. 3) may, in this scenario, be performed by the UE 1004. The quality assessment and / or the optimization procedure may be based on communication requirements (e.g., communication rates) and / or sensing requirements (e.g., target localization error, latency, false alarm / missed detection).

[0166] The quality assessment may also have an associated confidence level (or uncertainty). For example, the confidence level may be a value between 1 and 100, where 100 implies that the measurements have the highest confidence level (or very low uncertainty). It will be appreciated that alternative means of expressing a confidence level or uncertainty are possible.

[0167] In some embodiments, the network may ask the UE 1004 to configure the sensing signals (e.g., those shown to reflect off the sensing target 1008 in Fig. 10A) and the sensor information signals by privileging one or the other in order to reach a sensing requirement (target’s localization error, latency, etc). The sensor information reports may be part of the communication resources (e.g., signals containing data that needs to be decoded), and / or they may comprise actual sensor measurements. The sensor information reports may include estimated (at the UE) target’s parameters based on the sensor measurements.

[0168] Figure 10B demonstrates how the techniques disclosed herein may be used to optimise downlink (DL) resources. Figure 10B depicts the same entities as Figure 10A: a base station (BS) 1002, a UE 1004, and a sensing target 1008. The UE 1004 is again equipped with onboard sensor(s) 1006 (e.g., camera, lidar, etc.) that can sense the environment around the UE 1004 and can be used to improve sensing of a target (e.g., the sensing target 1008 shown in Fig. 10B). Thus, the RAT-dependent sensors (UE 1004) and the RAT-independent sensors (onboard sensor 1006) of Fig. 10B are again located at the same node.

[0169] As shown in Figure 10B, the UE 1004 may use DL network resources to receive communication signals from the BS 1002. The UE 1004 may also use DL network resources for receiving sensing signals that are reflected off the sensing target 1008 (RAT-dependent sensing), i.e. , the UE 1004 may act as the sensing receiver and the sensing processing may be performed based on DL signals. In this scenario, some sensing-related information fusion may be performed by the UE. Thus, the UE 1004 is configured to share its DL network resources between communication and sensing.

[0170] The optimization procedure used to determine the UE resource configuration (e.g., which sensing units to activate or deactivate / which DL network resources to use) may be based on the sensor information reports (e.g., their periodicity), communication requirements and / or sensing requirements. The resource configuration may be determined such that DL resources are reserved for communication purposes and only used for RAT-dependent sensing when the available RAT-independent sensors are insufficient (e.g., do not provide a required sensing quality). Thus, DL RAT-dependent radio resource is disabled for sensing when the RAT- independent sensor measurement reports meet the needed sensing measurement quality.

[0171] When some part of the information fusion is performed at the UE, the network may ask the UE to report some sensor information, such as relative target position as sensed by the sensor (instead of an entire measurement report).

[0172] Figure 10C demonstrates how the techniques disclosed herein may be used to optimise sidelink (SL) resources. Figure 10C depicts the same entities as Figure 10A: a base station (BS) 1002, a first UE 1004, and a sensing target 1008. The first UE 1004 is again equipped with onboard sensor(s) 1006 (e.g., camera, lidar, etc.) that can sense the environment around the first UE 1004 and can be used to improve sensing of a target (e.g., the sensing target 1008 shown in Fig. 10C). Figure 10C also depicts a second UE 1010.

[0173] As shown in Figure 10C, the first UE 1004 may share its transmitter / receiver resources between SL communication (e.g., with the second UE 1010), Uu communication (e.g., with the base station 1002), and sensing (e.g., sensing signals for sensing the sensing target 1008).

[0174] According to the techniques disclosed herein, the first UE 1004 may to optimize resources between SL communication, Uu communication, and sensing. For example, RAT-dependent radio resources for sensing may be disabled when the RAT-independent sensor measurement report meets the needed sensing measurement quality. Furthermore, RAT-dependent radio resources for sensing may be configured based on a quality assessment at the network which is obtained based on the RAT-independent sensor measurement reports through the Uu link.

[0175] Figure 11 is a schematic illustrating the optimization techniques disclosed herein according to some embodiments.

[0176] As illustrated in Figure 11 , the network 1102 configures a variety of sensing units 1110, 1120, 1130, 1140 to perform sensing, e.g., of a target object. The network 1102 may also obtain capabilities of the sensing units 1110, 1120, 1130, 1140 as well as sensing measurement results. The network 1102 performs an optimization procedure that seeks to optimize a number of RAT-dependent sensing units used for sensing, e.g., for sensing a first object. For example, the optimization procedure may seek to minimize the number of RAT-dependent sensing units being used subject to a constraint on sensing quality. Thus, at 1104, the network 1102 considers whether there are enough RAT-independent sensors available. If there are (yes, Y), then fewer radio sensing beams are enabled at step 1106. If there are not (no, N), then more radio sensing beams are enabled at step 1108 to ensure that the required sensing quality is met.

[0177] Figure 12 illustrates an example of how an SeMF 1208 and an SPF 1210 could be incorporated into 3GPP positioning architecture according to some embodiments of the present disclosure. Fig. 12 shows the SeMF 1208 and SPF 1210 incorporated into the schematic of Fig. 2.

[0178] The SeMF 1208 may be configured to perform the method 300 of Fig. 3. The SPF 1210 may be configured to perform the method 400 of Fig. 4.

[0179] The SeMF 1208 may be configured to extract information, such as information about which network nodes (e.g., gNBs, sensing units, etc.) could and / or should enable (or disable) the sensing function. If requests come from multiple sources, the SeMF 1208 may enable the reuse of sensing information. It should be able to orchestrate collection of measurements from multiple gNBs towards the SPF 1210. The SeMF 1208 may also provide sensing configuration (e.g., patterns for transmission or reception of reference signals for sensing) to the radio nodes (e.g., gNBs, sensing nodes, etc.), or collaborate with the radio nodes (e.g., gNBs, sensing nodes, etc.), to configure or coordinate transmissions and / or receptions of the necessary radio signals, avoid interference, etc.

