Network nodes, and methods therein for sensing target objects, in a communications network

Abstract

A method performed by a third network node is provided. The method is for handling signals related to sensing of one or more target objects in a geographical area of a communications network. The sensing of the one or more target objects is performed by dividing a sensing cell in the communications network into one or more cell grids. The sensing cell is a geographical area in the communications network comprising the one or more target objects. The third network node obtains (503) from one or more first network nodes, one or more first reports related to a first hierarchical level. The first hierarchical level comprises one or more first cell grids of a first size. The one or more first reports comprise information related to a preprocessing performed by the respective one or more first network nodes. The preprocessing is of one or more sensing signals received from the one or more target objects in the one or more first cell grids. The third network node evaluates (504) the one or more first reports based on one or more out of: a target object detection method, a target object detection threshold, a probability of detecting a target object, and a probability of false alarm of detecting a target object. Based on the evaluation, the third network node computes (505) a next hierarchical level comprising one or more next cell grids. To perform this computation, the third network node (505a) selects one or more cell grids out of the one or more first cell grids and the third network node divides (505b) the selected one or more cell grids into a second size. The second size is smaller than the first size. Then the third network node transmits (506) the next hierarchical level to one or more first network nodes.

Description

[0001] NETWORK NODES, AND METHODS THEREIN, IN A COMMUNICATIONS NETWORK

[0002] TECHNICAL FIELD

[0003] Embodiments herein relate to a third network node, a first network node and methods therein. In some aspects, embodiments relate to handling signals related to sensing of one or more target objects in a geographical area of a communications network.

[0004] BACKGROUND

[0005] In a typical communications network, wireless devices, also known as wireless communication devices, mobile stations, stations (STA) and / or User Equipment (UE), communicate via a Wide Area Network or a Local Area Network such as a Wi-Fi network or a cellular network comprising a Radio Access Network (RAN) part and a Core Network (CN) part. The RAN covers a geographical area which is divided into service areas or cell areas, which may also be referred to as a beam or a beam group, with each service area or cell area being served by a radio network node such as a radio access node e.g., a WiFi access point, a Base Station (BS) or a radio base station (RBS), which in some networks may also be denoted, for example, a Base Station (BS), a NodeB, eNodeB (eNB), or gNodeB (gNB) as denoted in Fifth Generation (5G) telecommunications. A service area or cell area is a geographical area where radio coverage is provided by the radio network node. The radio network node communicates over an air interface operating on a radio frequency with the wireless devices within the range of the radio network node.

[0006] 3rd Generation Partnership Project (3GPP) is the standardization body for specifying the standards for the cellular system evolution, e.g., including 3G, 4G, 5G and the future evolutions. Specifications for Evolved Universal Terrestrial Radio Access (E- UTRA) and Evolved Packet System (EPS) have been completed within the 3GPP. In 4G also called a Fourth Generation (4G) network, EPS is core network and E-UTRA is radio access network. In 5G, 5G Core (5GC) is core network, NR is radio access network. As a continued network evolution, the new release of 3GPP specifies a 5G network also referred to as 5G New Radio (NR) and 5GC.

[0007] Frequency bands for 5G NR are being separated into two different frequency ranges, Frequency Range 1 (FR1) and Frequency Range 2 (FR2). FR1 comprises sub-6 GHz frequency bands. Some of these bands are bands traditionally used by legacy standards but have been extended to cover potential new spectrum offerings from 410 MHz to 7125 MHz. FR2 comprises frequency bands from 24.25 GHz to 52.6 GHz. Bands in this millimeter wave range have shorter range but higher available bandwidth than bands in the FR1.

[0008] Multi-antenna techniques may significantly increase the data rates and reliability of a wireless communication system. For a wireless connection between a single user, such as UE, and a base station (BS), the performance is in particular improved if both the transmitter and the receiver are equipped with multiple antennas, which results in a Multiple-Input Multiple-Output (MIMO) communication channel. This may be referred to as Single-User (SU)-MIMO. In the scenario where MIMO techniques is used for the wireless connection between multiple users and the base station, MIMO enables the users to communicate with the base station simultaneously using the same time-frequency resources by spatially separating the users, which increases further the cell capacity. This may be referred to as Multi-User (MU)-MIMO. Note that MU-MIMO may benefit when each UE only has one antenna. The cell capacity can be increased linearly with respect to the number of antennas at the BS side. Due to that, more and more antennas are employed in BS. Such systems and / or related techniques are commonly referred to as massive MIMO.

[0009] The future generations of telecommunication networks such as e.g., 5G and beyond may offer an early design involving cooperation between sensing and communication in wireless communication networks. Such a merger of services may be achieved via a fully integrated system capable of transmitting radio frequency signals and receiving attenuated and distorted echoes of the transmitted radio frequency signals for performing sensing of the physical world. MIMO radar is a potential candidate that may be exploited in offering such integrated services. The MIMO radar is a cooperative multi-static radar in which the processing is mostly performed in a joint and / or a centralized unit. This is different from other multi-static radars which are independent bi-static radars with the processing mostly performed locally. A main benefit of MIMO radars is the possibility to exploit diversity gains if the receiving antennas are sufficiently separated, or if the target object that is to be sensed is sufficiently complex and has a large enough dimension. When the target object is viewed as an antenna with aperture length D, the target’s beamwidth would not illuminate two receivers simultaneously. Figure 1 shows that the elements of the channel matrix decorrelate when the receiver antennas of the MIMO radar fall in different beamwidths originating from the target object. If a single receiver is illuminated, then the paths are decorrelated and there is path diversity to exploit. Compared to conventional phased array radars, which have co-located antennas, Ml MO radars with widely separated antennas benefit more from diversity gains when the Signal- to-Noise Ratio (SNR) is high enough.

[0010] SUMMARY

[0011] As part of developing embodiments herein, the inventors identified some problems that first will be described.

[0012] MIMO radar for the purpose of sensing of target objects may be implemented by dividing a sensing space corresponding to a geographical area in a communications network into cells and then testing each cell for the presence of the target object. Figure 2 illustrates cell-based processing in a MIMO radar. The top of Figure 2 shows a 2D space divided into several cells. These cells may be referred to herein as e.g., range cells, cell grids, and cells. A range cell or a cell grid when used herein means e.g., a small area and / or a volume of a large sensing space. The range cell may e.g., be of any form e.g., a rectangular area as shown in Figure 2, or a cubic volume in 3D. The signals transmitted from a transmitter to each of the receivers e.g., BS2 and BS3 in Figure 2 is associated with a propagation delay at each hypothesized cell. For currently hypothesized range cell, a joint processing unit knows and may calculate AT = + TT^2 ~ These delays may be used in the sampling of the output of the matched filters at each receiver as shown at the bottom of Figure 2 before combining them together for sensing the target objects.

[0013] Sensing of target objects in a large search space using 2D or 3D scanning of range cells at a resolution given by the processed bandwidth of the sensing signal may be difficult. Target objects may also be referred to herein as Reflection Points (RPs). The sampling time of each receiver is adjusted according to a range cell grid point determined by the position of the range cells. The range cell grid point when used herein means e.g., the center, or the corners of the particular range cell. If target objects exist only quite far from the next range cell grid point, and if the grid distance is larger than the distance corresponding to the sampling period, and if the autocorrelation of the transmitter signal is an ideal delta function, then the correlator samples of several or all of the receivers may be zero on all of the range cell grid points, e.g. the 8 corners of the range cell containing the target objects if the range cell is a cube. The grid distance when used herein refers to e.g., the distance between two closest range cell grid points. For a 2D range cell under similar circumstances, the correlator samples of several or all of the receivers may be zero on all of the 4 corners of the range cell containing the target objects. In these cases, the target objects will not be detected at this low cell grid resolution i.e., large size of the range cells. There might not be any indication to raster the current range cell into smaller range cells in order to detect and / or resolve the target objects.

[0014] The problem is further illustrated in Figure 3 in which the correlator output power for two receivers positioned orthogonally with respect to the target object is shown. The circles in rows and columns correspond to sample positions of the correlators of the two receivers positioned orthogonally with respect to the target object. The sum power of both correlators is represented by the level of the density of dots in the circles e.g., the more compact the dots are in the circle, the higher the sum power. Figure 3 shows that the correlator output is not a delta function at the sample position corresponding to the position of the target object, but shows some gradual decay e.g., due to non-ideal transmit signal autocorrelation function or channel multipath. The hypothesis testing of the range cells for the detection of the target object is performed only for the four samples on the intersection of the thick lines. However, at these samples the correlator power is already diminished to a level that is close to the noise floor and so the presence of the target object may not be detected. In addition to the above stated problem, performing and repeating the sensing procedure to detect a target object by using small range cells results in the generation of enormous amounts of signals to be sensed and processed increasing the computational complexity at the different network nodes involved.

[0015] An object of embodiments herein is to improve the handling of signals related to sensing of one or more target objects in a geographical area of a communications network.

[0016] According to an aspect of embodiments herein, the object is achieved by a method performed by a third network node such as e.g, a UE or a core network node. The method is for handling signals related to sensing of one or more target objects in a geographical area of a communications network. The sensing of the one or more target objects is performed by dividing a sensing cell in the communications network into one or more cell grids. The sensing cell is a geographical area in the communications network comprising the one or more target objects. The third network node obtains from one or more first network nodes, one or more first reports related to a first hierarchical level. The first hierarchical level comprises one or more first cell grids of a first size. The one or more first reports comprise information related to a preprocessing performed by the respective one or more first network nodes. The preprocessing is of one or more sensing signals received from the one or more target objects in the one or more first cell grids. The third network node evaluates the one or more first reports based on one or more out of: a target object detection method, a target object detection threshold, a probability of detecting a target object, and a probability of false alarm of detecting a target object. Based on the evaluation, the third network node computes a next hierarchical level comprising one or more next cell grids. To perform this computation, the third network node selects one or more cell grids out of the one or more first cell grids and the third network node divides the selected one or more cell grids into a second size e.g., forming the one or more next cell grids. The second size is smaller than the first size. Then the third network node transmits the next hierarchical level to one or more first network nodes.

[0017] According to an aspect of embodiments herein, the object is achieved by a method performed by a first network node. The method is for handling signals related to sensing of one or more target objects in a geographical area of a communications network. The sensing of the one or more target objects is performed by dividing a sensing cell in the communications network into one or more cell grids. The sensing cell is a geographical area in the communications network comprising the one or more target objects. The first network node receives a first hierarchical level from a third network node. The first hierarchical level comprises one or more first cell grids of a first size. The first network node receives one or more sensing signals from the one or more target objects in the one or more first cell grids comprised in the first hierarchical level. The first network node preprocesses the received one or more sensing signals based on one or more out of: a target object detection method, a target object detection threshold, a probability of detecting a target object, a probability of false alarm of detecting a target object and a filtering of the received one or more sensing signals. The first network node transmits a first report to the third network node. The first report comprises information related to the preprocessing of the one or more sensing signals. Based on the transmitted first report, the first network node receives from the third network node a next hierarchical level comprising one or more next cell grids. The one or more next cell grids comprises one or more cell grids selected out of the one or more first cell grids and further divided into a second size. The second size is smaller than the first size.

