Node selection for detecting one or more objects in a joint communication and detection system

Abstract

A system (1) for enabling detection of one or more objects (9) is configured to: obtain detection requirements, e.g., information specifying an area of ​​interest, for detecting the one or more objects; obtain communication requirements, e.g., regarding throughput, latency, and / or reliability level; obtain information, e.g., node locations and receiver characteristics, for each of a set of nodes (11-12, 31-36); select a set of nodes from the set of nodes based on the detection requirements, communication requirements, and the information for each of the set of nodes; and instruct one or more nodes of the set of nodes to participate in detecting the one or more objects. At least one node of the set of nodes will transmit a wireless signal, and at least one node of the set of nodes will receive the wireless signal.

Description

[Technical Field]

[0001] The present invention relates to a system for enabling the detection of one or more objects, and to a node for participating in the detection of one or more objects. The present invention further relates to methods that enable the detection of one or more objects and methods that involve the detection of one or more objects.

[0002] The invention also relates to a computer program product enabling a computer system to carry out such a method. [Background technology]

[0003] Joint communication and sensing (JCAS) is considered one of the key 6G candidate technologies, in which the same system / network is used to perform both communication and sensing tasks. In this context, the term sensing typically refers to the detection and / or tracking of an object of interest, which may or may not be connected (or capable of being connected) to a mobile network in a communication sense. Use cases include real-time object detection for autonomous driving, intruder detection, UAV detection, and UAV flight control / coordination, as well as real-time monitoring, including high-precision object localization, for industrial applications. Objects of interest may have different attributes, such as shape, size, speed, distance, location, orientation, material type, color, temperature, heartbeat, pitch, yaw, and / or roll.

[0004] In detection, a distinction is made between a monitoring mode and a tracking mode. In monitoring mode, the detection objective is to detect the presence of a target object, which typically includes detecting one or more of the aforementioned object attributes, for example the object's location. In tracking mode, the detection objective is to follow the trajectory of a detected target object, which typically requires the object's speed, changes in speed, and the object's direction of movement.

[0005] Base stations (abbreviated as BS (Base station)) and / or ordinary mobile terminals, i.e., User Equipment (UE), can be used as JCAS nodes, for example. For example, a base station may communicate with ordinary mobile terminals, but is also used to sense / detect one or more objects. At least one JCAS node emits a radio signal, which is reflected by nearby objects. The reflected signal is received by the at least one JCAS node and can be processed to detect attributes of the object, such as the attributes mentioned above.

[0006] The paper "Enabling Joint Communication and Radar Sensing in Mobile Networks - A survey" by JAZhang et al. in IEEE Communications Surveys & Tutorials, Volume 24, No. 1, pp. 306-345, Q1 2022, investigates different techniques for realizing JCAS. There are generally the following options for the design of the radio signals used for sensing: 1. A dedicated sensing signal is designed for sensing and multiplexed with other sensing and / or communication signals in the code, time, frequency, and / or spatial domains. The advantage of this option is that the waveform is optimized for sensing, ultimately leading to higher sensing performance. The disadvantage of this option is that the same signal cannot be used for communication and sensing simultaneously, and resource consumption (e.g., time, frequency, or power) may result in being greater than options 2 and 3. 2. The same (new) radio signal (waveform) is designed for both communication and sensing, taking into account the communication and sensing requirements jointly. The advantage of this option over the design and implementation of both dedicated sensing and communication signals is lower implementation complexity. The use of such a signal (waveform) can also be relatively resource efficient when the signal is used for both communication and sensing simultaneously, since resources do not need to be used exclusively for the dedicated sensing signal. The disadvantage of this option over option 1 is that the performance of both communication and sensing is compromised, since the requirements for communication and sensing are significantly different. 3. Traditional communication radio signals (waveforms) designed for communication are used for both communication and sensing. The advantage of this option is that the waveforms used are optimized for the communication task, eliminating the need to design new waveforms for sensing. Existing communication systems, such as 5G and Wi-Fi, can be used, so existing hardware / devices can be used (potentially with software updates). The advantage of this option over using both dedicated sensing and communication signals is relatively high resource efficiency when signals are used simultaneously for communication and sensing, since resources do not need to be used exclusively for dedicated sensing signals. The disadvantage of this option over options 2 and 3 is potentially suboptimal sensing performance, since the communication signals are not designed / optimized for sensing. With this option, for example, a common reference signal and / or a signal with a communication payload can be used for sensing.