[0180] Figure 13 is a schematic illustrating an example of the role of the SeMF (i.e., the sensing control function). The SeMF 1308 is configured to receive a sensing request 1310. Based on the sensing request 1310, the SeMF provides sensing configurations 1312, 1314, 1316 to sensing units 1302, 1304 and 1306 respectively. The sensing configurations 1312, 1314, 1316 define patterns for transmission or reception of reference signals for sensing, where 0 implies OFF and 1 implies ON.

[0181] Figure 14 is a schematic illustrating an example of the role of the SPF (the aggregation and processing function). The SPF 1408 is configured to receive raw data or measurement data 1412, 1414 and 1416 from the sensing units 1302, 1304 and 1306. Sensing data, when produced by radio sensing units (e.g., integrated in RAN nodes such as gNBs), may comprise reported sensing events, radio measurements, and / or raw radio sample data which may not be useful for external applications.

[0182] The SPF 1408 is further configured to process the received data 1412, 1414 and 1416 to provide processed data 1410. Thus, the raw data may be processed or converted into processed data (which may also include sensing events) to provide a more meaningful interpretation. The processed data 1410 may comprise spatial and / or movement information, such as an object’s position / location, speed and / or direction of movement.

[0183] Figure 15 shows an example of a communication system 1500 in accordance with some embodiments.

[0184] In the example, the communication system 1500 includes a telecommunication network 1502 that includes an access network 1504, such as a radio access network (RAN), and a core network 1506, which includes one or more core network nodes 1508. The access network 1504 includes one or more access network nodes, such as network nodes 1510a and 1510b (one or more of which may be generally referred to as network nodes 1510), or any other similar 3rdGeneration Partnership Project (3GPP) access nodes or non-3GPP access points. 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 1502 includes one or more Open-RAN (ORAN) network nodes. An ORAN network node is a node in the telecommunication network 1502 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 1502, including one or more network nodes 1510 and / or core network nodes 1508.

[0185] Examples of an ORAN network node include an open radio unit (0-Rll), 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 A1 , F1 , W1 , E1 , 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 O-RAN Alliance or comparable technologies. The network nodes 1510 facilitate direct or indirect connection of user equipment (UE), such as by connecting lies 1512a, 1512b, 1512c, and 1512d (one or more of which may be generally referred to as Ues 1512) to the core network 1506 over one or more wireless connections.

[0186] 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 1500 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 1500 may include and / or interface with any type of communication, telecommunication, data, cellular, radio network, and / or other similar type of system.

[0187] The Ues 1512 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 1510 and other communication devices. Similarly, the network nodes 1510 are arranged, capable, configured, and / or operable to communicate directly or indirectly with the Ues 1512 and / or with other network nodes or equipment in the telecommunication network 1502 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 1502.

[0188] In the depicted example, the core network 1506 connects the network nodes 1510 to one or more hosts, such as host 1516. 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 1506 includes one more core network nodes (e.g., core network node 1508) 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 1508. 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 (ALISF), 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).

[0189] The host 1516 may be under the ownership or control of a service provider other than an operator or provider of the access network 1504 and / or the telecommunication network 1502, and may be operated by the service provider or on behalf of the service provider. The host 1516 may host a variety of applications to provide one or more services. Examples of such applications include the provision of live and / or pre-recorded audio / video content, data collection services, for example, 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.

[0190] As a whole, the communication system 1500 of Figure 15 enables connectivity between the Ues, network nodes, and hosts. In that sense, the communication system 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 2G, 3G, 4G, 5G standards, or any applicable future generation standard (e.g., 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.

[0191] In some examples, the telecommunication network 1502 is a cellular network that implements 3GPP standardized features. Accordingly, the telecommunications network 1502 may support network slicing to provide different logical networks to different devices that are connected to the telecommunication network 1502. For example, the telecommunications network 1502 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 loT services to yet further Ues. In some examples, the lies 1512 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 1504 on a predetermined schedule, when triggered by an internal or external event, or in response to requests from the access network 1504. Additionally, a UE may be configured for operating in single- or multi-RAT or multi-standard mode. For example, a UE may operate with any one or combination of Wi-Fi, NR (New Radio) and LTE, i.e. being configured for multi-radio dual connectivity (MR-DC), such as E-UTRAN (Evolved-UMTS Terrestrial Radio Access Network) New Radio - Dual Connectivity (EN-DC).

[0192] In the example illustrated in Figure 15, the hub 1514 communicates with the access network 1504 to facilitate indirect communication between one or more Ues (e.g., UE 1512c and / or 1512d) and network nodes (e.g., network node 1510b). In some examples, the hub 1514 may be a controller, router, a content source and analytics node, or any of the other communication devices described herein regarding Ues. For example, the hub 1514 may be a broadband router enabling access to the core network 1506 for the UEs. As another example, the hub 1514 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 1510, or by executable code, script, process, or other instructions in the hub 1514. As another example, the hub 1514 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 1514 may be a content source. For example, for a UE that is a VR headset, display, loudspeaker or other media delivery device, the hub 1514 may retrieve VR assets, video, audio, or other media or data related to sensory information via a network node, which the hub 1514 then provides to the UE either directly, after performing local processing, and / or after adding additional local content. In still another example, the hub 1514 acts as a proxy server or orchestrator for the Ues, in particular if one or more of the UEs are low energy loT devices.

[0193] The hub 1514 may have a constant / persistent or intermittent connection to the network node 1510b. The hub 1514 may also allow for a different communication scheme and / or schedule between the hub 1514 and Ues (e.g., UE 1512c and / or 1512d), and between the hub 1514 and the core network 1506. In other examples, the hub 1514 is connected to the core network 1506 and / or one or more Ues via a wired connection. Moreover, the hub 1514 may be configured to connect to an M2M service provider over the access network 1504 and / or to another UE over a direct connection. In some scenarios, Ues may establish a wireless connection with the network nodes 1510 while still connected via the hub 1514 via a wired or wireless connection. In some embodiments, the hub 1514 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 1510b. In other embodiments, the hub 1514 may be a non-dedicated hub - that is, a device which is capable of operating to route communications between the lies and network node 1510b, but which is additionally capable of operating as a communication start and / or end point for certain data channels.