[0018] According to another aspect of embodiments herein, the object is achieved by a third network node. The third network node is configured to handle signals related to sensing of one or more target objects in a geographical area of a communications network. The sensing of the one or more target objects is adapted to be performed by dividing a sensing cell in the communications network into one or more cell grids. The sensing cell is a geographical area in the communications network comprising the one or more target objects. The third network node is further being configured to obtain, from one or more first network nodes, one or more first reports related to a first hierarchical level. The first hierarchical level is adapted to comprise one or more first cell grids of a first size. The one or more first reports is adapted to comprise information related to a preprocessing, performed by the respective one or more first network nodes. The preprocessing is of one or more sensing signals received from the one or more target objects in the one or more first cell grids. The third network node is further being configured to evaluate the one or more first reports based on one or more out of: a target object detection method, a target object detection threshold, a probability of detecting a target object, and a probability of false alarm of detecting a target object. The third network node is further being configured to, based on the evaluation, compute a next hierarchical level comprising one or more next cell grids. This is performed by further being configured to select one or more cell grids out of the one or more first cell grids and divide the selected one or more cell grids into a second size e.g., forming the one or more next cell grids. The second size is smaller than the first size. The third network node is further being configured to transmit the next hierarchical level to one or more first network nodes.

[0019] According to an aspect of embodiments herein, the object is achieved by a first network node. The first network node is configured to handle signals related to sensing of one or more target objects in a geographical area of a communications network. The sensing of the one or more target objects is adapted to be performed by dividing a sensing cell in the communications network into one or more cell grids. The sensing cell is a geographical area in the communications network comprising the one or more target objects. The first network node is further being configured to receive a first hierarchical level from a third network node. The first hierarchical level is adapted to comprise one or more first cell grids of a first size. The first network node is further being configured to receive one or more sensing signals from the one or more target objects in the one or more first cell grids adapted to be comprised in the first hierarchical level. The first network node is further being configured to preprocess the received one or more sensing signals based on one or more out of: a target object detection method, a target object detection threshold, a probability of detecting a target object, a probability of false alarm of detecting a target object and a filtering of the received one or more sensing signals. The first network node is further being configured to transmit a first report to the third network node. The first report is adapted to comprise information related to the preprocessing of the one or more sensing signals. The first network node is further being configured to, based on the transmitted first report, receive from the third network node a next hierarchical level comprising one or more next cell grids. The one or more next cell grids is adapted to comprise one or more cell grids selected out of the one or more first cell grids and further divided into a second size. The second size is smaller than the first size.

[0020] Thanks to that the third network node performs an evaluation of the first cell grids to compute the next cell grids smaller in size than the first cell grids, the first network node is able to use these next cell grids to receive one or more sensing signals from the target object and resolve details e.g., related to the target object which might otherwise have not been detected when using large first cell grids for sensing. Thus, the amount of sensing signals required to be received, preprocessed and transmitted to the third network node by the first network node is reduced. This further reduces the processing complexity at the third network node. In this way, by performing the above method, the handling of signals related to sensing of one or more target objects in a geographical area of a communications network is improved.

[0021] Embodiments herein may provide one or more of the following advantages:

[0022] Ensure that the target objects may be detected using distributed antenna such as e.g., MIMO antenna reception;

[0023] Reduce the processing complexity at the first network node and / or the third network node and further reduce the number of sensing signal transmissions; and

[0024] Reduce the signaling required between the first network node such as e.g., reception node and the third network node such as e.g., central processing unit.

[0025] BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Examples of embodiments herein are described in more detail with reference to attached drawings in which:

[0027] Figure 1 is a schematic block diagram according to prior art.

[0028] Figure 2 is a schematic block diagram according to prior art.

[0029] Figure 3 is a schematic block diagram according to prior art.

[0030] Figure 4 is a schematic block diagram illustrating embodiments of a communications network.

[0031] Figure 5 is a flowchart depicting an embodiment of a method in a third network node. Figure 6 is a flowchart depicting an embodiment of a method in a first network node. Figure 7 is a schematic block diagram illustrating an example embodiment of a method herein.

[0032] Figure 8 is a schematic block diagram illustrating an example embodiment of a method herein.

[0033] Figure 9 is a schematic block diagram illustrating an example embodiment of a method herein.

[0034] Figure 10 is a schematic block diagram illustrating an example embodiment of a method herein.

[0035] Figure 11 is a flowchart illustrating an example embodiment of a method herein.

[0036] Figure 12 is a schematic diagram illustrating an example embodiment of a method herein.

[0037] Figure 13 is a schematic block diagram illustrating embodiments of a third network node. Figure 14 is a schematic block diagram illustrating embodiments of a first network node. Figure 15 schematically illustrates embodiments of a communication system.

[0038] Figure 16 is a generalized block diagram of embodiments of a UE.

[0039] Figure 17 is a generalized block diagram of embodiments of a network node. Figure 18 is a generalized block diagram of embodiments of a virtualization environment.

[0040] DETAILED DESCRIPTION

[0041] Figure 4 is a schematic overview depicting a communications network 100 wherein embodiments herein may be implemented. The communications network 100 comprises one or more RANs, such as RAN 110 one or more CNs such as CN 106. The communications network 100 may use 5G NR but may further use a number of other different technologies, such as, 6G, Wi-Fi, Long Term Evolution (LTE), LTE-Advanced, Wideband Code Division Multiple Access (WCDMA), Global System for Mobile communications / enhanced Data rate for GSM Evolution (GSM / EDGE), Worldwide Interoperability for Microwave Access (WiMax), or Ultra Mobile Broadband (UMB), just to mention a few possible implementations.

[0042] RAN nodes, such as a RAN node 111 , a RAN node 112, and a RAN node 113 operate in the RAN 110 of the communications network 100. The RAN nodes 111, 112, 113 provide radio coverage over a geographical area represented by the service areas 11, 12, 13, respectively. The RAN nodes 111, 112, 113 may each be a transmission and reception point e.g. a radio access network node such as a base station, e.g. a radio base station such as a NodeB, an evolved Node B (eNB, eNode B), an NR Node B (gNB), a base transceiver station, a radio remote unit, an Access Point Base Station, a base station router, a transmission arrangement of a radio base station, a stand-alone access point, a Wireless Local Area Network (WLAN) access point or an Access Point Station (AP STA), an access controller, or any other network unit capable of communicating with UEs, such as UE 121, 122, 123 within a cell, served by the respective RAN nodes 111 , 112, 113. The respective RAN nodes 111 , 112, 113 may be referred to as a serving radio network node and may communicate with the UE 121 , 122, 123 with Downlink (DL) transmissions to the UE 121 , 122, 123 and Uplink (UL) transmissions from the UE 121 , 122, 123.

[0043] One or more UEs operate in the communication network 100, such as e.g. the UE 121, UE 122, and UE 123. The UE 121 , 122, 123 may e.g. be a remote UE, a wireless device, an NR device, a mobile station, a wireless terminal, an NB-loT device, an MTC device, an eMTC device, a CAT-M device, a WiFi device, an LTE device and an a non- access point (non-AP) STA, a STA, that communicates via a RAN node such as e.g. RAN node 111 , one or more Access Networks (AN), e.g. a RAN such as e.g., RAN 110, to one or more core network (CN) nodes such as e.g., CN node 131 , in one or more CNs such as e.g., CN 106. It should be understood by the skilled in the art that “UE” is a non-limiting term which means any terminal, client, mobile client, IMS client, wireless communication terminal, user equipment, Device to Device (D2D) terminal, or node e.g. smart phone, laptop, mobile phone, sensor, relay, mobile tablets or even a car or any small base station communicating within a cell.

[0044] CN nodes, such as a CN node 131 operate in the CN 106 of the communications network 100.

[0045] Network nodes, such as first network node 101 , operate in the communications network 100. In some embodiments, the first network node 101 is a RAN node such as e.g., RAN node 111. In some other embodiments, the first network node 101 is a UE such as e.g., UE 121.

[0046] Network nodes, such as second network node 102, operate in the communications network 100. In some embodiments, the second network node 102 is a RAN node such as e.g., RAN node 112. In some other embodiments, the second network node 102 is a UE such as e.g., UE 122.

[0047] Network nodes, such as third network node 103, operate in the communications network 100. In some embodiments, the third network node 103 is a RAN node such as e.g., RAN node 113. In some other embodiments, the third network node 103 is a CN node such as e.g., CN node 131.

[0048] Methods according to embodiments herein are performed by the first network node 101 and the third network node 103. These nodes may be Distributed Nodes (DN)s and functionality, e.g. comprised in a cloud 170 as shown in Figure 4.

[0049] Example embodiments herein provide a method to reduce the search and signal preprocessing complexity of a MIMO radar implemented for the sensing of target objects. According to example embodiments herein, the amount of information and / or signals transmitted from the first network node 101 to the third network node 103 may be reduced by testing for the presence of target objects e.g., Reflection Points (RPs) in cell grids in a hierarchical manner. As described earlier, according to example embodiments herein, a sensing space and / or a sensing cell corresponding to a geographical area in the communications network is divided into cells and then each cell is tested for the presence of the target object in a hierarchical manner. These cells may be referred to herein as e.g., cell grids. A cell grid when used herein means e.g., a small area and / or a volume of a larger sensing space.

[0050] According to example embodiments herein, the sensing and / or detection of the target object is performed by the third network node 103 by repeating the sensing procedure as described in example embodiments herein. Each repetition cycle in this repeating i.e. , hierarchical sensing and / or search procedure may be performed by using a specific and / or a unique hierarchical level. With each hierarchical level, the size of the cell grids is reduced, and the probability of false alarm Pfis adapted. The size of the cell grid may e.g., be modified by adjusting the processed bandwidth of the sensing signal. A smaller processed bandwidth leads to a small range resolution and may be used in earlier hierarchical layers with larger cell grids. The small range resolution when used herein means e.g., that the distance between the one or more target objects is large enough to be resolved. One way of adapting Pf may be by using various hypothesis test methods. Hypothesis testing when used herein means e.g., testing to detect the target object. Only the cell grids for which the target object hypothesis test is true are considered for the next hierarchical level. Some other cell grids may also be excluded from the next hierarchical level for further testing based on a decision made by the third network node 103.

[0051] As the size of cell grids is inversely proportional to the transmitted and / or processed signal bandwidth, it may be advantageous to increase the transmitted and / or processed signal bandwidth when the size of the cell grids decreases at each subsequent hierarchical level i.e., with increasing number of repetition cycles. According to example embodiments provided herein, this may be achieved by adapting the receiver bandwidth to span only a portion of the transmitter bandwidth, by applying windowing to the received sensing signal, or by splitting the receiver bandwidth into multiple parts. Further, if the properties of the sequence of the transmitted sensing signal need to be maintained, example embodiments herein provide a method to use combs to transmit various sequences on different parts of the bandwidth.

[0052] Example embodiments herein also provide signalling required to exchange information between the first network node 101 , second network node 102 and the third network node 103. Depending on where the third network node 103 is located, e.g. within a RAN node such as e.g., a base station 113 or in the core network, and depending on the type of first network node 101 and second network node 102, e.g., a RAN node such as e.g., a base station 111 or a User Equipment (UE) 121 , different signalling may be needed.

[0053] Example embodiments herein provide a method to perform hierarchical search of a target object in the communications network 100 by decreasing the search area and by decreasing the size of the cell grids at each hierarchical level e.g., with increasing repetition cycles. Decreasing the search area is performed by the third network node 103 by excluding one or more cell grids from the previous hierarchical level for the next level of the hierarchical search. Only the cell grids for which the target object hypothesis test is true are considered in the next hierarchic level. Example embodiments herein also provide different methods to decrease the processed signal bandwidth of the sensing signal when decreasing the size of the cell grid. Example embodiments herein also provide the signaling between the different nodes involved such as e.g., signaling between the first network node 101 and the second network node 102, signaling between the first network node 101 and the third network node 103, and the signaling between the third network node 101 and the second network node 102.