[0007] The dense deployment of cellular networks facilitates enormous sensing opportunities. The aforementioned document, "Enabling Joint Communication and Radar Sensing in Mobile Networks - A survey," identifies different existing communication channels / signals in 5G NR as suitable for sensing, such as reference signals (e.g., DL / UL DM-RS, UL SRS, DL CSI-RS), synchronization signals (e.g., DL SSB), and payload signals (e.g., DL PDSCH and UL PUSCH).

[0008] The techniques described in the aforementioned documents do not address selecting a subset of nodes for a given sensing task and do not recognize that using all available nodes for a given sensing task may not be ideal. Even when simultaneously using the same signals for communication and sensing, each receiving node may experience degradation in communication performance; while the receiving node is receiving wireless signals for sensing, the receiving node cannot receive or transmit communication signals intended for the receiving node. Furthermore, because the receiving node will typically transmit sensing reports wirelessly, the receiving node must use additional time-frequency resources, which may degrade not only its own communication performance but also that of other nodes. These degradations in communication performance often reduce the efficiency of a joint communication and sensing system. Summary of the Invention [Problem to be solved by the invention]

[0009] It is a primary object of the present invention to provide a system capable of efficiently meeting the requirements of both communication and sensing tasks in a joint communication and sensing system. It is a second object of the present invention to provide a method that can be used to efficiently meet the requirements of both communication and sensing tasks in a joint communication and sensing system. [Means for solving the problem]

[0010] In a first aspect of the present invention, a system for enabling detection of one or more objects includes at least one processor configured to: obtain detection requirements for detecting the one or more objects; obtain communication requirements; obtain information for each of a set of nodes; select a set of nodes from the set of nodes based on the detection requirements, the communication requirements, and the information for each of the set of nodes; and instruct one or more nodes of the set of nodes to participate in detecting the one or more objects, wherein at least one node of the set of nodes transmits a wireless signal and at least one node of the set of nodes receives the wireless signal.

[0011] The at least one processor may be configured to obtain characteristics of the received wireless signal, where the received wireless signal includes a received version of the transmitted wireless signal and where the received wireless signal reflects an impact of one or more objects on the transmitted wireless signal, and to determine, or enable another system to determine, one or more physical properties for each of the one or more objects based on the characteristics of the received wireless signal.

[0012] To efficiently satisfy the requirements of both communication and sensing tasks, the system can select a (suitable) subset of the set of nodes to perform a given sensing task. By selecting a set of nodes (e.g., BSs and UEs) based on sensing requirements, communication requirements, and information about each of the set of nodes, nodes can be selected such that time-frequency resources and / or transmit power, and optionally node (e.g., computational) resources, are used efficiently while satisfying the requirements of both communication and sensing tasks, e.g., the ongoing communication / sensing task and one or more newly given sensing tasks. Because there is an inherent trade-off between sensing and communication utilizing the same resources, it is beneficial to take this trade-off into account and, for example, select nodes whose participation in the sensing task should substantially benefit sensing performance without incurring too high a cost in terms of communication performance. Operators of mobile communication networks can define in operator policies how this trade-off should be implemented.

[0013] At a particular moment, it may be sufficient to select a set of nodes based only on the sensing requirements and information about each of the set of nodes, and not based on communication requirements, for example when there is no communication task.

[0014] The detection requirements may specify, for example, one or more target areas, one or more target directions, one or more target object types, one or more target objects (e.g., one or more object identifiers), target object velocity, target object size, and detection performance requirements. The detection performance requirements may specify, for example, requirements for detection accuracy, detection urgency, and / or detection reliability. The detection accuracy requirements may include, for example, target range resolution. The detection reliability requirements may include, for example, a minimum probability of detection and a limit on the false alarm rate.

[0015] Transmissions can use dedicated sensing signals, waveforms designed for both communication and sensing, or waveforms designed only for communication and not sensing. The latter has the advantage that the transmitted communication signal in any manner can be utilized for an additional purpose, i.e., for the sensing task. On the other hand, when dedicated sensing signals are emitted specifically for a given sensing task, resources are specifically consumed by the sensing task and may therefore be unavailable for performing communication tasks by one or more nodes. It is beneficial to take this into consideration when selecting a subset of nodes. In this way, the impact of the use of dedicated sensing signals on other nodes can be reduced.