[0194] Figure 16 shows a network node 1600 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. The network node 1600 may be operable as a core network node, a core network function or, more generally, a core network entity, such as the core network node 1508 described above with respect to Figure 15). Examples of network nodes in this context include core network entities such as 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), Policy Control Function (PCF) and / or a User Plane Function (UPF).

[0195] The network node 1600 includes processing circuitry 1602, a memory 1604, a communication interface 1606, and a power source 1608, and / or any other component, or any combination thereof. The network node 1600 may be composed of multiple physically separate components, which may each have their own respective components. In certain scenarios in which the network node 1600 comprises multiple separate components, one or more of the separate components may be shared among several network nodes.

[0196] The processing circuitry 1602 may comprise a combination of one or more of a microprocessor, controller, microcontroller, central processing unit, digital signal processor, application-specific integrated circuit, field programmable gate array, 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 1600 components, such as the memory 1604, network node 1600 functionality. For example, the processing circuitry 1602 may be configured to cause the network node 1600 to perform the methods as described with reference to Figures 3 or 4. The network node 1600 may correspond to the SeMF 860 described with reference to Figure 8. The network node 1600 may correspond to the SeMF / SPF 950 described with reference to Figure 9. The network node 1600 may correspond to the SeMF 1208 and / or the SPF 1210 of Fig. 12. The network node 1600 may correspond to the SeMF 1308 of Fig. 13 and / or the SPF 1408 of Fig. 14. The memory 1604 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, random access memory (RAM), read-only memory (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 1602. The memory 1604 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 1602 and utilized by the network node 1600. The memory 1604 may be used to store any calculations made by the processing circuitry 1602 and / or any data received via the communication interface 1606. In some embodiments, the processing circuitry 1602 and memory 1604 is integrated.

[0197] The communication interface 1606 is used in wired or wireless communication of signaling and / or data between a network node, access network, and / or UE.

[0198] The power source 1608 provides power to the various components of network node 1600 in a form suitable for the respective components (e.g., at a voltage and current level needed for each respective component). The power source 1608 may further comprise, or be coupled to, power management circuitry to supply the components of the network node 1600 with power for performing the functionality described herein. For example, the network node 1600 may be connectable to an external power source (e.g., the power grid, an electricity outlet) via an input circuitry or interface such as an electrical cable, whereby the external power source supplies power to power circuitry of the power source 1608. As a further example, the power source 1608 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.

[0199] Embodiments of the network node 1600 may include additional components beyond those shown in Figure 16 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 1600 may include user interface equipment to allow input of information into the network node 1600 and to allow output of information from the network node 1600. This may allow a user to perform diagnostic, maintenance, repair, and other administrative functions for the network node 1600.

[0200] Figure 17 shows a network node 1700 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, access points (Aps) (e.g., radio access points), base stations (BSs) (e.g., radio base stations, Node Bs, evolved Node Bs (eNBs) and NR NodeBs (gNBs)), O-RAN nodes or components of an O-RAN node (e.g., O-RU, O-DU, O-CU).

[0201] 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 O-RAN access node) and / or remote radio units (RRUs), sometimes referred to as Remote Radio Heads (RRHs). Such remote radio units 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).

[0202] 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 base station controllers (BSCs), base transceiver stations (BTSs), transmission points, transmission nodes, multi-cell / multlSACt 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).

[0203] The network node 1700 includes processing circuitry 1702, a memory 1704, a communication interface 1706, and a power source 1708, and / or any other component, or any combination thereof. The network node 1700 may be composed of multiple physically separate components (e.g., a NodeB component and a 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 1700 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 1700 may be configured to support multiple radio access technologies (RATs). In such embodiments, some components may be duplicated (e.g., separate memory 1704 for different RATs) and some components may be reused (e.g., a same antenna 1710 may be shared by different RATs). The network node 1700 may also include multiple sets of the various illustrated components for different wireless technologies integrated into network node 1700, for example GSM, WCDMA, LTE, NR, WiFi, Zigbee, Z-wave, 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 network node 1700.

[0204] The processing circuitry 1702 may comprise a combination of one or more of a microprocessor, controller, microcontroller, central processing unit, digital signal processor, application-specific integrated circuit, field programmable gate array, 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 1700 components, such as the memory 1704, network node 1700 functionality. For example, the processing circuitry 1702 may be configured to cause the network node to perform the method 500 described with reference to Figure 5 and / or the method 600 described with respect to Figure 6. The network node 1700 may host the sensing unit(s) 702 described with respect to Figure 7. The network node 1700 may host the sensing unit(s) 830 of Figure 8 and / or the sensing units 930, 940 described with respect to Figure 9. The network node 1700 may host any of the sensing units 1302, 1304, 1306 of Figures 13 and 14.

[0205] In some embodiments, the processing circuitry 1702 includes a system on a chip (SOC). In some embodiments, the processing circuitry 1702 includes one or more of radio frequency (RF) transceiver circuitry 1712 and baseband processing circuitry 1714. In some embodiments, the radio frequency (RF) transceiver circuitry 1712 and the baseband processing circuitry 1714 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 RF transceiver circuitry 1712 and baseband processing circuitry 1714 may be on the same chip or set of chips, boards, or units.

[0206] The memory 1704 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, random access memory (RAM), read-only memory (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 1702. The memory 1704 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 1702 and utilized by the network node 1700. The memory 1704 may be used to store any calculations made by the processing circuitry 1702 and / or any data received via the communication interface 1706. In some embodiments, the processing circuitry 1702 and memory 1704 is integrated.