[0054] A number of embodiments will now be described, some of which may be seen as alternatives, while some may be used in combination.

[0055] A method according to embodiments will first be described as seen from the view of the third network node 103 together with Figure 5, and then as seen from the view of the first network node 101 together with Figure 6. Figure 5 shows exemplary embodiments of a method performed by the third network node 103. The third network node 103 may be represented by a processing node such as e.g., a central processor comprising any one out of: a RAN node such as e.g., RAN node 113 e.g., a base station, and a core network node such as e.g., CN node 131. The method is for handling signals related to sensing of one or more target objects in the geographical area of the communications network 100. The sensing may be performed by using a multi antenna radar system e.g., a MIMO radar system. The sensing of the one or more target objects is performed by dividing the sensing cell in the communications network 100 into the one or more cell grids. The sensing cell is the geographical area such as e.g., a coverage area in the communications network 100 comprising the one or more target objects. In some embodiments, the sensing cell is the same geographical area as the service area such as e.g., service area 11. In some other embodiments, the sensing cell is the geographical area that is overlapping two different service areas such as e.g., service area 11, 12. In some embodiments, the sensing cell is the geographical area that is one or more out of: part of one service area such as e.g., service area 11 , and combination of one or more service areas such as e.g., service areas 11 , 12, 13.

[0056] According to an example scenario, the target object to be sensed and / or detected may be present between the UE 121 and the UE 122 in the service area 11 covered by the RAN node 111. The third network node 103 in this case may define a search area which it may refer to as the sensing cell. The third network node 103 may then divide this sensing cell into one or more cell grids which then correspond to a first hierarchical level.

[0057] The method comprises the following actions, which actions may be taken in any suitable order. Optional actions are referred to as dashed boxes in Figure 5.

[0058] Action 501. The third network node 103 may transmit the first hierarchical level to the one or more first network nodes 101. The first network node 101 may be represented by a receiving node comprising any one out of: a RAN node such as e.,g RAN node 111 e.g., a base station, and the UE such as e.g., UE 121. Since the search area is between the UE 121 and the UE 122 in the example scenario, the third network node 103 may select UE 121 and UE 122 as the one or more first network nodes i.e. , the receiving nodes. In this case, the third network node 103 may transmit the first hierarchical level to UE 121 and UE 122.

[0059] Action 502. The third network node 103 may instruct one or more second network nodes 102 to transmit the one or more sensing signals. The second network node 102 may be represented by a transmitting node comprising any one out of: a RAN node such as e.g., RAN node 111 e.g., a base station, and the UE such as e.g., UE 121. According to the example scenario, the second network node 102 may be the RAN node 111. The third network node 103 may further instruct the one or more first network nodes 101 to receive the one or more sensing signals.

[0060] Action 503. The third network node 103 obtains from one or more first network nodes 101 , one or more first reports related to a first hierarchical level. The first hierarchical level comprises one or more first cell grids of a first size. The one or more first reports comprise information related to a preprocessing, performed by the respective one or more first network nodes 101. The preprocessing is of one or more sensing signals received from the one or more target objects in the one or more first cell grids.

[0061] Action 504. The third network node 103 evaluates the one or more first reports based on one or more out of a target object detection method, a target object detection threshold, a probability of detecting a target object, and a probability of false alarm of detecting a target object. The evaluation may be performed by combining the one or more first reports from the one or more first network nodes 101.

[0062] Action 505. The third network node 103, based on the evaluation, computes a next hierarchical level comprising one or more next cell grids. This computation is performed by the third network node 103 through the following two actions.

[0063] Action 505a. The third network node 103 selects one or more cell grids out of the one or more first cell grids. For example, the number of first cell grids may e.g., be 100. In this case, the third network node 103 after evaluation may compute that only 50 of those first cell grids are relevant for the next hierarchical search.

[0064] Action 505b. After the selection, the third network node 103 divides the selected one or more cell grids into a second size. The second size is smaller than the first size. According to the example as stated above, the third network node 103 may then divide each of those selected 50 first cell grids further into say e.g., 100 next cell grids. These 100 next cell grids divided out of a single first cell grid may be of a smaller size than the single first cell grid.

[0065] In some embodiments, the first hierarchical level and the next hierarchical level further comprises, specific to the first hierarchical level and the next hierarchical level, one or more out of: a target object detection method, a target object detection threshold, a probability of detecting a target object, and a probability of false alarm of detecting a target object. The target object detection method, the target object detection threshold, the probability of detecting a target object, and the probability of false alarm of detecting a target object is selected for each specific hierarchical level based on a decision taken by the third network node 103.

[0066] Action 506. The third network node 103 transmits the next hierarchical level to one or more first network nodes 101. In some embodiments, the transmission of the next hierarchical level comprising one or more next cell grids further comprises transmission of information related to the identification and / or the location of the one or more next cell grids. In these embodiments, the third network node 103 may transmit to the first network node 101 one or more out of: a reference to the first cell grids from the first i.e. , previous hierarchical level and a cell division scheme to be applied by the first network node 101 to split those first cell grids into the one or more next cell grids. In some embodiments, the one or more first network nodes 101 receiving the next hierarchical level is the same as the one or more first network nodes 101 that received the first hierarchical level. In some other embodiments, the third network node 103 excludes one or more first network nodes 101 to which it transmitted the first hierarchical level while transmitting the next hierarchical level.

[0067] The above-mentioned Actions 502, 503, 504, 505, and 506 are repeated in repetition cycles. The next hierarchical level from a first repetition cycle becomes the first hierarchical level for a second repetition cycle. The repeating is performed until the size of the one or more cell grids is equal to or lesser than a pre-defined threshold. The predefined threshold is related to a resolution required of the sensing of the target object.

[0068] In this way by using the methods above, the third network node 103 is able to perform a hierarchical search and / or sensing of the one or more target objects in a geographical area of the communications network 100 thereby improving the detection of the target objects. The third network node 103 is also able to reduce the number of signals and / or information related to sensing i.e., the overhead that is received from the one or more first network nodes 101. In doing so, the third network node 103 further reduces the processing complexity during the sensing of the one or more target objects. The third network node 103 is further able to reduce energy consumption due to the reduced overhead and the reduced processing complexity.

[0069] Figure 6 shows exemplary embodiments of a method performed by the first network node 101. The first network node 101 may be represented by a receiving node comprising any one out of: a RAN node such as e.g., RAN node 111 e.g., a base station, and a UE such as e.g., the UE 121. The method is for handling signals related to sensing of one or more target objects in the geographical area of the communications network 100. The sensing of the one or more target objects is performed by dividing the sensing cell in the communications network 100 into the one or more cell grids. The sensing cell is the geographical area such as e.g., a coverage area in the communications network 100 comprising the one or more target objects.

[0070] According to an example scenario, the target object to be sensed and / or detected may be present between the UE 121 and the UE 122 in the service area 11 covered by the RAN node 111. The third network node 103 may select one or more first network nodes suitable for sensing the target object. In this case, the third network node 103 may select UE 121 and UE 122 as the one or more first network nodes i.e. , the receiving nodes.

[0071] The method comprises the following actions, which actions may be taken in any suitable order. Optional actions are referred to as dashed boxes in Figure 6.

[0072] Action 601. The first network node 101 receives a first hierarchical level from a third network node 103. The third network node 103 may be represented by a processing node such as e.g., a central processor comprising any one out of: a RAN node such as e.g., RAN node 113 e.g., a base station, and a core network node such as e.g., CN node 131. The first hierarchical level comprises one or more first cell grids of a first size. According the above-stated example scenario, the third network node 103 may transmit the first hierarchical level to UE 121 and UE 122.

[0073] Action 602. The first network node 101 may receive an instruction from the third network node 103 to receive the one or more sensing signals from the one or more target objects in the one or more first cell grids comprised in the first hierarchical level. The one or more sensing signals are transmitted by a second network node 102. The second network node 102 may be represented by a transmitting node comprising any one out of: a RAN node such as e.g., RAN node 111 e.g., a base station, and a UE such as e.g., the UE 121. According to the example scenario, the second network node 102 may be the RAN node 111 since the search area is between the UE 121 and the UE 122. The sensing signals transmitted from the second network node 102 may reach the target object comprised in the sensing cell and may e.g., be reflected and / or scattered from the target object. These sensing signals from the target object may then be received by the one or more first network nodes 101 for sensing of the target object. Action 603. The first network node 101 receives one or more sensing signals from the one or more target objects in the one or more first cell grids comprised in the first hierarchical level. In some embodiments, a bandwidth and / or a beamwidth of the one or more sensing signals transmitted from the second network node 102 is based on the size of the one or more cell grids in each hierarchical level. In some embodiments, a bandwidth of reception of the first network node 101 spans a portion of a bandwidth of transmission of the second network node 102. In some embodiments, a bandwidth of reception of the first network node 101 is a bandwidth of transmission of the second network node 102. In these embodiments, the first network node 101 and / or the second network node 102 applies a window function to receive the one or more sensing signals. In some embodiments, a bandwidth of reception of the first network node 101 is split into two portions. In these embodiments, the first network node 101 receives the one or more sensing signals in the respective two portions. The two portions may either be overlapping or be non-overlapping.

[0074] Action 604. The first network node 101 preprocesses the received one or more sensing signals based on one or more out of: a target object detection method, a target object detection threshold, a probability of detecting a target object, a probability of false alarm of detecting a target object and a filtering of the received one or more sensing signals. In some embodiments, the first network node 101 performs preliminary processing of the received one or more sensing signals to perform preliminary detection of the one or more target objects. In some embodiments, the first network node 101 performs matched filtering.

[0075] Action 605. The first network node 101 transmits a first report to the third network node 103. The first report comprises information related to the preprocessing of the one or more sensing signals. In some embodiments, the first report comprises information related to the preliminary detection of the one or more target objects performed by the first network node 101. In some embodiments, the first report comprises the peak and / or energy level of the one or more cell grids from which the one or more sensing signals were received. In these embodiments, the complete process of detection of the one or more target objects is performed at the third network node 103.

[0076] Action 606. The first network node 101 , based on the transmitted first report, receives from the third network node 103 a next hierarchical level comprising one or more next cell grids. The one or more next cell grids comprises one or more cell grids selected out of the one or more first cell grids and further divided into a second size. The second size is smaller than the first size. In some embodiments, the first hierarchical level and the next hierarchical level further comprises, specific to the first hierarchical level and the next hierarchical level, one or more out of: a target object detection method, a target object detection threshold, a probability of detecting a target object, and a probability of false alarm of detecting a target object.

[0077] In this way by using the methods above, the first network node 101 is able to reduce the number of signals and / or information related to sensing i.e. , the overhead that is transmitted from the one or more first network nodes 101. This in way the resources used for transmission is reduced thereby reducing the energy consumption in the communications network 100.

[0078] Embodiments herein such as the embodiments mentioned above will now be further described and exemplified. The text below is applicable to and may be combined with any suitable embodiment described above.