[0016] The node may be, for example, a UE or a BS. The wireless signal may be received by a node different from the node that transmitted the wireless signal. A single node may be both the transmitting node and the receiving node. The physical properties of the one or more objects that are the target of the sensing task may include, for example, one or more of shape, size, speed, distance, location, orientation, material type, color, temperature, heartbeat, pitch, yaw, and roll. The system may be, for example, a BS, a UE, or another system in a wireless access network.

[0017] The information about each of the set of nodes may indicate one or more of node location, cell-specific antenna configuration, cell-specific carrier frequency, cell load, current set of actively transmitted reference signals, maximum transmit power, receiver characteristics, and supported frequency bands. This information may include node characteristics and characteristics of paths between the nodes. The latter may include, for example, average channel gain on the wireless link between the transmitting node and the receiving node. The average channel gain and cell load may be used to estimate whether communication performance requirements can be met. The foregoing is a non-exhaustive list of examples that may be used to determine communication and / or sensing performance in the process of selecting a set of nodes.

[0018] The at least one processor may be configured to assign each respective node of the set of nodes to a first set of transmitting nodes and / or a second set of receiving nodes, wherein the first set of transmitting nodes transmits wireless signals and the second set of receiving nodes receives the wireless signals.

[0019] In certain situations, it may not be necessary to assign a role to each selected node, for example, because all UEs are only receiving nodes and all BSs are only transmitting nodes, or because all nodes are both receiving and transmitting nodes. Nevertheless, it may be possible to achieve better efficiency or better communication (and / or sensing) performance by assigning a role to each selected node. For example, using a specific BS as a transmitting node and a specific UE as a receiving node may result in better efficiency or performance than using a specific BS as a receiving node and a specific UE as a transmitting node. Role assignment may be performed simultaneously with node selection.

[0020] The at least one processor may be configured to instruct a second set of receiving nodes to receive wireless signals for the (sole or additional) purpose of detecting one or more objects. If roles are assigned by the system and only unconditioned wireless communication signals are transmitted, it may be sufficient for the system to instruct the receiving nodes. Alternatively, roles may not be assigned by the system. In this case, node roles may be configured at the nodes; for example, a BS may only be able to function as a transmitting node, a UE may only be able to function as a receiving node, or each node may be both a transmitting node and a receiving node (bistatic).

[0021] The at least one processor may be configured to instruct the first set of transmitting nodes to transmit wireless signals for the sole or additional purpose of detecting one or more objects. This may be beneficial, for example, when the wireless signals include wireless communication signals adjusted for detecting one or more objects and / or dedicated detection signals. The wireless communication signals may be adjusted by adjusting beam characteristics of the wireless communication signals or by adjusting scheduled frequency and time resources of the wireless communication signals compared to wireless communication signals transmitted solely for communication purposes. For example, a repetition interval of the reference signal may be adjusted. If only unadjusted wireless communication signals are transmitted, it may not be necessary to instruct the transmitting nodes.

[0022] The at least one processor may be configured to: form a plurality of candidate node combinations from a set of nodes, each of the plurality of node combinations including a first subset and a second subset of the set of nodes, the first subset being assigned a role of transmitting wireless signals and the second subset being assigned a role of receiving wireless signals; determine, for each of the plurality of node combinations, at least one communication performance for at least one communication task and at least one sensing performance for at least one sensing task based on information about each of the set of nodes; determine, for each of the plurality of node combinations, whether communication requirements and sensing requirements can be met based on the at least one communication performance and the at least one sensing performance; select node combinations from the plurality of node combinations as a set of nodes based on one or more of the at least one communication performance and the at least one sensing performance and based on whether the communication requirements and sensing requirements can be met; and assign the first subset of the selected node combinations to a first set and the second subset of the selected node combinations to a second set.

[0023] This allows for proper consideration of the inherent trade-off between sensing and communication, typically in accordance with the network operator's policies: any induced resource cost (e.g., code, power, time, frequency) may cause a loss of communication performance due to reduced availability of said resources for handling communication tasks.

[0024] At a particular moment, for example, when there is no communication task, it may be sufficient to determine only the sensing performance for the sensing task and not the communication performance for the communication task. In this situation, the processor may determine, for each of the plurality of node combinations, whether the sensing requirement can be met based on at least one sensing performance, and may select a node combination from the plurality of node combinations as a set of nodes based on the at least one sensing performance and whether the sensing requirement can be met.