[0207] The communication interface 1706 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 1706 comprises port(s) / terminal(s) 1716 to send and receive data, for example to and from a network over a wired connection. The communication interface 1706 also includes radio front-end circuitry 1718 that may be coupled to, or in certain embodiments a part of, the antenna 1710. Radio front-end circuitry 1718 comprises filters 1720 and amplifiers 1722. The radio front-end circuitry 1718 may be connected to an antenna 1710 and processing circuitry 1702. The radio front-end circuitry may be configured to condition signals communicated between antenna 1710 and processing circuitry 1702. The radio front-end circuitry 1718 may receive digital data that is to be sent out to other network nodes or lies via a wireless connection. The radio front-end circuitry 1718 may convert the digital data into a radio signal having the appropriate channel and bandwidth parameters using a combination of filters 1720 and / or amplifiers 1722. The radio signal may then be transmitted via the antenna 1710. Similarly, when receiving data, the antenna 1710 may collect radio signals which are then converted into digital data by the radio front-end circuitry 1718. The digital data may be passed to the processing circuitry 1702. In other embodiments, the communication interface may comprise different components and / or different combinations of components.

[0208] In certain alternative embodiments, the network node 1700 does not include separate radio front-end circuitry 1718, instead, the processing circuitry 1702 includes radio front-end circuitry and is connected to the antenna 1710. Similarly, in some embodiments, all or some of the RF transceiver circuitry 1712 is part of the communication interface 1706. In still other embodiments, the communication interface 1706 includes one or more ports or terminals 1716, the radio front-end circuitry 1718, and the RF transceiver circuitry 1712, as part of a radio unit (not shown), and the communication interface 1706 communicates with the baseband processing circuitry 1714, which is part of a digital unit (not shown).

[0209] The antenna 1710 may include one or more antennas, or antenna arrays, configured to send and / or receive wireless signals. The antenna 1710 may be coupled to the radio front-end circuitry 1718 and may be any type of antenna capable of transmitting and receiving data and / or signals wirelessly. In certain embodiments, the antenna 1710 is separate from the network node 1700 and connectable to the network node 1700 through an interface or port.

[0210] The antenna 1710, communication interface 1706, and / or the processing circuitry 1702 may Be configured to perform any receiving operations and / or certain obtaining operations described herein as being performed by the network node. Any information, data and / or signals may be received from a UE, another network node and / or any other network equipment. Similarly, the antenna 1710, the communication interface 1706, and / or the processing circuitry 1702 may be configured to perform any transmitting operations described herein as being performed by the network node. Any information, data and / or signals may be transmitted to a UE, another network node and / or any other network equipment.

[0211] The power source 1708 provides power to the various components of network node 1700 in a form suitable for the respective components (e.g., at a voltage and current level needed for each respective component). The power source 1708 may further comprise, or be coupled to, power management circuitry to supply the components of the network node 1700 with power for performing the functionality described herein. For example, the network node 1700 may be connectable to an external power source (e.g., the power grid, an electricity outlet) via an input circuitry or interface such as an electrical cable, whereby the external power source supplies power to power circuitry of the power source 1708. As a further example, the power source 1708 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.

[0212] Embodiments of the network node 1700 may include additional components beyond those shown in Figure 17 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 1700 may include user interface equipment to allow input of information into the network node 1700 and to allow output of information from the network node 1700. This may allow a user to perform diagnostic, maintenance, repair, and other administrative functions for the network node 1700. Figure 18 shows a UE 1800 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 lies. Examples of a UE include, but are not limited to, a smart phone, mobile phone, cell phone, voice over IP (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 3rdGeneration Partnership Project (3GPP), including a narrow band internet of things (NB-loT) UE, a machine type communication (MTC) UE, and / or an enhanced MTC (eMTC) UE.

[0213] A UE may support device-to-device (D2D) communication, for example by implementing a 3GPP standard for sidelink communication, Dedicated Short-Range Communication (DSRC), vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), orvehicle-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).

[0214] The UE 1800 includes processing circuitry 1802 that is operatively coupled via a bus 1804 to an input / output interface 1806, a power source 1808, a memory 1810, a communication interface 1812, and / or any other component, or any combination thereof. Certain uEs may utilize all or a subset of the components shown in Figure 18. 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.

[0215] The processing circuitry 1802 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 1810. The processing circuitry 1802 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 1802 may include multiple central processing units (CPUs). The processing circuitry 1802 may be operable to provide, either alone or in conjunction with other UE 1800 components, such as the memory 1810, UE 1800 functionality. For example, the processing circuitry 1802 may be configured to cause the UE 1802 to perform the methods as described with reference to Figure 6. The UE 1800 may host the sensing unit(s) 702 described with respect to Figure 7. The UE 1800 may host the sensing unit(s) 830 of Figure 8 and / or the sensing units 930, 940 described with respect to Figure 9. The UE 1800 may correspond to the UE 206 of Figure 12 and / or the UE 1512A, 1512B of Figure 15. The UE 1800 may host any of the sensing units 1302, 1304, 1306 of Figures 13 and 14.

[0216] In the example, the input / output interface 1806 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 1800. 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.

[0217] In some embodiments, the power source 1808 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 1808 may further include power circuitry for delivering power from the power source 1808 itself, and / or an external power source, to the various parts of the UE 1800 via input circuitry or an interface such as an electrical power cable. Delivering power may be, for example, for charging of the power source 1808. Power circuitry may perform any formatting, converting, or other modification to the power from the power source 1808 to make the power suitable for the respective components of the UE 1800 to which power is supplied. The memory 1810 may be or be configured to include memory such as random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic disks, optical disks, hard disks, removable cartridges, flash drives, and so forth. In one example, the memory 1810 includes one or more application programs 1814, such as an operating system, web browser application, a widget, gadget engine, or other application, and corresponding data 1816. The memory 1810 may store, for use by the UE 1800, any of a variety of various operating systems or combinations of operating systems.