[0079] Hierarchical Search

[0080] Examples of embodiments described herein apply a hierarchical search with decreasing size of the cell grids and decreasing of the search area. The search area when used herein refers to e.g., the one or more cell grids used in each hierarchical level for the sensing procedure. These one or more cell grids may be disconnected from each other. Thus the total search area integrated over all of the cell grids in the respective hierarchical level is decreasing. The Actions 502-506 described earlier may herein be referred to as e.g., hierarchical search for detection of the target object. The first hierarchical level may comprise a target object detection method that has a high probability of detection of the target object Pd inside the cell grid thereby sacrificing on the probability of false alarm of detecting a target object Pf. In each hierarchical level, if the target object detection hypothesis is true for a particular cell grid, then that particular cell grid is retained as active and considered for subsequent evaluation in the next hierarchical level that uses a smaller size of the cell grid. Figure 7 illustrates an example of the cell splitting at each hierarchical level according to example embodiments as described in Action 502-506. At the first hierarchical level e.g., Level 1 , the sensing cell is divided into four first cell grids e.g., cell grids 1 ,2,3, and 4 and the sensing procedure according to Actions 502-506 is performed on all the four first cell grids. The third network node 103 may decide that only two cell grids e.g., cell grids 1 and 4 out of the four first cell grids from the first hierarchical level e.g., Level 1 are relevant for the next hierarchical level e.g., Level 2 corresponding to the second repetition cycle. The first cell grids 1 and 4 are then each divided further into four cell grids of a second size smaller than the first size e.g., size of the first cell grids. For example, cell grid 1 from Level 1 is divided into smaller cell grids 5, 6, 7, and 8 while cell grid 4 from Level 1 is divided into cell grids 9, 10, 11, and 12. These eight cell grids become the next cell grids for the next hierarchical level to perform the sensing procedure according to Actions 502-506.

[0081] As described earlier in Action 505, the target object detection method and the target object detection threshold may be changed to suit the current hierarchical level. Pf that is dependent on the detection threshold and the detection method may e.g., decrease for each hierarchical level. This means that at a high hierarchical level e.g., the first hierarchical level, the target object detection hypothesis may be true for many cell grids in which there may actually be no target object present. This may e.g., be due to noise. However, considering a first cell grid comprising no target object for evaluation in the next hierarchical level and dividing them further into smaller next cell grids with a detection method and detection threshold that enables lower Pf may result in identifying that there is indeed no target object present on any of those next cell grids derived from the first cell grid. The re-testing and / or re-evaluation at the next hierarchical levels of the one or more next cell grids derived out of a specific first cell grid comprised in the first hierarchical level with a tighter detection threshold may then reveal that there is actually no target object on any of these next cell grids, up to the limit set for the Pf of that next hierarchical level. The Pf limit of a specific hierarchical level is set based on decision taken by the third network node 103. The decision may be based on the hypthesis test method.

[0082] As described in Actions 504 and 604, the target object detection method is used by the third network node 103 to perform evaluation of the next hierarchical level and may also used by the first network node 101 to perform preprocessing of the received one or more sensing signals. The target object detection method may be specific to each hierarchical level i.e., each repetition cycle of the sensing procedure may have a different method to detect the target object with a different detection threshold and a corresponding Pd and Pf. The sensing procedure when used herein refers e.g., to the Actions 502-506 described earlier. During each repetition cycle, the next hierarchical level from the previous repetition cycle becomes the first hierarchical level for the current repetition cycle. The target object detection method may herein be referred to as e.g., hypothesis test method. Each cell grid i.e., the individual cell may be sampled at multiple delay points i.e., the sampling resolution of the respective first network node 101 is higher than the delay range that the cell grid represents. This results in multiple samples corresponding to each cell grid. Figures 8, 9 and 10 show some examples of hypothesis test methods that may be used at each hierarchical level to aggregate the value of all these samples and / or over all the first network nodes 101 at the respective hierarchical level to one hypothesis outcome for the considered cell grid. Figure 8 illustrates a test method according to which the test is true for any first network node 101 e.g., a receiver of the one or more sensing signals for any sample in the current cell grid. Figure 9 illustrates a test method according to which the test considering the energy aggregation over all samples in the cell grid of every first network node 101 is true for any first network node 101. Figure 10 illustrates a test method according to which the test considering the energy aggregation over all samples in the cell grid over all first network nodes 101 is true.

[0083] The hierarchical search as described in example embodiments herein may be exploited for reducing the complexity for the detection of target object in the third network node 103 that receives information about the received one or more sensing signals from the one or more first network nodes 101. Example embodiments herein may as well be exploited for reducing the complexity of preprocessing of the received one or more sensing signals in the one or more first network nodes 101 and for reducing the amount of information that may be conveyed in the first report from the one or more first network nodes 101 to the third network node 103.

[0084] For example, in the case of the hypothesis testing methods illustrated in Figures 8 and 9, the first network node 101 needs to transmit to the third network node 103 only the indices of the cell grids of the current hierarchical level for which the test is true. As described in Action 604, in the above case, the first network node 101 may perform preliminary detection of the target object and may transmit information related to the preliminary detection. For method illustrated in Figure 10, each first network node 101 needs to report the energy of each cell grid. As described in Action 604, in the above case, the first network node 101 may only perform matched filtering to report the peak and / or energy levels corresponding to all cell grids. The first network node 101 may also report the complete result of the matched filtering to the third network node 103.

[0085] For the reduction of the size of the first report with each repetition cycle of the sensing procedure, the first network node 101 needs to be informed about the one or more cell grids to be evaluated in each hierarchical level and for which one or more cell grids, the first network node 101 needs to send information in the first report. In each hierarchical level i.e. , with each repetition cycle, as described in Action 504, the third network node 103 collects the one or more first reports from the one or more first network nodes 101 and evaluates i.e., hypothesis tests the one or more first reports for each active cell grid. After performing the evaluation, the third network node 103 is required to signal the one or more next cell grids that have passed the test to one or more first network nodes 101 so that the one or more first network nodes 101 may limit further evaluation in the next hierarchical level i.e., next repetition cycle to these one or more next cell grids. The further evaluation performed by the first network node 101 comprises receiving sensing signals from the target object in the cell grid and performing preprocessing of the received sensing signal.

[0086] In some embodiments, the one or more cell grids transmitted by the third network node 103 in a hierarchical level may be specific to each of the first network nodes 101. In these embodiments, the hierarchical level transmitted to each of the first network nodes 101 is different from each other. For example, a first first network node such as e.g., RAN node 111 may receive cell grids 1 ,3, and 4 for evaluation in the next hierarchical level while a second first network node such as e.g., UE 121 may receive only cell grids 1 and 3 for evaluation in the next hierarchical level. The selection of the cell grids for each of the first network nodes 101 depends on the position of the respective first network nodes 111 and 121. Referring to the above-mentioned example, the third network node 103 may exclude the cell grid 4, that has passed the hypothesis test, from the signalling towards the second first network node i.e., UE 121 e.g., for the following two reasons. The considered first network node 101 i.e., the UE 121 may not have evaluated the excluded cell grid e.g., the cell grid 4 in the previous hierarchical level for which the considered first network node 101 i.e., UE 121 has reported before. The third network node 103 may have a-priori knowledge that the one or more sensing signals from the excluded cell is unlikely to be receivable by the considered first network node 101 i.e., the UE 121 because of the known position of the considered first network node 101 i.e., UE 121 being too far away from the excluded cell grid or blocked by large known objects. Figure 11 shows a flowchart illustrating the hierarchical search according to the example embodiments described herein.

[0087] Action 1101 : This is similar to Action 601 described earlier. The first hierarchical level comprising e.g., the identification and / or location corresponding to the one or more first cell grids is initialized in the first network node 101 by e.g., the third network node 103. The initialized first hierarchical level may further comprise the target object detection method, the target object detection threshold, a probability of detecting a target object, and the probability of false alarm of detecting a target object. Action 1102: The first network node 101 then evaluates the one or more sensing signals related to the one or more first cell grids in the first hierarchical level similar to as described in Action 604.

[0088] Action 1103: This step is similar to the Action 605 as described earlier. The first network node 101 then transmits the results from the evaluation in the form of a report to the third network node 103.

[0089] Action 1104: The third network node 103 evaluates the received report from the first network node 101 as described in Action 504.

[0090] Action 1105: The third network node 103 decides if the hierarchical search procedure as described in Actions 1102-1107 corresponding to Actions 502-506 is to be continued.

[0091] Action 1106: If the third network node 103 decides that the hierarchical search procedure is to continue further, the third network node 103 transmits a next hierarchical level comprising the information related to the one or more next cell grids to the first network node 101. This is similar to Action 506 as mentioned earlier.

[0092] Action 1107: The first network node 101 then begins its next e.g., the second repetition cycle of the sensing procedure by using the received next hierarchical level. The Actions 1102-1107 are repeated again in this repetition cycle e.e.g, second repetition cycle by detecting the target object in the one or more next cell grids.

[0093] Action 1108: If the third network node 103, during one of the repetition cycles, decides that the hierarchical search procedure has reached its required limit such that the size of the one or more cell grids in the respective hierarchical level is equal to or lesser than a required resolution of sensing of the target object, then the third network node 103 provides the detection decision.

[0094] Bandwidth adaptation

[0095] According to example embodiments herein as described in Action 603, the bandwidth of the sensing signal transmitted from the second network node 102 is decreased with increasing size of the cell grids, as the minimum distance between the cell grids is inversely proportional to the transmission signal bandwidth. However, a disadvantage of these embodiments is that an additional sensing signal needs to be transmitted from the second network node 102 for each hierarchical level, which is an overhead in terms of radio resource utilization and energy consumption. Furthermore, for each hierarchical level the first network node 101 needs to report the preprocessed received one or more sensing signals to the third network node 103 that is responsible for the combining of these sensing signals for the hypothesis testing i.e., detection of the target object. This may be a significant overhead, in particular if the first network node 101 is a UE such as e.g., UE 121 that need to use the radio interface for the reporting.

[0096] In some embodiments, the sensing signal bandwidth adaptation is achieved by using a sensing signal transmission bandwidth that is large enough to reach the smallest target cell grid resolution size and adapt the bandwidth of the first network node 101 to span only a portion of the bandwidth of the transmitted sensing signal. Adapting the bandwidth at the first network node 101 according to these embodiments have the benefit over adapting the bandwidth of transmission at the second network node 102 because the hierarchical search may herein be performed based on a single transmitted signal that is originally received and sampled at the full bandwidth at the first network node 101 and from which then a smaller bandwidth is extracted that fits the size of cell grid of the currently evaluated hierarchical level. This may be achieved e.g., by applying a Fast Fourier Transform (FFT) on the full-bandwidth sampled signal and then using a range of subcarriers according to the desired bandwidth, discarding the remaining subcarriers in the first network node 101. A drawback of these embodiments may be that the energy contained in the discarded subcarriers is lost for the current hierarchical level, implying reduced detection performance.

[0097] In some embodiments, the full bandwidth for the reception of the signal at the first network node 101 is used and then a windowing i.e., a window function over the subcarriers in the first network node 101 is applied. The window function may be rectangular. The window function may be required to suppress sidelobes and widen main lobe. A disadvantage of these embodiments may be that also here energy is lost due to suppression of some subcarriers.