[0025] Typically, node selection is performed upon the arrival of a new sensing request based on the requirements of this new task and any existing tasks, which may be (i) none, (ii) only communication tasks, (iii) only other sensing tasks, or (iv) a mix of communication tasks and other sensing tasks.

[0026] The at least one processor may be configured to determine the detection performance by determining, for each node combination among the plurality of node combinations and for each detection task among the at least one detection task, a detection probability based on roles assigned to the nodes in the node combination. For example, a node combination with at least a minimum required detection probability that meets communication requirements and incurs the lowest processing cost may be selected. Alternatively, for example, a node combination with the highest detection probability that meets communication requirements and optionally incurs up to the highest processing cost may be selected.

[0027] The at least one processor may be configured to, for each node combination among the plurality of node combinations, determine a processing cost for each node combination in the second subset based on the information about each node in the set of nodes, and select the node combination as the set of nodes further based on the processing cost. The processing cost may be determined based on, for example, one or more of whether the node is a BS or a UE, whether the node is active or inactive, the processing load of the node, the sensing capability of the node, and the battery level of the node. Typically, each receiving node involved in sensing faces a processing cost, which is an additional reason why using all available nodes for a given sensing task may not be ideal.

[0028] The at least one processor may be configured to select a plurality of candidate nodes from the set of nodes based on information about each of the set of nodes, and to select a set of nodes from the plurality of candidate nodes based on the sensing requirements, the communication requirements, and the information. If selecting a set of nodes from the plurality of candidate nodes based on the sensing requirements, the communication requirements, and the information involves complex calculations, for example, as part of an optimization algorithm whose complexity increases with the number of nodes considered, it may be beneficial to pre-filter the set of nodes and perform the complex calculations only on a more limited number of candidate nodes.

[0029] For example, the information about each of the set of nodes may indicate the willingness and / or ability of each node to participate in detecting one or more objects and / or indicate the proximity of each node to an area of ​​interest, where the area of ​​interest is specified in the detection requirements, and the at least one processor may be configured to select multiple candidate nodes based on the willingness and / or ability of the nodes to participate in detecting and / or based on the nodes' proximity to the area of ​​interest. In the latter case, a node may only be included as a candidate node if, for example, the node's coverage area (transmission and / or reception) has or is estimated to have at least a certain amount of overlap with the area of ​​interest.

[0030] In a second aspect of the present invention, a node for participating in the detection of one or more objects may include at least one processor configured to receive instructions to participate in detecting one or more objects from a system for enabling detection of one or more objects, and based on the instructions, transmit and / or receive wireless signals for detecting the one or more objects, wherein the received wireless signals include received versions of the transmitted wireless signals and the received wireless signals reflect the impact of the one or more objects on the transmitted wireless signals.

[0031] The instructions may specify whether the node should transmit, receive, or transmit and receive wireless signals to detect one or more objects, and at least one processor of the node may be configured to transmit, receive, or transmit and receive wireless signals in accordance with the instructions.

[0032] In a third aspect of the present invention, a method for enabling detection of one or more objects includes obtaining detection requirements for detecting one or more objects, obtaining communication requirements, obtaining information about each of a set of nodes, selecting a set of nodes from the set of nodes based on the detection requirements, the communication requirements, and the information about each of the set of nodes, and instructing one or more nodes of the set of nodes to participate in detecting the one or more objects, wherein at least one node of the set of nodes transmits a wireless signal and at least one node of the set of nodes receives the wireless signal. The method may be implemented by software running on a programmable device. The software may be provided as a computer program product.

[0033] In a fourth aspect of the present invention, a method for engaging in detection of one or more objects includes receiving instructions to engage in detecting one or more objects from a system for enabling detection of one or more objects, and transmitting and / or receiving, based on the instructions, wireless signals for detecting the one or more objects, the received wireless signals including received versions of the transmitted wireless signals and reflecting impacts of the one or more objects on the transmitted wireless signals. The method may be implemented by software running on a programmable device. The software may be provided as a computer program product.

[0034] Additionally, there is provided a computer program for performing the methods described herein, and a non-transitory computer-readable storage medium storing the computer program, which may, for example, be downloaded by or uploaded to existing devices or stored during manufacture of these systems.

[0035] The non-transitory computer-readable storage medium stores at least a first software code portion, the first software code portion being configured, when executed or processed by a computer, to perform executable operations to enable detection of one or more objects.