[0218] The memory 1810 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 random access memory (SDRAM), external micro-DIMM SDRAM, smartcard memory such as tamper resistant module in the form of a universal integrated circuit card (UICC) including one or more subscriber identity modules (SIMs), such as a USIM and / or ISIM, other memory, or any combination thereof. The UICC may for example be an embedded UICC (eUlCC), integrated UICC (iUICC) or a removable UICC commonly known as ‘SIM card.’ The memory 1810 may allow the UE 1800 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 1810, which may be or comprise a device-readable storage medium.

[0219] The processing circuitry 1802 may be configured to communicate with an access network or other network using the communication interface 1812. The communication interface 1812 may comprise one or more communication subsystems and may include or be communicatively coupled to an antenna 1822. The communication interface 1812 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 1818 and / or a receiver 1820 appropriate to provide network communications (e.g., optical, electrical, frequency allocations, and so forth). Moreover, the transmitter 1818 and receiver 1820 may be coupled to one or more antennas (e.g., antenna 1822) and may share circuit components, software or firmware, or alternatively be implemented separately.

[0220] In some embodiments, communication functions of the communication interface 1812 may include cellular communication, Wi-Fi communication, LPWAN communication, data communication, voice communication, multimedia communication, short-range communications such as Bluetooth, near-field communication, 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 in according to one or more communication protocols and / or standards, such as IEEE 802.11 , Code Division Multiplexing Access (CDMA), Wideband Code Division Multiple Access (WCDMA), GSM, LTE, New Radio (NR), UMTS, WiMax, Ethernet, transmission control protocol / internet protocol (TCP / IP), synchronous optical networking (SONET), Asynchronous Transfer Mode (ATM), QUIC, Hypertext Transfer Protocol (HTTP), and so forth.

[0221] Regardless of the type of sensor, a UE may provide an output of data captured by its sensors, through its communication interface 1812, 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 18 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).

[0222] 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 controls a robotic arm performing a medical procedure according to the received input.

[0223] A UE, when in the form of an Internet of Things (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 devices which are or which are embedded in: a connected refrigerator or freezer, a TV, 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 Virtual Reality (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 on the intended application of the loT device in addition to other components as described in relation to the UE 1800 shown in Figure 18.

[0224] 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 such monitoring 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 3GPP NB-loT standard. In other scenarios, a UE may represent a vehicle, such as a car, a bus, a truck, a ship and an airplane, or other equipment that is capable of monitoring and / or reporting on its operational status or other functions associated with its operation.

[0225] 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.

[0226] Figure 19 shows a communication diagram of a host 1902 communicating via a network node 1904 with a UE 1906 over a partially wireless connection in accordance with some embodiments. Example implementations, in accordance with various embodiments, of the UE (such as a UE 1512A, 1512B of Figure 15 and / or UE 1800 of Figure 18), network node (such as network node 1510A, 1510B of Figure 15 and / or network node 1700 of Figure 17), and host (such as host 1516 of Figure 15 and / or host 1902 of Figure 19) discussed in the preceding paragraphs will now be described with reference to Figure 19. Embodiments of host 1902 include hardware, such as a communication interface, processing circuitry, and memory. The host 1902 also includes software, which is stored in or accessible by the host 1902 and executable by the processing circuitry. The software includes a host application that may be operable to provide a service to a remote user, such as the UE 1906 connecting via an over-the-top (OTT) connection 1950 extending between the UE 1906 and host 1902. In providing the service to the remote user, a host application may provide user data which is transmitted using the OTT connection 1950.

[0227] The network node 1904 includes hardware enabling it to communicate with the host 1902 and UE 1906. The connection 1960 may be direct or pass through a core network (like core network 1506 of Figure 15) and / or one or more other intermediate networks, such as one or more public, private, or hosted networks. For example, an intermediate network may be a backbone network or the Internet.

[0228] The UE 1906 includes hardware and software, which is stored in or accessible by UE 1906 and executable by the UE’s processing circuitry. The software includes a client application, such as a web browser or operator-specific “app” that may be operable to provide a service to a human or non-human user via UE 1906 with the support of the host 1902. In the host 1902, an executing host application may communicate with the executing client application via the OTT connection 1950 terminating at the UE 1906 and host 1902. In providing the service to the user, the UE's client application may receive request data from the host's host application and provide user data in response to the request data. The OTT connection 1950 may transfer both the request data and the user data. The UE's client application may interact with the user to generate the user data that it provides to the host application through the OTT connection 1950.

[0229] The OTT connection 1950 may extend via a connection 1960 between the host 1902 and the network node 1904 and via a wireless connection 1970 between the network node 1904 and the UE 1906 to provide the connection between the host 1902 and the UE 1906. The connection 1960 and wireless connection 1970, over which the OTT connection 1950 may be provided, have been drawn abstractly to illustrate the communication between the host 1902 and the UE 1906 via the network node 1904, without explicit reference to any intermediary devices and the precise routing of messages via these devices.

[0230] As an example of transmitting data via the OTT connection 1950, in step 1908, the host 1902 provides user data, which may be performed by executing a host application. In some embodiments, the user data is associated with a particular human user interacting with the UE 1906. In other embodiments, the user data is associated with a UE 1906 that shares data with the host 1902 without explicit human interaction. In step 1910, the host 1902 initiates a transmission carrying the user data towards the UE 1906. The host 1902 may initiate the transmission responsive to a request transmitted by the UE 1906. The request may be caused by human interaction with the UE 1906 or by operation of the client application executing on the UE 1906. The transmission may pass via the network node 1904, in accordance with the teachings of the embodiments described throughout this disclosure. Accordingly, in step 1912, the network node 1904 transmits to the UE 1906 the user data that was carried in the transmission that the host 1902 initiated, in accordance with the teachings of the embodiments described throughout this disclosure. In step 1914, the UE 1906 receives the user data carried in the transmission, which may be performed by a client application executed on the UE 1906 associated with the host application executed by the host 1902.