[0098] In some embodiments, the reception bandwidth may be split into two portions and the reception may be performed twice by the first network node 101. In these embodiments, the lower part of the bandwidth of the received signal is correlated with the lower part of the bandwidth of the transmitted signal i.e., by using the lower half of the subcarriers in an OFDM system. In these embodiments, the upper part of the bandwidth of the received signal is correlated with the upper part of the bandwidth of the transmitted signal i.e., using the upper half of the subcarriers in an OFDM system. The two portions of the bandwidth that are split may be overlapping or non-overlapping. By splitting the bandwidth into two parts, the main lobe of the time-domain autocorrelation function of each half-bandwidth signal doubles, making this signal suitable for twice as large cell grids. To avoid the energy loss mentioned in the earlier example embodiments, correlations are calculated with each half-bandwidth signal and then subsequently combined to mitigate the energy loss. Instead of splitting the bandwidth into two parts it may be split into multiple parts, and each part may be separately filtered and subsequently combined.

[0099] In some embodiments, sequences used for the sensing signal with special properties such as e.g., Zadoff-Chu sequences e.g., with good periodic autocorrelation and robustness to high Doppler shift i.e. , velocity are transmitted from the second network node 102 as sensing signals mapped to subcarriers. In these embodiments, selecting portions of bandwidth of the original transmitted signal bandwidth as described in earlier example embodiments for processing at the first network node 101 may destroy some of the sequence properties. In these embodiments, it is required to transmit a wideband first sequence on a first comb-2 and two narrowband second and third sequences and the other comb-2, in the lower and upper allocated frequency allocation. Figure 12 illustrated a wideband sensing signal transmitted on a first comb and two narrowband sensing signals transmitted on a second comb.

[0100] According to the example as illustrated in Figure 12, in the first hierarchical level the detection of the target object may be performed by the third network node 103 based on coherently combining the one or more first reports comprising the detection results obtained with narrowband second and third sequence. Due to the combining, energy from both sequences may be utilized. Since each of the second and third sequence of the sensing signal are narrowband, they may have a wide time-domain autocorrelation main peak and may thus be suitable for a coarser cell grid i.e., larger cell grids in the initial repetition cycles of the sensing procedure. In the next hierarchical levels with cell grids of smaller size, the detection of the target object may be based on the wideband first sequence. Since the signal sequence is wideband, it may have a narrow time-domain autocorrelation main peak and may thus be suitable for a finer cell grid i.e., smaller cell grids in the latter repetition cycles of the sensing procedure. Second and third sequences may be the same or different sequences. An advantage of these example embodiments of bandwidth adaptation is that special sequences with very good properties such as e.g. Zadoff-Chu sequeces with good periodic ACF and robustness towards high Doppler shifts, may be used and that a single transmission of the sensing signal may be sufficient. A drawback may be that each hierarchical level only uses half of the subcarriers i.e., one comb and thus only half of the total energy. Instead of using a comb-2, other comb distances may be used as well. Instead of using two narrowband sequences more than two narrowband sequences may be used. Using different second and third sequences may result in a time-domain signal with lower Peak to Average Power Ratio (PAPR) which is preferable for the power amplifier at the second network node 102. This may however depend on how the remaining part of the carrier is used.

[0101] Signalling

[0102] Signalling is reguired to exchange hierarchical information, signal configuration, and measurement results according to example embodiments herein among the second network node 102, the first network node 101 , and the third network node 103. Hierarchical information when used herein refer to e.g., size of the cell grids, which cell grids are currently processed, and the target object detection method. Signal configuration when used herein refer to configurations related to e.g., bandwidth, seguences, and comb. Measurement results when used herein correspond to e.g., correlator output power, and result of the target object detection method. The signalling may depend on the type of the third network node 103, second network node 102, and the first network node 101. As described earlier, the first network node 101 may comprise a RAN node such as e.g., RAN node 111 e.g., a base station, or a UE such as e.g., the UE 121. The second network node 102 may comprise a RAN node such as e.g., RAN node 111 e.g., a base station, or a UE such as e.g., the UE 121. The third network node 103 may comprise a RAN node such as e.g., RAN node 113 e.g., a base station, or a core network node such as e.g., CN node 131. The signalling may also depend on where the third network node 103 is located.

[0103] Sensing between RAN nodes

[0104] In this case, the sensing is performed between RAN nodes e.g., base stations i.e., the first network node 101 and the second network node 102 are both RAN nodes such as e.g., RAN node 111 and RAN node 112, respectively. The third network node 103 may be within a RAN node e.g., base station such that e.g., the RAN node 113. In such a scenario, standardized signalling between base stations may be used, such as e.g., the Xn interface. Standardized signalling allows sensing operations to be performed according to example embodiments herein between RAN nodes from different vendors. In case the third network node 103 is not part of the RAN node but a CN node such as e.g., the CN node 131 , signalling between the third network node 103 and the second network node 102 such as e.g., RAN node 112 and between the third network node 103 and the first network node 101 such as e.g., RAN node 111 is needed to exchange hierarchical information, signal configuration, and measurement results. Examples of such signalling may be an extension to the NRPPa defined in 3GPP TS38.455, or be part of a new protocol that may be specified for sensing rather than positioning functionality.

[0105] Sensing between UEs or between RAN node and UE

[0106] In this case, the sensing may be performed between a RAN node and a UE e.g., the first network node 101 is e.g., RAN node 111 and the second network node 102 is e.g., UE 122 or the sensing may be performed between UEs e.g., first network node 101 is e.g., UE 121 and second network node 102 is e.g., UE 122. In such a scenario, air interface control signalling such as e.g., L1 / L2 control signalling, MAC CE signalling, and RRC signalling may be used to exchange hierarchical information and signal configuration. Measurement results may either be exchanged via a control channel or data channel such as e.g., Physical Data Shared Channel (PDSCH) or Physical Uplink Shared Channel (PUSCH) or sidelink channel. In a scenario where the second network node 102 is a RAN node such as e.g., RAN node 112 and the third network node 103 is a CN node such as e.g., CN node 131 , standardized signalling between the third network node 103 and second network node 102 may be used to inform second network node 102 at least about hierarchical information. For exchange of signal configuration and measurement results, signals such as e.g., an extension to the NRPPa defined in 3GPP TS38.455, or be part of a new protocol that may be specified for sensing rather than positioning functionality may be used. In the case where the first network node 101 and the second network node 102 are UEs such as e.g., UE 121 and UE 122, respectively, standardized over-the-air signalling may be used by the third network node 103 to inform the UEs at least about signal configuration, and hierarchical information.

[0107] To perform the method actions above, the third network node 103 is configured to handle signals related to sensing of one or more target objects in a geographical area of a communications network 100. The sensing of the one or more target objects is adapted to be performed by dividing a sensing cell in the communications network 100 into one or more cell grids. The sensing cell is a geographical area in the communications network 100 comprising the one or more target objects.

[0108] The third network node 103 may comprise an arrangement depicted in Figure 13. The third network node 103 may comprise an input and output interface 1300 configured to communicate in the communications network 100, e.g., with the first network node 101 and the second network node 102. The input and output interface 1300 may comprise a wireless receiver not shown, and a wireless transmitter not shown. The third network node 103 is further configured to obtain, from one or more first network nodes 101 , one or more first reports related to a first hierarchical level. The first hierarchical level is adapted to comprise one or more first cell grids of a first size. The one or more first reports is adapted to comprise information related to a preprocessing, performed by the respective one or more first network nodes 101. The preprocessing is of one or more sensing signals received from the one or more target objects in the one or more first cell grids.

[0109] The third network node 103 is further configured to evaluate the one or more first reports based on one or more out of a target object detection method, a target object detection threshold, a probability of detecting a target object, and a probability of false alarm of detecting a target object.

[0110] The third network node 103 is further configured to, based on the evaluation, compute a next hierarchical level comprising one or more next cell grids. This is performed by further being configured to select one or more cell grids out of the one or more first cell grids and divide the selected one or more cell grids into a second size. The second size is smaller than the first size.

[0111] The third network node 103 is further configured to transmit the next hierarchical level to one or more first network nodes 101.

[0112] The third network node 103 may further be configured to transmit the first hierarchical level to the one or more first network nodes 101.

[0113] The third network node 103 may further be configured to instruct one or more out of: one or more second network nodes 102 to transmit the one or more sensing signals, and the one or more first network nodes 101 to receive the one or more sensing signals.

[0114] In some embodiments, the first hierarchical level and the next hierarchical level further comprises, specific to the first hierarchical level and the next hierarchical level, one or more out of: a target object detection method, a target object detection threshold, a probability of detecting a target object, and a probability of false alarm of detecting a target object.

[0115] In some embodiments, the first network node 101 is adapted to be represented by a receiving node comprising any one out of: a RAN node, a base station, a UE.

[0116] In some embodiments, the second network node 102 is adapted to be represented by a transmitting node comprising any one out of: a RAN node, a base station, a UE.

[0117] In some embodiments, the third network node 103 is adapted to be represented by a processing node comprising any one out of: a RAN node, a base station, a core network node. To perform the method actions above, the first network node 101 is configured to handle signals related to sensing of one or more target objects in a geographical area of a communications network 100. The sensing of the one or more target objects is adapted to be performed by dividing a sensing cell in the communications network 100 into one or more cell grids. The sensing cell is a geographical area in the communications network 100 comprising the one or more target objects.

[0118] The first network node 101 may comprise an arrangement depicted in Figure 14. The first network node 101 may comprise an input and output interface 1400 configured to communicate in the communications network 100, e.g., with the third network node 103 and the second network node 102. The input and output interface 1400 may comprise a wireless receiver not shown, and a wireless transmitter not shown.

[0119] The first network node 101 is further being configured to receive a first hierarchical level from a third network node 103. The first hierarchical level is adapted to comprise one or more first cell grids of a first size.

[0120] The first network node 101 is further being configured to receive one or more sensing signals from the one or more target objects in the one or more first cell grids adapted to be comprised in the first hierarchical level.

[0121] The first network node 101 is further being configured to preprocess the received one or more sensing signals based on one or more out of a target object detection method, a target object detection threshold, a probability of detecting a target object, a probability of false alarm of detecting a target object and a filtering of the received one or more sensing signals.

[0122] The first network node 101 is further being configured to transmit a first report to the third network node 103. The first report is adapted to comprise information related to the preprocessing of the one or more sensing signals.

[0123] The first network node 101 is further being configured to, based on the transmitted first report, receive from the third network node 103 a next hierarchical level comprising one or more next cell grids. The one or more next cell grids is adapted to comprise one or more cell grids selected out of the one or more first cell grids and further divided into a second size. The second size is smaller than the first size.

[0124] In some embodiments, the first network node 101 is further being configured to receive an instruction from the third network node 103 to receive the one or more sensing signals from the one or more target objects in the one or more first cell grids adapted to be comprised in the first hierarchical level. The one or more sensing signals may be transmitted by a second network node 102.

[0125] In some embodiments, a bandwidth and / or a beamwidth of the one or more sensing signals transmitted from the second network node 102 is adapted to be based on the size of the one or more cell grids in each hierarchical level.

[0126] In some embodiments, a bandwidth of reception of the first network node 101 is adapted to span a portion of a bandwidth of transmission of the second network node 102, and

[0127] In some embodiments, a bandwidth of reception of the first network node 101 is a bandwidth of transmission of the second network node 102. In these embodiments, the first network node 101 and / or the second network node 102 is adapted to apply a window function to receive the one or more sensing signals.

[0128] In some embodiments, the first hierarchical level and the next hierarchical level further comprises, specific to the first hierarchical level and the next hierarchical level, one or more out of: a target object detection method, a target object detection threshold, a probability of detecting a target object, and a probability of false alarm of detecting a target object.