[0036] The executable operations include obtaining detection requirements for detecting one or more objects; obtaining communication requirements; obtaining information about each of a set of nodes; selecting a set of nodes from the set of nodes based on the detection requirements, the communication requirements, and the information about each of the set of nodes; and instructing one or more nodes of the set of nodes to participate in detecting the one or more objects, wherein at least one node of the set of nodes transmits a wireless signal and at least one node of the set of nodes receives the wireless signal.

[0037] The non-transitory computer-readable storage medium stores at least a second software code portion, the second software code portion being configured, when executed or processed by a computer, to perform executable operations for participating in the detection of one or more objects.

[0038] The executable operations include receiving instructions to engage in detecting one or more objects from a system for enabling detection of the one or more objects, and transmitting and / or receiving, based on the instructions, wireless signals to detect the one or more objects, where the received wireless signals include received versions of the transmitted wireless signals and reflect the impact of the one or more objects on the transmitted wireless signals. The method may be implemented by software running on a programmable device. The software may be provided as a computer program product.

[0039] As will be appreciated by those skilled in the art, aspects of the present invention may be embodied as a device, a method, or a computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, microcode, etc.), or an embodiment combining software and hardware aspects, all of which may be generally referred to herein as a "circuit," "module," or "system." Functions described in this disclosure may be implemented as an algorithm executed by a computer processor / microprocessor. Furthermore, aspects of the present invention may take the form of a computer program product embodied in, e.g., stored on, one or more computer-readable medium(s) having computer-readable program code embodied therein.

[0040] Any combination of one or more computer-readable media may be utilized. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of the present invention, a computer-readable storage medium may be any tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0041] A computer-readable signal medium may include a propagated data signal in which computer-readable program code is embodied, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electromagnetic, optical, or any suitable combination thereof. A computer-readable signal medium is not a computer-readable storage medium but may be any computer-readable medium capable of communicating, propagating, or transporting a program for use by or in connection with an instruction execution system, apparatus, or device.

[0042] Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including, but not limited to, wireless, wireline, fiber optic, cable, RF, etc., or any suitable combination of the foregoing. Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java™, Smalltalk, C++, or the like, and conventional procedural programming languages ​​such as the “C” programming language or similar programming languages. The program code may execute entirely on the user's computer, partially on the user's computer as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be to an external computer (e.g., through the Internet using an Internet Service Provider).

[0043] Aspects of the present invention are described below with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor, particularly a microprocessor or central processing unit (CPU), of a general-purpose computer, special-purpose computer, or other programmable data processing device to produce a machine, such that the instructions, executing via a processor of the computer, other programmable data processing device, or other device, create means for performing the functions / acts specified in one or more blocks of the flowchart illustrations and / or block diagrams.

[0044] These computer program instructions may also be stored on a computer-readable medium, and the instructions stored on the computer-readable medium may direct a computer, other programmable data processing apparatus, or other device to function in a particular manner to produce an article of manufacture including instructions that perform the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams.

[0045] Computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device such that a series of operational steps are performed on the computer, other programmable apparatus, or other device to produce a computer-executed process, such that the instructions, executing on the computer or other programmable apparatus, provide a process for performing the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams.

[0046] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of devices, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowcharts or block diagrams may represent a module, segment, or portion of code comprising one or more executable instructions for performing the specified logical function(s).

[0047] It should also be noted that in some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may in fact be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending on the functionality involved. It should also be noted that each block of the block diagrams and / or flowchart illustrations, and combinations of blocks in the block diagrams and / or flowchart illustrations, can be implemented by a special-purpose hardware-based system that performs the specified functions or acts, or a combination of special-purpose hardware and computer instructions.

[0048] These and other aspects of the invention will be apparent from and further explained by way of example with reference to the drawings in which: [Brief explanation of the drawings]