[0231] In some examples, the UE 1906 executes a client application which provides user data to the host 1902. The user data may be provided in reaction or response to the data received from the host 1902. Accordingly, in step 1916, the UE 1906 may provide user data, which may be performed by executing the client application. In providing the user data, the client application may further consider user input received from the user via an input / output interface of the UE 1906. Regardless of the specific manner in which the user data was provided, the UE 1906 initiates, in step 1918, transmission of the user data towards the host 1902 via the network node 1904. In step 1920, in accordance with the teachings of the embodiments described throughout this disclosure, the network node 1904 receives user data from the UE 1906 and initiates transmission of the received user data towards the host 1902. In step 1922, the host 1902 receives the user data carried in the transmission initiated by the UE 1906.

[0232] One or more of the various embodiments improve the performance of OTT services provided to the UE 1906 using the OTT connection 1950, in which the wireless connection 1970 forms the last segment.

[0233] In an example scenario, factory status information may be collected and analyzed by the host 1902. As another example, the host 1902 may process audio and video data which may have been retrieved from a UE for use in creating maps. As another example, the host 1902 may collect and analyze real-time data to assist in controlling vehicle congestion (e.g., controlling traffic lights). As another example, the host 1902 may store surveillance video uploaded by a UE. As another example, the host 1902 may store or control access to media content such as video, audio, VR or AR which it can broadcast, multicast or unicast to UEs. As other examples, the host 1902 may be used for energy pricing, remote control of non-time critical electrical load to balance power generation needs, location services, presentation services (such as compiling diagrams etc. from data collected from remote devices), or any other function of collecting, retrieving, storing, analyzing and / or transmitting data.

[0234] In some examples, a measurement procedure may be provided for the purpose of monitoring data rate, latency and other factors on which the one or more embodiments improve. There may further be an optional network functionality for reconfiguring the OTT connection 1950 between the host 1902 and UE 1906, in response to variations in the measurement results. The measurement procedure and / or the network functionality for reconfiguring the OTT connection may be implemented in software and hardware of the host 1902 and / or UE 1906. In some embodiments, sensors (not shown) may be deployed in or in association with other devices through which the OTT connection 1950 passes; the sensors may participate in the measurement procedure by supplying values of the monitored quantities exemplified above, or supplying values of other physical quantities from which software may compute or estimate the monitored quantities. The reconfiguring of the OTT connection 1950 may include message format, retransmission settings, preferred routing etc.; the reconfiguring need not directly alter the operation of the network node 1904. Such procedures and functionalities may be known and practiced in the art. In certain embodiments, measurements may involve proprietary UE signaling that facilitates measurements of throughput, propagation times, latency and the like, by the host 1902. The measurements may be implemented in that software causes messages to be transmitted, in particular empty or ‘dummy’ messages, using the OTT connection 1950 while monitoring propagation times, errors, etc.

[0235] Figure 20 is a block diagram illustrating a first network node 2000 according to some embodiments. The first network node 2000 comprises an obtaining module 2002 configured to obtain a sensing quality assessment for one or more sensing measurements for sensing one or more first objects, where the one or more sensing measurements are performed by a first set of sensing units comprising at least one RAT-independent sensing unit. The first network node 2000 further comprises a performing module 2004 configured to perform, based on the sensing quality assessment, an optimization procedure to determine a second set of sensing units for sensing the one or more first objects, where the optimization procedure seeks to optimize a number of RAT-dependent sensing units comprised in the second set subject to a constraint. The first network node 2000 may operate in the manner described herein in respect of a first network node or an SeMF. Figure 21 is a block diagram illustrating a second network node 2100 according to some embodiments. The second network node 2100 comprises an obtaining module 2102 configured to obtain sensor information for a first set of sensing units comprising at least one RAT-independent sensing unit. The second network node 2100 further comprises a determining module 2104 configured to determine, based on the obtained sensor information, a sensing quality assessment for one or more sensing measurements for sensing one or more first objects, where the one or more sensing measurements are performed by the first set of sensing units. The second network node 2100 may operate in the manner described herein in respect of a second network node or an SPF.

[0236] Figure 22 is a block diagram illustrating a RAN node 2200 according to some embodiments. The RAN node 2200 comprises a receiving module 2202, a transmitting module 2204, receiving module 2206, and a configuring module 2208. The receiving module 2202 is configured to receive sensing information for a first sensing unit comprised in a first set of sensing units, where the first set of sensing units comprises at least one RAT-independent sensing unit. The transmitting module 2204 is configured to transmit the sensing information to a second network node. The receiving module 2206 is configured to receive a request to configure a second set of sensing units to perform sensing measurements. The configuring module 2208 is configured to configure, based on the request, the sensing units comprised in the second configuration to perform sensing measurements.

[0237] Figure 23 is a block diagram illustrating a first sensing unit 2300 according to some embodiments. The first sensing unit 2300 comprises a transmitting module 2302, a receiving module 2304 and a performing module 2306. The transmitting module 2302 is configured to transmit, to a first network node, one or more sensing capabilities of the first sensing unit. The receiving module 2304 is configured to after transmitting the one or more sensing capabilities, receive an indication to perform sensing measurements. The performing module 2306 is configured to perform the sensing measurements.

[0238] There is provided a computer program product, embodied on a non-transitory machine- readable medium, comprising instructions which are executable by processing circuitry to cause the processing circuitry to perform at least part of the method described herein. There is provided a computer program product comprising a carrier containing instructions for causing processing circuitry to perform at least part of the method described herein. In some embodiments, the carrier can be any one of an electronic signal, an optical signal, an electromagnetic signal, an electrical signal, a radio signal, a microwave signal, or a computer- readable storage medium. It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design many alternative embodiments without departing from the scope of the appended claims. The word “comprising” does not exclude the presence of elements or steps other than those listed in a claim, “a” or “an” does not exclude a plurality, and a single processor or other unit may fulfil the functions of several units recited in the claims. Any reference signs in the claims shall not be construed so as to limit their scope.