[0129] In some embodiments, the first network node 101 is adapted to be represented by a receiving node comprising any one out of: a RAN node, a base station, a UE.

[0130] In some embodiments, the second network node 102 is adapted to be represented by a transmitting node comprising any one out of: a RAN node, a base station, a UE.

[0131] In some embodiments, the third network node 103 is adapted to be represented by a processing node comprising any one out of: a RAN node, a base station, a core network node.

[0132] Embodiments herein may be implemented through a respective processor or one or more processors, such as the respective processor 1310 of a processing circuitry in the third network node 103 depicted in Figure 13, and processor 1410 of a processing circuitry in the first network node 101 depicted in Figure 14 together with respective computer program code for performing the functions and actions of the embodiments herein. The program code mentioned above may also be provided as a computer program product, for instance in the form of a data carrier carrying computer program code for performing the embodiments herein when being loaded into the respective third network node 103 and first network node 101. One such carrier may be in the form of a CD ROM disc. It is however feasible with other data carriers such as a memory stick. The computer program code may furthermore be provided as pure program code on a server and downloaded to the respective third network node 103 and first network node 101.

[0133] The third network node 103 and first network node 101 may further comprise a respective memory 1320 and memory 1420 comprising one or more memory units. The respective memory 1320 and memory 1420 comprises instructions executable by the processor in the respective third network node 103 and first network node 101. The respective memory 1320 and memory 1420 are arranged to be used to store e.g., media functions, indications, tags, information, data, configurations, communication data, and applications to perform the methods herein when being executed in the respective third network node 103 and first network node 101.

[0134] In some embodiments, a respective computer program 1330 and computer program 1430 comprises instructions, which when executed by the respective at least one processor 1310 and processor 1410, cause the at least one processor of respective third network node 103 and first network node 101 to perform the actions above.

[0135] In some embodiments, a respective carrier 1340 and carrier 1440 comprises the respective computer program 1330 and computer program 1430, wherein the respective carrier 1340 and carrier 1440 is one of an electronic signal, an optical signal, an electromagnetic signal, a magnetic signal, an electric signal, a radio signal, a microwave signal, or a computer-readable storage medium.

[0136] Those skilled in the art will appreciate that units in the respective third network node 103 and first network node 101 described above may refer to a combination of analog and digital circuits, and / or one or more processors configured with software and / or firmware, e.g. stored in the respective third network node 103 and first network node 101 , that when executed by the respective one or more processors such as the processors described above. One or more of these processors, as well as the other digital hardware, may be included in a single Application-Specific Integrated Circuitry ASIC, or several processors and various digital hardware may be distributed among several separate components, whether individually packaged or assembled into a System-on-a-Chip (SoC).

[0137] Figure 15 shows an example of a communication system QQ100 in accordance with some embodiments.

[0138] In the example, the communication system QQ100 includes a telecommunication network QQ102 that includes an access network QQ104, such as a radio access network (RAN), and a core network QQ106, which includes one or more core network nodes QQ108. The access network QQ104 includes one or more access network nodes, such as network nodes QQ110a and QQ110b (one or more of which may be generally referred to as network nodes QQ110), or any other similar 3rd Generation 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 QQ102 includes one or more Open-RAN (ORAN) network nodes. An ORAN network node is a node in the telecommunication network QQ102 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 QQ102, including one or more network nodes QQ110 and / or core network nodes QQ108.

[0139] Examples of an ORAN network node include an open radio unit (0-Rll), an open distributed unit (0-Dll), an open central unit (O-CU), including an O-CU control plane (O- CLI-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 QQ110 facilitate direct or indirect connection of user equipment (UE), such as by connecting UEs QQ112a, QQ112b, QQ112c, and QQ112d (one or more of which may be generally referred to as UEs QQ112) to the core network QQ106 over one or more wireless connections.

[0140] 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 QQ100 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 QQ100 may include and / or interface with any type of communication, telecommunication, data, cellular, radio network, and / or other similar type of system.

[0141] The UEs QQ112 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 QQ110 and other communication devices. Similarly, the network nodes QQ110 are arranged, capable, configured, and / or operable to communicate directly or indirectly with the UEs QQ112 and / or with other network nodes or equipment in the telecommunication network QQ102 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 QQ102.

[0142] In the depicted example, the core network QQ106 connects the network nodes QQ110 to one or more host computing systems, such as host QQ116. 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 QQ106 includes one more core network nodes (e.g., core network node QQ108) 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 QQ108. Example core network nodes include functions of one or more of a Mobile Switching Center (MSC), Mobility Management Entity (MME), Home Subscriber Server (HSS), Access and Mobility Management Function (AMF), Session Management Function (SMF), Authentication Server Function (AUSF), Subscription Identifier De-concealing function (SIDF), Unified Data Management (UDM), Security Edge Protection Proxy (SEPP), Network Exposure Function (NEF), and / or a User Plane Function (UPF).

[0143] The host QQ116 may be under the ownership or control of a service provider other than an operator or provider of the access network QQ104 and / or the telecommunication network QQ102. The host QQ116 may host a variety of applications to provide one or more service. Examples of such applications include live and pre-recorded audio / video content, data collection services such as retrieving and compiling data on various ambient conditions detected by a plurality of UEs, analytics functionality, social media, functions for controlling or otherwise interacting with remote devices, functions for an alarm and surveillance center, or any other such function performed by a server.

[0144] As a whole, the communication system QQ100 of 9 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.

[0145] In some examples, the telecommunication network QQ102 is a cellular network that implements 3GPP standardized features. Accordingly, the telecommunications network QQ102 may support network slicing to provide different logical networks to different devices that are connected to the telecommunication network QQ102. For example, the telecommunications network QQ102 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.

[0146] In some examples, the UEs QQ112 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 QQ104 on a predetermined schedule, when triggered by an internal or external event, or in response to requests from the access network QQ104. 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).

[0147] In the example, the hub QQ114 communicates with the access network QQ104 to facilitate indirect communication between one or more UEs (e.g., UE QQ112c and / or QQ112d) and network nodes (e.g., network node QQ110b). In some examples, the hub QQ114 may be a controller, router, content source and analytics, or any of the other communication devices described herein regarding UEs. For example, the hub QQ114 may be a broadband router enabling access to the core network QQ106 for the UEs. As another example, the hub QQ114 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 QQ110, or by executable code, script, process, or other instructions in the hub QQ114. As another example, the hub QQ114 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 QQ114 may be a content source. For example, for a UE that is a VR device, display, loudspeaker, or other media delivery device, the hub QQ114 may retrieve VR assets, video, audio, or other media or data related to sensory information via a network node, which the hub QQ114 then provides to the UE either directly, after performing local processing, and / or after adding additional local content. In still another example, the hub QQ114 acts as a proxy server or orchestrator for the UEs, in particular if one or more of the UEs are low energy loT devices.

[0148] The hub QQ114 may have a constant / persistent or intermittent connection to the network node QQ110b. The hub QQ114 may also allow for a different communication scheme and / or schedule between the hub QQ114 and UEs (e.g., UE QQ112c and / or QQ112d), and between the hub QQ114 and the core network QQ106. In other examples, the hub QQ114 is connected to the core network QQ106 and / or one or more UEs via a wired connection. Moreover, the hub QQ114 may be configured to connect to an M2M service provider over the access network QQ104 and / or to another UE over a direct connection. In some scenarios, UEs may establish a wireless connection with the network nodes QQ110 while still connected via the hub QQ114 via a wired or wireless connection. In some embodiments, the hub QQ114 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 QQ110b. In other embodiments, the hub QQ114 may be a non-dedicated hub - that is, a device which is capable of operating to route communications between the UEs and network node QQ110b, but which is additionally capable of operating as a communication start and / or end point for certain data channels.

[0149] Figure 16 shows a UE QQ200 in accordance with some embodiments. The UE QQ200 presents additional details of some embodiments of the UE QQ112 of Figure 15 and of the first network node 101 such as e.g., UE 121 and second network node 102 such as e.g., UE 122 of Figure 4 as described in example embodiments herein. As used herein, a UE refers to a device capable, configured, arranged and / or operable to communicate wirelessly with network nodes such as e.g., first network node 101 , second network node 102, and third network node 103 and / or other UEs such as e.g., UE 121, and UE 122. 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 cameras, gaming console or device, music storage / playback device, wearable terminal device, wireless endpoint, mobile station, tablet, laptop, laptop-embedded equipment (LEE), laptop-mounted equipment (LME), an Augmented Reality (AR) or Virtual Reality (VR) device, wireless customerpremise equipment (CPE), vehicle, vehicle-mounted or vehicle embedded / integrated wireless device, etc. Other examples include any UE identified by the 3rd Generation 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.

[0150] 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), or vehicle-to-everything (V2X). In other examples, a UE may not necessarily have a user in the sense of a human user who owns and / or operates the relevant device. Instead, a UE may represent a device that is intended for sale to, or operation by, a human user but which may not, or which may not initially, be associated with a specific human user (e.g., a smart sprinkler controller). Alternatively, a UE may represent a device that is not intended for sale to, or operation by, an end user but which may be associated with or operated for the benefit of a user (e.g., a smart power meter).

[0151] The UE QQ200 includes processing circuitry QQ202 that is operatively coupled via a bus QQ204 to an input / output interface QQ206, a power source QQ208, a memory QQ210, a communication interface QQ212, and / or any other component, or any combination thereof. Certain UEs may utilize all or a subset of the components shown in 10. The level of integration between the components may vary from one UE to another UE. Further, certain UEs may contain multiple instances of a component, such as multiple processors, memories, transceivers, transmitters, receivers, etc.

[0152] The processing circuitry QQ202 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 QQ210. The processing circuitry QQ202 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 QQ202 may include multiple central processing units (CPUs).

[0153] In the example, the input / output interface QQ206 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 QQ200. 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.

[0154] In some embodiments, the power source QQ208 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 QQ208 may further include power circuitry for delivering power from the power source QQ208 itself, and / or an external power source, to the various parts of the UE QQ200 via input circuitry or an interface such as an electrical power cable. Delivering power may be, for example, for charging of the power source QQ208. Power circuitry may perform any formatting, converting, or other modification to the power from the power source QQ208 to make the power suitable for the respective components of the UE QQ200 to which power is supplied.

[0155] The memory QQ210 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 QQ210 includes one or more application programs QQ214, such as an operating system, web browser application, a widget, gadget engine, or other application, and corresponding data QQ216. The memory QQ210 may store, for use by the UE QQ200, any of a variety of various operating systems or combinations of operating systems.

[0156] The memory QQ210 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 QQ210 may allow the UE QQ200 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 QQ210, which may be or comprise a device-readable storage medium.

[0157] The processing circuitry QQ202 may be configured to communicate with an access network or other network using the communication interface QQ212. The communication interface QQ212 may comprise one or more communication subsystems and may include or be communicatively coupled to an antenna QQ222. The communication interface QQ212 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 QQ218 and / or a receiver QQ220 appropriate to provide network communications (e.g., optical, electrical, frequency allocations, and so forth). Moreover, the transmitter QQ218 and receiver QQ220 may be coupled to one or more antennas (e.g., antenna QQ222) and may share circuit components, software or firmware, or alternatively be implemented separately.

[0158] In the illustrated embodiment, communication functions of the communication interface QQ212 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.