[0049] [Figure 1] 1 is a flow diagram of a first embodiment of a method for enabling detection of one or more objects. [Figure 2] 1 is a flow diagram of an embodiment of a method involving detecting one or more objects. [Figure 3] 4 is a flow diagram of a second embodiment of a method for enabling detection of one or more objects. [Figure 4] 10 is a flow diagram of a third embodiment of a method for enabling detection of one or more objects. [Figure 5] 5 is an exemplary diagram of the selection of candidate nodes according to the method of FIG. 4. [Figure 6]10 is a flow chart of a fifth embodiment of the method. [Figure 7] 7 is an illustrative diagram of the determination of the probability of detection in a first implementation of the method of FIG. 6; [Figure 8] 7 is an illustrative diagram of the determination of the probability of detection in a second implementation of the method of FIG. 6. [Figure 9] FIG. 1 is a block diagram of a first embodiment of a system. [Figure 10] FIG. 2 is a block diagram of a second embodiment of the system. [Figure 11] 1 is a block diagram of an exemplary data processing system for implementing the methods of the present invention; DETAILED DESCRIPTION OF THE INVENTION

[0050] Corresponding elements in the drawings are designated by the same reference numerals. A first embodiment of a method for enabling detection of one or more objects is shown in FIG. 1. In this embodiment, the steps of the method are performed by a single system. Step 101 includes obtaining detection requirements for detecting one or more objects. The detection requirements typically relate to any ongoing detection task and, if applicable, to newly requested detection tasks. The detection requirements may specify, for example, one or more target areas, one or more target directions, one or more target object types, one or more target objects (e.g., one or more object identifiers), target object velocity, target object size, and one or more detection performance requirements. The detection performance requirements may specify, for example, requirements for detection accuracy, detection urgency, and / or detection reliability. The detection accuracy requirements may include, for example, target range resolution. The detection reliability requirements may include, for example, a minimum probability of detection and a limit on the false alarm rate.

[0051] In one implementation, the sensing requirements include a task description and performance requirements. The task description includes "where" (e.g., in a well-defined area around Amsterdam), "when" (e.g., between 2:00 PM and 4:00 PM today), and "what" (e.g., in H MIN <H<HMAX , B MIN <B < B MAX , L MIN <L < L MAX In the case of [H (height), B (width), L (length)] of the measured values of the flying drone / device), it may be possible to instruct. The detection performance requirements can define, for example, detection of the target object within x seconds of entering the area or within x seconds of starting the detection task, successful detection probability > y, and / or false alarm rate < z. The specific values of these parameters (regarding the task description and performance requirements) can be provided by an external application.

[0052] The detection requirements can be, for example, related to the monitoring mode or the tracking mode. In the monitoring mode, the detection purpose is to detect the presence of the target object, typically including one or more of the aforementioned object attributes, such as the location of the object. Possible detection requirements include the detection range, detection accuracy, and detection speed (required time), and each such requirement is potentially imposed on any target attribute of the object.

[0053] In the tracking mode, the detection purpose is to track the trajectory of the detected target object, typically requiring estimation of the object's speed, change in the object's speed, and the direction of movement of the object. Possible detection requirements include the maximum detectable speed, speed detection, and granularity of the direction of movement, and each such requirement is potentially imposed on any target attribute of the object or the object's trajectory.

[0054] Both the monitoring mode and the tracking mode can be enhanced by further determining the shape and orientation of the target object to be detected / tracked. Possible detection requirements here are the accuracy of orientation and the accuracy of shape.

[0055] Step 103 involves obtaining communication requirements, e.g., requirements regarding throughput, latency, and / or reliability levels. The communication requirements typically relate to any ongoing communication tasks and, if applicable, newly requested communication tasks. Step 105 involves obtaining information about each of the set of nodes. The information may include static and / or dynamic parameters. Two non-exhaustive lists of selected examples are provided below. Static parameters: ● BS / cell location ● Cell-specific direction angle / tilt / antenna configuration / maximum transmission power ● BS detection (tx / rx) capability ● Carrier frequency and bandwidth allocated to the cell ● Cell receiver sensitivity / noise level / other characteristics Dynamic parameters: ● Current cell transmission / processing load and associated service requirements for communication / sensing tasks. ● The current set of actively transmitted CSI-RS per cell The set of currently existing UEs and their characteristics (all UE-specific parameters are considered dynamic, since the existence of the UEs themselves is dynamic), e.g. - UE Location - current UE transmission / processing load of communication / sensing tasks and associated service requirements; - UE detection (tx / rx) capability - frequency bands supported by the UE - UE receiver sensitivity / noise level / other characteristics - Active / inactive mode (UE) - UE battery level ● Battery power cell battery level Steps 101, 103, and 105 may be performed in an information collection phase, in which other information, such as (regular) CSI feedback of the UE, may also be collected.