Claims

CLAIMS1. A method (300) performed by a first network node for managing sensing in a Radio Access Technology, RAT, communication network, the method comprising: obtaining (302) a sensing quality assessment for one or more sensing measurements performed by a first set of sensing units for providing sensing, wherein the first set comprises at least one RAT-independent sensing unit; and performing (304), based on the sensing quality assessment, an optimization procedure to determine a second set of sensing units for providing the sensing, wherein the optimization procedure seeks to optimize a number of RAT-dependent sensing units comprised in the second set subject to at least one constraint.

2. The method of claim 1 , wherein the sensing provided by the first and second set of sensing units comprises sensing one or more first objects.

3. The method of claim 1 or 2, wherein the optimization procedure seeks to minimize the number of RAT-dependent sensing units comprised in the second set subject to the at least one constraint.

4. The method of any preceding claim, wherein the at least one constraint comprises one or both of: a sensing requirement and a communication requirement.

5. The method of claim 4, wherein the sensing requirement comprises a constraint on one or more of: sensing quality; RAT-dependent resources used for sensing; a localization error for a target object; network latency; a false alarm occurrence rate; and a missed detection occurrence rate.

6. The method of claim 4 or 5, wherein the communication requirement comprises a constraint on a communication rate.

7. The method of any preceding claim, wherein performing the optimization procedure to determine the second set of sensing units comprises: determining to activate a sensing function of a first RAT-dependent sensing unit responsive to the obtained sensing quality assessment failing to satisfy a first constraint.

8. The method of any preceding claim, wherein performing the optimization procedure to determine a second set of sensing units comprises:determining to deactivate a sensing function of a second RAT-dependent sensing unit responsive to the obtained sensing quality assessment satisfying a second constraint.

9. The method of any preceding claim, wherein performing the optimization procedure is further based on a sensing capability of one or more available sensing units.

10. The method of any preceding claim, further comprising: after determining the second set of sensing units, initiating implementation of the second set of sensing units for providing the sensing.

11. The method of claim 10, wherein initiating implementation of the second set of sensing units comprises requesting activation of one or more sensing units comprised in the second set and / or deactivation of one or more sensing units comprised in the first set.

12. The method of any preceding claim, wherein the at least one RAT-independent sensing unit comprises one or more of: a radar sensor; a lidar sensor; a camera sensor; a pressure sensor; a motion sensor; an inertial measurement unit; and a health sensor.

13. The method of any preceding claim, wherein the RAT-dependent sensing units to be optimized comprise one or more of: a RAT-dependent sensing unit configured to perform sensing using uplink traffic; a RAT-dependent sensing unit configured to perform sensing using downlink traffic; and a RAT-dependent sensing unit configured to perform sensing using sidelink traffic.

14. The method of any preceding claim, wherein obtaining the sensing quality assessment for the one or more sensing measurements performed by the first set of sensing units comprises receiving the sensing quality assessment from a second network node in the RAT communication network.

15. The method of claim 14, wherein the sensing quality assessment is received with corresponding sensor information for the first set of sensing units.

16. The method of any claim 15, wherein the sensor information comprises one or more sensing measurement results for the one or more sensing measurements performed by the first set of sensing units.

17. The method of any of claims 14-16, wherein the sensing quality assessment is received with an associated confidence level.

18. The method of any of claims 1-13, wherein obtaining the sensing quality assessment comprises: receiving sensor information from one or more sensing units comprised in the first set; and determining the sensing quality assessment based on the received sensor information.

19. The method of any preceding claim, wherein the method further comprises: prior to obtaining the sensing quality assessment for the one or more sensing measurements provided by the first set of sensing units, obtaining sensing capabilities of at least the sensing units comprised in the first set.

20. The method of claim 19, wherein the method further comprises: prior to obtaining the sensing quality assessment for the one or more sensing measurements provided by the first set of sensing units, determining the first set of sensing units based on the obtained sensing capabilities of at least the sensing units comprised in the first set; and initiating activation of the sensing units comprised in the first set.

21. The method of claim 20, wherein initiating activation of the sensing units comprised in the first set comprises: transmitting, to a Radio Access Network, RAN, node, a request to configure the sensing units comprised in the first set to perform sensing measurements.

22. A method (400) performed by a second network node in a radio access technology, RAT, communication network, the method comprising: obtaining (402) sensor information for a first set of sensing units for providing sensing, wherein the first set comprises at least one RAT-independent sensing unit; and determining (404), based on the obtained sensor information, a sensing quality assessment for one or more sensing measurements performed by the first set of sensing units.

23. The method of claim 22, wherein determining the sensing quality assessment for the one or more sensing measurements performed by the first set of sensing units is further based on one or both of: a sensing requirement and a communication requirement.

24. The method of claim 23, wherein the sensing requirement comprises a constraint on one or more of: a localization error for a target object; network latency; a false alarm occurrence rate; and a missed detection occurrence rate.

25. The method of any of claims 23-24, wherein the communication requirement comprises a constraint on a communication rate.

26. The method of any of claims 22-25, wherein determining the sensing quality assessment for the first set further comprises determining a confidence level associated with the sensing quality assessment.

27. The method of any of claims 22-26, wherein the sensor information comprises one or more sensing measurement results for the one or more sensing measurements performed by the first set of sensing units.

28. The method of claim 27, wherein determining the sensing quality assessment based on the obtained sensor information comprises performing an information fusion of at least one obtained sensing measurement result from a RAT-independent sensing unit and at least one obtained sensing measurement result from a RAT-dependent sensing unit.

29. The method of claim 27 or 28, wherein obtaining the sensor information comprises performing at least one of the one or more sensing measurements.

30. The method of claim 29, wherein the second network node is a user equipment, UE, or a Radio Access Network, RAN, node.

31. The method of any of claims 22-28, wherein obtaining the sensor information comprises receiving the sensor information.