[0159] 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.

[0160] Regardless of the type of sensor, a UE may provide an output of data captured by its sensors, through its communication interface QQ212, via a wireless connection to a network node. Data captured by sensors of a UE can be communicated through a wireless connection to a network node via another UE. The output may be periodic (e.g., once every 15 minutes if it reports the sensed temperature), random (e.g., to even out the load from reporting from several sensors), in response to a triggering event (e.g., when moisture is detected an alert is sent), in response to a request (e.g., a user initiated request), or a continuous stream (e.g., a live video feed of a patient).

[0161] As another example, a UE comprises an actuator, a motor, or a switch, related to a communication interface configured to receive wireless input from a network node via a wireless connection. In response to the received wireless input the states of the actuator, the motor, or the switch may change. For example, the UE may comprise a motor that adjusts the control surfaces or rotors of a drone in flight according to the received input or to a robotic arm performing a medical procedure according to the received input.

[0162] 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 a device which is or which is 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 smartwatch, a fitness tracker, a wearable for tactile augmentation or sensory enhancement, a water sprinkler, an animal- or item-tracking device, a sensor for monitoring a plant or animal, an industrial robot, an Unmanned Aerial Vehicle (UAV), and any kind of medical device, like a heart rate monitor or a remote controlled surgical robot. A UE in the form of an loT device comprises circuitry and / or software in dependence of the intended application of the loT device in addition to other components as described in relation to the UE QQ200 shown in Figure 16.

[0163] 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.

[0164] 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.

[0165] Figure 17 shows a network node QQ300 in accordance with some embodiments. The network node QQ300 presents additional details of some embodiments of the first network node 101 such as e.g., RAN node 111 , second network node 102 such as e.g., RAN node 112 and third network node 103 such as e.g., RAN node 113 of Figure 4 as described in example embodiments herein. 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).

[0166] 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).

[0167] 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- cel l / multicast coordination entities (MCEs), Operation and Maintenance (O&M) nodes, Operations Support System (OSS) nodes, Self-Organizing Network (SON) nodes, positioning nodes (e.g., Evolved Serving Mobile Location Centers (E-SMLCs)), and / or Minimization of Drive Tests (MDTs).

[0168] The network node QQ300 includes a processing circuitry QQ302, a memory QQ304, a communication interface QQ306, and a power source QQ308. The network node QQ300 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 QQ300 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 QQ300 may be configured to support multiple radio access technologies (RATs). In such embodiments, some components may be duplicated (e.g., separate memory QQ304 for different RATs) and some components may be reused (e.g., a same antenna QQ310 may be shared by different RATs). The network node QQ300 may also include multiple sets of the various illustrated components for different wireless technologies integrated into network node QQ300, 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 QQ300. The processing circuitry QQ302 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 QQ300 components, such as the memory QQ304, to provide network node QQ300 functionality.

[0169] In some embodiments, the processing circuitry QQ302 includes a system on a chip (SOC). In some embodiments, the processing circuitry QQ302 includes one or more of radio frequency (RF) transceiver circuitry QQ312 and baseband processing circuitry QQ314. In some embodiments, the radio frequency (RF) transceiver circuitry QQ312 and the baseband processing circuitry QQ314 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 QQ312 and baseband processing circuitry QQ314 may be on the same chip or set of chips, boards, or units.

[0170] The memory QQ304 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 QQ302. The memory QQ304 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 QQ302 and utilized by the network node QQ300. The memory QQ304 may be used to store any calculations made by the processing circuitry QQ302 and / or any data received via the communication interface QQ306. In some embodiments, the processing circuitry QQ302 and memory QQ304 is integrated.

[0171] The communication interface QQ306 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 QQ306 comprises port(s) / terminal(s) QQ316 to send and receive data, for example to and from a network over a wired connection. The communication interface QQ306 also includes radio front-end circuitry QQ318 that may be coupled to, or in certain embodiments a part of, the antenna QQ310. Radio front-end circuitry QQ318 comprises filters QQ320 and amplifiers QQ322. The radio front-end circuitry QQ318 may be connected to an antenna QQ310 and processing circuitry QQ302. The radio front-end circuitry may be configured to condition signals communicated between antenna QQ310 and processing circuitry QQ302. The radio front-end circuitry QQ318 may receive digital data that is to be sent out to other network nodes or UEs via a wireless connection. The radio front-end circuitry QQ318 may convert the digital data into a radio signal having the appropriate channel and bandwidth parameters using a combination of filters QQ320 and / or amplifiers QQ322. The radio signal may then be transmitted via the antenna QQ310. Similarly, when receiving data, the antenna QQ310 may collect radio signals which are then converted into digital data by the radio front-end circuitry QQ318. The digital data may be passed to the processing circuitry QQ302. In other embodiments, the communication interface may comprise different components and / or different combinations of components.

[0172] In certain alternative embodiments, the network node QQ300 does not include separate radio front-end circuitry QQ318, instead, the processing circuitry QQ302 includes radio front-end circuitry and is connected to the antenna QQ310. Similarly, in some embodiments, all or some of the RF transceiver circuitry QQ312 is part of the communication interface QQ306. In still other embodiments, the communication interface QQ306 includes one or more ports or terminals QQ316, the radio front-end circuitry QQ318, and the RF transceiver circuitry QQ312, as part of a radio unit (not shown), and the communication interface QQ306 communicates with the baseband processing circuitry QQ314, which is part of a digital unit (not shown).

[0173] The antenna QQ310 may include one or more antennas, or antenna arrays, configured to send and / or receive wireless signals. The antenna QQ310 may be coupled to the radio front-end circuitry QQ318 and may be any type of antenna capable of transmitting and receiving data and / or signals wirelessly. In certain embodiments, the antenna QQ310 is separate from the network node QQ300 and connectable to the network node QQ300 through an interface or port.

[0174] The antenna QQ310, communication interface QQ306, and / or the processing circuitry QQ302 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 QQ310, the communication interface QQ306, and / or the processing circuitry QQ302 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.

[0175] The power source QQ308 provides power to the various components of network node QQ300 in a form suitable for the respective components (e.g., at a voltage and current level needed for each respective component). The power source QQ308 may further comprise, or be coupled to, power management circuitry to supply the components of the network node QQ300 with power for performing the functionality described herein. For example, the network node QQ300 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 QQ308. As a further example, the power source QQ308 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.

[0176] Embodiments of the network node QQ300 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 QQ300 may include user interface equipment to allow input of information into the network node QQ300 and to allow output of information from the network node QQ300. This may allow a user to perform diagnostic, maintenance, repair, and other administrative functions for the network node QQ300. In some embodiments providing a core network node, such as core network node 106 of Figure 4, some components, such as the radio front-end circuitry QQ318 and the RF transceiver circuitry QQ312 may be omitted.

[0177] Figure 18 is a block diagram illustrating a virtualization environment QQ400 in which functions implemented by some embodiments may be virtualized. In the present context, virtualizing means creating virtual versions of apparatuses or devices which may include virtualizing hardware platforms, storage devices and networking resources. As used herein, virtualization can be applied to any device described herein, or components thereof, and relates to an implementation in which at least a portion of the functionality is implemented as one or more virtual components. Some or all of the functions described herein may be implemented as virtual components executed by one or more virtual machines (VMs) implemented in one or more virtual environments QQ400 hosted by one or more of hardware nodes, such as a hardware computing device that operates as a network node, UE, core network node, or host. Further, in embodiments in which the virtual node does not require radio connectivity (e.g., a core network node or host), then the node may be entirely virtualized. In some embodiments, the virtualization environment QQ400 includes components defined by the O-RAN Alliance, such as an O-Cloud environment orchestrated by a Service Management and Orchestration Framework via an 0-2 interface. Virtualization may facilitate distributed implementations of a network node, UE, core network node, or host.

[0178] Applications QQ402 (which may alternatively be called software instances, virtual appliances, network functions, virtual nodes, virtual network functions, etc.) are run in the virtualization environment Q400 to implement some of the features, functions, and / or benefits of some of the embodiments disclosed herein.

[0179] Hardware QQ404 includes processing circuitry, memory that stores software and / or instructions executable by hardware processing circuitry, and / or other hardware devices as described herein, such as a network interface, input / output interface, and so forth. Software may be executed by the processing circuitry to instantiate one or more virtualization layers QQ406 (also referred to as hypervisors or virtual machine monitors (VMMs)), provide VMs QQ408a and QQ408b (one or more of which may be generally referred to as VMs QQ408), and / or perform any of the functions, features and / or benefits described in relation with some embodiments described herein. The virtualization layer QQ406 may present a virtual operating platform that appears like networking hardware to the VMs QQ408.

[0180] The VMs QQ408 comprise virtual processing, virtual memory, virtual networking or interface and virtual storage, and may be run by a corresponding virtualization layer QQ406. Different embodiments of the instance of a virtual appliance QQ402 may be implemented on one or more of VMs QQ408, and the implementations may be made in different ways. Virtualization of the hardware is in some contexts referred to as network function virtualization (NFV). NFV may be used to consolidate many network equipment types onto industry standard high volume server hardware, physical switches, and physical storage, which can be located in data centers, and customer premise equipment.

[0181] In the context of NFV, a VM QQ408 may be a software implementation of a physical machine that runs programs as if they were executing on a physical, non-virtualized machine. Each of the VMs QQ408, and that part of hardware QQ404 that executes that VM, be it hardware dedicated to that VM and / or hardware shared by that VM with others of the VMs, forms separate virtual network elements. Still in the context of NFV, a virtual network function is responsible for handling specific network functions that run in one or more VMs QQ408 on top of the hardware QQ404 and corresponds to the application QQ402.

[0182] Hardware QQ404 may be implemented in a standalone network node with generic or specific components. Hardware QQ404 may implement some functions via virtualization. Alternatively, hardware QQ404 may be part of a larger cluster of hardware (e.g. such as in a data center or CPE) where many hardware nodes work together and are managed via management and orchestration QQ410, which, among others, oversees lifecycle management of applications QQ402. In some embodiments, hardware QQ404 is coupled to one or more radio units that each include one or more transmitters and one or more receivers that may be coupled to one or more antennas. Radio units may communicate directly with other hardware nodes via one or more appropriate network interfaces and may be used in combination with the virtual components to provide a virtual node with radio capabilities, such as a radio access node or a base station. In some embodiments, some signaling can be provided with the use of a control system QQ412 which may alternatively be used for communication between hardware nodes and radio units.

[0183] Although the computing devices described herein (e.g., UEs, network nodes) may include the illustrated combination of hardware components, other embodiments may comprise computing devices with different combinations of components. It is to be understood that these computing devices may comprise any suitable combination of hardware and / or software needed to perform the tasks, features, functions and methods disclosed herein. Determining, calculating, obtaining or similar operations described herein may be performed by processing circuitry, which may process information by, for example, converting the obtained information into other information, comparing the obtained information or converted information to information stored in the network node, and / or performing one or more operations based on the obtained information or converted information, and as a result of said processing making a determination. Moreover, while components are depicted as single boxes located within a larger box, or nested within multiple boxes, in practice, computing devices may comprise multiple different physical components that make up a single illustrated component, and functionality may be partitioned between separate components. For example, a communication interface may be configured to include any of the components described herein, and / or the functionality of the components may be partitioned between the processing circuitry and the communication interface. In another example, non-computationally intensive functions of any of such components may be implemented in software or firmware and computationally intensive functions may be implemented in hardware.