[0056] Step 107 includes selecting a set of nodes from the set of nodes based on the sensing requirements obtained in step 101, the communication requirements obtained in step 103, and information about each of the set of nodes obtained in step 105. If the node selected in step 107 is a base station and this base station provides coverage to multiple cells, one of these multiple cells may be further selected in step 107.

[0057] Typically, node selection is performed upon the arrival of a new sensing request based on the requirements of this new task and any existing tasks. The existing tasks may be (i) none, (ii) only communication tasks, (iii) only other sensing tasks, or (iv) a mixture of communication tasks and other sensing tasks. If there are no communication tasks at a particular moment, step 103 may be skipped for this moment, and a node may then be selected based on the sensing requirements obtained in step 101 and the information about each of the set of nodes obtained in step 105, as well as based on no communication requirements.

[0058] Step 109 includes instructing one or more nodes of the set of nodes to participate in detecting one or more objects, where at least one node of the set of nodes will transmit a wireless signal and at least one node of the set of nodes will receive the wireless signal.

[0059] Optionally, the method further includes steps 111 and 113. Step 111 includes scheduling frequency and time resources for transmission of wireless signals and / or determining beam characteristics of beams for transmission of wireless signals based on the detection requirements obtained in step 101 and the communication requirements obtained in step 103. The wireless signals may include, for example, communication payload data. Step 111 may include, for example, determining beam widths and / or beam directions and / or transmission powers of one or more beams based on the detection requirements obtained in step 101 and the communication requirements obtained in step 103.

[0060] Step 113 includes, for example, transmitting a wireless signal on the scheduled frequency and time resources scheduled in step 111 and / or via a beam having beam characteristics determined in step 111. As mentioned above, in general, the following options exist for the design of the wireless signal: 1. A dedicated sensing signal is used for sensing, possibly multiplexed with other sensing and / or communication signals in the time, frequency, code, and / or spatial domains. 2. The same (new) radio signal (waveform) is designed for both communication and sensing purposes, taking into account the communication and sensing requirements together. 3. Traditional communication radio signals, either transmitted for a specific communication task or transmitted as, for example, reference / control signals to support the communication task, are additionally utilized, possibly in a modified form, for the sensing task.

[0061] In step 111, a selection is made among available signal options, such as using an available communication signal and optionally using a dedicated sensing signal. Optionally, steps 115 and 117 are performed after step 113, or after step 109 if steps 111 and 113 are omitted. Step 115 includes obtaining characteristics of the received wireless signal that include a received version of the transmitted wireless signal and that reflect the impact of one or more objects on the transmitted wireless signal. Characteristics of the received wireless signal that do not include a received version of the transmitted wireless signal or that do not reflect the impact of one or more objects on the transmitted wireless signal need not be obtained in step 115.

[0062] Step 117 includes determining, or enabling another system to determine, one or more physical properties for each of the one or more objects based on characteristics of the received wireless signals as obtained in step 115. The other system may be enabled to determine the one or more physical properties by transmitting sensing data including the characteristics of the received signals obtained in step 115 to the other system in step 117. The physical properties of the one or more objects may include, for example, one or more of shape, size, speed, distance, location, orientation, material type, color, temperature, heart rate, pitch, yaw, and roll. If steps 115 and 117 are omitted, these steps may be performed by a further system, for example, a sensing application function (described with respect to FIG. 10). Additionally, one or more steps of one or more of the embodiments of FIGS. 3, 4, and 6 may be added to the embodiment of FIG. 1.

[0063] An embodiment of a method involved in detecting one or more objects is shown in Figure 2. In this embodiment, the steps of the method are performed by a single node. Step 121 includes receiving an instruction to participate in detecting one or more objects from a system for enabling detection of one or more objects. This system may, for example, be a system implementing the method of Figure 1.

[0064] The instructions may specify whether the node should transmit, receive, or transmit and receive wireless signals to detect one or more objects. If the node is configured to always transmit, receive, or transmit and receive wireless signals to detect one or more objects, the instructions need not specify this.

[0065] Step 123 includes transmitting and / or receiving wireless signals to detect one or more objects based on the instructions received in step 121. The wireless signals received in step 123 include received versions of the transmitted wireless signals that reflect the impact of one or more objects on the transmitted wireless signals. Other wireless signals may be received in other steps (not shown in FIG. 2).