32. The method of claim 31, wherein the sensor information is received from the sensing units comprised in the first set.

33. The method of any of claims 31-32, wherein the sensor information is received from a Radio Access Network, RAN, node in the RAT communication network.

34. The method of any of claims 22-33, further comprising: sending the sensing quality assessment for the one or more sensing measurements performed by the first set of sensing units to a first network node.

35. A method performed by a Radio Access Network, RAN, node in a Radio Access Technology, RAT, communication network, the method comprising: receiving (502) sensing information for a first sensing unit comprised in a first set of sensing units, wherein the first set of sensing units comprises at least one RAT- independent sensing unit; transmitting (504) the sensing information to a second network node; after transmitting the sensing information, receiving (506) a request to configure a second set of sensing units to perform sensing measurements; and configuring (508), based on the request, the sensing units comprised in the second set of sensing units to perform sensing measurements.

36. A method (600) performed by a first sensing unit in a radio access technology, RAT, communication network, the method comprising: transmitting (602), to a first network node, one or more sensing capabilities of the first sensing unit; after transmitting the one or more sensing capabilities, receiving (604) an indication to perform sensing measurements; and performing (606) the sensing measurements.

37. A first network node comprising processing circuitry and a memory, the memory containing instructions executable by the processing circuitry whereby the first network node is operable to: obtain a sensing quality assessment for one or more sensing measurements performed by a first set of sensing units for providing sensing, wherein the first set comprises at least one Radio Access Technology, RAT, independent sensing unit; and perform, based on the sensing quality assessment, an optimization procedure to determine a second set of sensing units for providing the sensing, wherein the optimization procedure seeks to optimize a number of RAT-dependent sensing units comprised in the second set subject to at least one constraint.

38. The first network node as claimed in claim 37 wherein the memory further contains instructions executable by the processing circuitry whereby the first network node is operable to perform the method as claimed in any one of claims 2 to 21.

39. A first network node (704, 860, 950, 1208, 1308, 1508, 1600, 2000) adapted to: obtain a sensing quality assessment for one or more sensing measurements performed by a first set of sensing units for providing sensing, wherein the first set comprises at least one Radio Access Technology, RAT, independent sensing unit; and perform, based on the sensing quality assessment, an optimization procedure to determine a second set of sensing units for providing the sensing, wherein the optimization procedure seeks to optimize a number of RAT-dependent sensing units comprised in the second set subject to at least one constraint.

40. The first network node (704, 860, 950, 1208, 1308, 1508, 1600, 2000) as claimed in claim 39 further adapted to perform the method as claimed in any one of claims 2 to 21.

41. A second network node comprising processing circuitry and a memory, the memory containing instructions executable by the processing circuitry whereby the second network node is operable to: obtain sensor information for a first set of sensing units for providing sensing, wherein the first set comprises at least one Radio Access Technology, RAT, independent sensing unit; and determine, based on the obtained sensor information, a sensing quality assessment for one or more sensing measurements performed by the first set of sensing units.

42. The second network node as claimed in claim 41 wherein the memory further contains instructions executable by the processing circuitry whereby the second network node is operable to perform the method as claimed in any one of claims 23- 34.

43. A second network node (706, 840, 950, 1210, 1408, 1508, 1600, 2100) adapted to:obtain sensor information for a first set of sensing units for providing sensing, wherein the first set comprises at least one Radio Access Technology, RAT, independent sensing unit; and determine, based on the obtained sensor information, a sensing quality assessment for one or more sensing measurements performed by the first set of sensing units.

44. The second network node (706, 840, 950, 1210, 1408, 1508, 1600, 2100) as claimed in claim 43 further adapted to perform the method as claimed in any one of claims 23- 34.

45. A Radio Access Network, RAN, node comprising processing circuitry and a memory, the memory containing instructions executable by the processing circuitry whereby the RAN node is operable to: receive sensing information for a first sensing unit comprised in a first set of sensing units, wherein the first set of sensing units comprises at least one RAT- independent sensing unit; transmit the sensing information to a second network node; after transmitting the sensing information, receive a request to configure a second set of sensing units to perform sensing measurements; and configure, based on the request, the sensing units comprised in the second set of sensing units to perform sensing measurements.

46. A Radio Access Network, RAN, node (850, 930, 940, 1002, 1510A, 1510B, 1700, 2200) adapted to: receive sensing information for a first sensing unit comprised in a first set of sensing units, wherein the first set of sensing units comprises at least one RAT- independent sensing unit; transmit the sensing information to a second network node; after transmitting the sensing information, receive a request to configure a second set of sensing units to perform sensing measurements; and configure, based on the request, the sensing units comprised in the second set of sensing units to perform sensing measurements.

47. A first sensing unit comprising processing circuitry and a memory, the memory containing instructions executable by the processing circuitry whereby the first sensing unit is operable to:transmit, to a first network node, one or more sensing capabilities of the first sensing unit; after transmitting the one or more sensing capabilities, receive an indication to perform sensing measurements; and perform the sensing measurements.

48. A first sensing unit (702, 830, 1004, 1006, 1110, 1120, 1130, 1140, 206, 1302, 1304, 1306, 1512A, 1512B, 1510A, 1510B, 1700, 1800, 2300) adapted to: transmit, to a first network node, one or more sensing capabilities of the first sensing unit; after transmitting the one or more sensing capabilities, receive an indication to perform sensing measurements; and perform the sensing measurements.

49. A computer program, comprising instructions which, when executed on at least one processor, cause the at least one processor to carry out a method according to any of claims 1 to 36.

50. A carrier containing the computer program according to claim 49, wherein the carrier comprises one of an electronic signal, optical signal, radio signal or computer readable storage medium.

51. A computer-readable medium comprising instructions that, when executed on at least one processor, cause the at least one processor to perform the method according to any of claims 1 to 36.

52. A computer program product comprising non transitory computer readable media having stored thereon a computer program according to claim 49.

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