[0184] In certain embodiments, some or all of the functionality described herein may be provided by processing circuitry executing instructions stored on in memory, which in certain embodiments may be a computer program product in the form of a non-transitory computer-readable storage medium. In alternative embodiments, some or all of the functionality may be provided by the processing circuitry without executing instructions stored on a separate or discrete device-readable storage medium, such as in a hard-wired manner. In any of those particular embodiments, whether executing instructions stored on a non-transitory computer-readable storage medium or not, the processing circuitry can be configured to perform the described functionality. The benefits provided by such functionality are not limited to the processing circuitry alone or to other components of the computing device, but are enjoyed by the computing device as a whole, and / or by end users and a wireless network generally.

[0185] When using the word "comprise" or “comprising” it shall be interpreted as nonlimiting, i.e. meaning "consist at least of".

[0186] It will be appreciated that the foregoing description and the accompanying drawings represent non-limiting examples of the methods and apparatus taught herein. As such, the apparatus and techniques taught herein are not limited by the foregoing description and accompanying drawings. Instead, the embodiments herein are limited only by the following claims and their legal equivalents.

Claims

1. CLAIMS1. A method performed by a third network node (103) for handling signals related to sensing of one or more target objects in a geographical area of a communications network (100), wherein the sensing of the one or more target objects is performed by dividing a sensing cell in the communications network (100) into one or more cell grids, which sensing cell is a geographical area in the communications network (100) comprising the one or more target objects, the method comprising: obtaining (503), from one or more first network nodes (101), one or more first reports related to a first hierarchical level, which first hierarchical level comprises one or more first cell grids of a first size, and wherein the one or more first reports comprise information related to a preprocessing, performed by the respective one or more first network nodes (101), of one or more sensing signals received from the one or more target objects in the one or more first cell grids, evaluating (504) the one or more first reports based on one or more out of: a target object detection method, a target object detection threshold, a probability of detecting a target object, and a probability of false alarm of detecting a target object, based on the evaluation, computing (505) a next hierarchical level comprising one or more next cell grids by selecting (505a) one or more cell grids out of the one or more first cell grids and dividing (505b) the selected one or more cell grids into a second size, which second size is smaller than the first size, and transmitting (506) the next hierarchical level to one or more first network nodes (101).

2. The method according to claim 1 , further comprising: transmitting (501) the first hierarchical level to the one or more first network nodes (101), and / or instructing (502) one or more out of: one or more second network nodes (102) to transmit the one or more sensing signals, and the one or more first network nodes (101) to receive the one or more sensing signals.

3. The method according to any of claims 1-2, wherein the instructing (502), obtaining (503), evaluating (504), computing (505), and transmitting (506) are repeated in repetition cycles, wherein the next hierarchical level from a first repetition cyclebecomes the first hierarchical level for a second repetition cycle, and wherein the repeating is performed until the size of the one or more cell grids is equal to or lesser than a pre-defined threshold, which pre-defined threshold is related to a resolution required of the sensing of the target object.

4. The method according to any of claims 1-3, wherein the first hierarchical level and the next hierarchical level further comprises, specific to the first hierarchical level and the next hierarchical level, one or more out of: a target object detection method, a target object detection threshold, a probability of detecting a target object, and a probability of false alarm of detecting a target object.

5. The method according to any of claims 1-4, wherein one or more out of: the first network node (101) is represented by a receiving node comprising any one out of: a RAN node, a base station, a UE, the second network node (102) is represented by a transmitting node comprising any one out of: a RAN node, a base station, a UE, and the third network node (103) is represented by a processing node comprising any one out of: a RAN node, a base station, a core network node.

6. A computer program comprising instructions, which when executed by a processor, causes the third network node (103) to perform actions according to any of the claims 1-5.

7. A carrier comprising the computer program of claim 6, wherein the carrier is one of an electronic signal, an optical signal, an electromagnetic signal, a magnetic signal, an electric signal, a radio signal, a microwave signal, or a computer-readable storage medium.

8. A method performed by a first network node (101) for handling signals related to sensing of one or more target objects in a geographical area of a communications network (100), wherein the sensing of the one or more target objects is performed by dividing a sensing cell in the communications network (100) into one or more cell grids, which sensing cell is a geographical area in the communications network (100) comprising the one or more target objects, the method comprising:receiving (601) a first hierarchical level from a third network node (103), which first hierarchical level comprises one or more first cell grids of a first size, receiving (603) one or more sensing signals from the one or more target objects in the one or more first cell grids comprised in the first hierarchical level, preprocessing (604) the received one or more sensing signals based on one or more out of: a target object detection method, a target object detection threshold, a probability of detecting a target object, a probability of false alarm of detecting a target object and a filtering of the received one or more sensing signals, transmitting (605) a first report to the third network node (103), which first report comprises information related to the preprocessing of the one or more sensing signals, and based on the transmitted first report, receiving (606) from the third network node (103) a next hierarchical level comprising one or more next cell grids, which one or more next cell grids comprises one or more cell grids selected out of the one or more first cell grids and further divided into a second size, which second size is smaller than the first size.

9. The method according to claim 8, further comprising: receiving (602) an instruction from the third network node (103) to receive the one or more sensing signals from the one or more target objects in the one or more first cell grids comprised in the first hierarchical level, which one or more sensing signals are transmitted by a second network node (102).

10. The method according to any of claims 8-9, wherein one or more out of: a bandwidth and / or a beamwidth of the one or more sensing signals transmitted from the second network node (102) is based on the size of the one or more cell grids in each hierarchical level, a bandwidth of reception of the first network node (101) spans a portion of a bandwidth of transmission of the second network node (102), and a bandwidth of reception of the first network node (101) is a bandwidth of transmission of the second network node (102), and wherein the first network node (101) and / or the second network node (102) applies a window function to receive the one or more sensing signals.

11. The method according to any of claims 8-10, wherein the first hierarchical level and the next hierarchical level further comprises, specific to the first hierarchical level and the next hierarchical level, one or more out of: a target object detection method, a target object detection threshold, a probability of detecting a target object, and a probability of false alarm of detecting a target object.

12. The method according to any of claims 8-11 , wherein one or more out of: the first network node (101) is represented by a receiving node comprising any one out of: a RAN node, a base station, a UE, the second network node (102) is represented by a transmitting node comprising any one out of: a RAN node, a base station, a UE, and the third network node (103) is represented by a processing node comprising any one out of: a RAN node, a base station, a core network node.

13. A computer program comprising instructions, which when executed by a processor, causes the first network node (101) to perform actions according to any of the claims 8-12.

14. A carrier comprising the computer program of claim 13, wherein the carrier is one of an electronic signal, an optical signal, an electromagnetic signal, a magnetic signal, an electric signal, a radio signal, a microwave signal, or a computer- readable storage medium.

15. A third network node (103) configured to handle signals related to sensing of one or more target objects in a geographical area of a communications network (100), wherein the sensing of the one or more target objects is adapted to be performed by dividing a sensing cell in the communications network (100) into one or more cell grids, which sensing cell is a geographical area in the communications network (100) comprising the one or more target objects, the third network node (103) further being configured to: obtain, from one or more first network nodes (101), one or more first reports related to a first hierarchical level, which first hierarchical level is adapted to comprise one or more first cell grids of a first size and wherein the one or more first reports is adapted to comprise information related to a preprocessing, performed by the respective one or more first network nodes (101), of one or moresensing signals received from the one or more target objects in the one or more first cell grids, evaluate the one or more first reports based on one or more out of: a target object detection method, a target object detection threshold, a probability of detecting a target object, and a probability of false alarm of detecting a target object, based on the evaluation, compute a next hierarchical level comprising one or more next cell grids by further being configured to select one or more cell grids out of the one or more first cell grids and divide the selected one or more cell grids into a second size, which second size is smaller than the first size, and transmit the next hierarchical level to one or more first network nodes (101).

16. The third network node (103) according to claim 15, further being configured to: transmit the first hierarchical level to the one or more first network nodes (101), and / or instruct one or more out of: one or more second network nodes (102) to transmit the one or more sensing signals, and the one or more first network nodes (101) to receive the one or more sensing signals.

17. The third network node (103) according to any of claims 15-16, wherein the first hierarchical level and the next hierarchical level further comprises, specific to the first hierarchical level and the next hierarchical level, one or more out of: a target object detection method, a target object detection threshold, a probability of detecting a target object, and a probability of false alarm of detecting a target object.

18. The third network node (103) according to any of claims 15-17, wherein one or more out of: the first network node (101) is adapted to be represented by a receiving node comprising any one out of: a RAN node, a base station, a UE, the second network node (102) is adapted to be represented by a transmitting node comprising any one out of: a RAN node, a base station, a UE, andthe third network node (103) is adapted to be represented by a processing node comprising any one out of: a RAN node, a base station, a core network node.

19. A first network node (101) configured to handle signals related to sensing of one or more target objects in a geographical area of a communications network (100), wherein the sensing of the one or more target objects is adapted to be performed by dividing a sensing cell in the communications network (100) into one or more cell grids, which sensing cell is a geographical area in the communications network (100) comprising the one or more target objects, the first network node (101) further being configured to: receive a first hierarchical level from a third network node (103), which first hierarchical level is adapted to comprise one or more first cell grids of a first size, receive one or more sensing signals from the one or more target objects in the one or more first cell grids adapted to be comprised in the first hierarchical level, preprocess the received one or more sensing signals based on one or more out of: a target object detection method, a target object detection threshold, a probability of detecting a target object, a probability of false alarm of detecting a target object and a filtering of the received one or more sensing signals, transmit a first report to the third network node (103), which first report is adapted to comprise information related to the preprocessing of the one or more sensing signals, and based on the transmitted first report, receive from the third network node (103) a next hierarchical level comprising one or more next cell grids, which one or more next cell grids is adapted to comprise one or more cell grids selected out of the one or more first cell grids and further divided into a second size, which second size is smaller than the first size.

20. The first network node (101) according to claim 19, further being configured to: receive an instruction from the third network node (103) to receive the one or more sensing signals from the one or more target objects in the one or more first cell grids adapted to be comprised in the first hierarchical level, which one or more sensing signals are transmitted by a second network node (102).

21. The first network node (101) according to any of claims 19-20, wherein one or more out of: a bandwidth and / or a beamwidth of the one or more sensing signals transmitted from the second network node (102) is adapted to be based on the size of the one or more cell grids in each hierarchical level, a bandwidth of reception of the first network node (101) is adapted to span a portion of a bandwidth of transmission of the second network node (102), and a bandwidth of reception of the first network node (101) is a bandwidth of transmission of the second network node (102), and wherein the first network node (101) and / or the second network node (102) is adapted to apply a window function to receive the one or more sensing signals.

22. The first network node (101) according to any of claims 19-21, wherein the first hierarchical level and the next hierarchical level further comprises, specific to the first hierarchical level and the next hierarchical level, one or more out of: a target object detection method, a target object detection threshold, a probability of detecting a target object, and a probability of false alarm of detecting a target object.

23. The first network node (101) according to any of claims 19-22, wherein one or more out of: the first network node (101) is adapted to be represented by a receiving node comprising any one out of: a RAN node, a base station, a UE, the second network node (102) is adapted to be represented by a transmitting node comprising any one out of: a RAN node, a base station, a UE, and the third network node (103) is adapted to be represented by a processing node comprising any one out of: a RAN node, a base station, a core network node.

Images