[0066] If step 123 includes receiving wireless signals for detecting one or more objects, optional step 125 may be performed. Step 125 includes determining, or enabling the system or another system to determine, one or more physical properties for each of the one or more objects based on characteristics of the wireless signals received in step 123. The system or another system may be enabled to determine the one or more physical properties by transmitting sensing data including characteristics of the signals received in step 123 to the (other) system in step 125.

[0067] A second embodiment of a method for enabling detection of one or more objects is shown in Figure 3. The second embodiment of Figure 3 is an extension of the first embodiment of Figure 1. In the embodiment of Figure 3, step 141 is performed between step 107 and step 109 of Figure 1, and step 109 of Figure 1 is performed by step 143.

[0068] Step 141 includes assigning each respective node of the set of nodes selected in step 107 to a first set of transmitting nodes and / or a second set of receiving nodes. The first set of transmitting nodes will transmit wireless signals and the second set of receiving nodes will receive the wireless signals. Step 143 includes instructing the second set of receiving nodes as identified in step 141 to receive wireless signals to detect one or more objects.

[0069] Optionally, step 143 includes instructing the first set of transmitting nodes as identified in step 141 to transmit wireless signals for the sole or additional purpose of detecting one or more objects. The latter is beneficial, for example, when the wireless signals include wireless communication signals conditioned for detecting one or more objects (e.g., in optional steps 111 and 113 as described with respect to FIG. 1) and / or dedicated detection signals. Additionally, one or more steps of one or more of the embodiments of FIGS. 4 and 6 may be added to the embodiment of FIG. 3.

[0070] A third embodiment of a method for enabling detection of one or more objects is shown in Figure 4. The third embodiment of Figure 4 is an extension of the first embodiment of Figure 1. In the embodiment of Figure 4, step 151 is performed after step 105 of Figure 1 is performed and before step 107 of Figure 1 is performed, and step 107 of Figure 1 is performed by step 153.

[0071] Step 151 includes selecting a plurality of candidate nodes from the set of nodes based on information about each of the set of nodes as obtained in step 105. Step 153 includes selecting a set of nodes from the plurality of candidate nodes selected in step 151 based on the sensing requirements obtained in step 101, the communication requirements obtained in step 103, and the information obtained in step 105.

[0072] In step 151, a candidate set (final candidate list) of nodes (BSs and / or UEs) is derived based on, for example, network planning data. This reduces the complexity of the optimization problem typically solved in step 153. The more extensive the list of candidate nodes, the more difficult the optimization (selection) problem in step 153, but it also potentially leads to better final node selection and therefore higher detection accuracy (e.g., less ambiguity) and / or lower resource costs. Therefore, it is better for the candidate set of nodes to be too large than too small.

[0073] The information obtained in step 105 may, for example, indicate the willingness and / or ability of each node to participate in the detection of one or more objects and / or indicate the proximity of each node to the area of ​​interest specified in the detection requirements. For example, the information obtained in step 105 may specify the detection (transmission / reception) capabilities of the BSs and UEs from which this capability can be determined and / or the BS / cell and / or UE location from which this proximity can be determined. Taking detection capabilities into account in step 151 allows incapable nodes to be immediately eliminated.

[0074] Step 151 may then include selecting multiple candidate nodes based on the willingness and / or ability of the nodes to participate in sensing and / or based on the proximity of the nodes to the area of ​​interest. If a base station is selected in step 151, one or more associated cells may also be selected in step 151. For example, one cell of the base station may be sufficiently close to the area of ​​interest, while another cell of the base station may not be sufficiently close to the area of ​​interest.

[0075] In a relatively simple implementation of step 151, candidate nodes are selected based solely on the candidate nodes' locations relative to the target area and, optionally, their sensing capabilities. The example of FIG. 5 shows five base stations 11-15, their respective coverage areas 51-55, three active UEs 31-33, four inactive UEs 71-74, and a target sensing area 59. In the example of FIG. 5, each base station provides coverage for a single cell. In this example, base station 13 provides little coverage in target sensing area 59, so base stations 11, 12, 14, and 15 are selected as candidates.

[0076] 5, all UEs (active or inactive) within target detection area 59, i.e., UEs 31, 32, 72, and 74, are labeled as candidates. Additionally, UEs outside the boundary of target detection area 59 but nearby may also be considered candidates, for example, only if they would be needed to contribute to fully covering target detection area 59. For example, UE 71 may additionally be selected as a candidate node. UE 33 may be considered not needed to contribute to fully covering target detection area 59 and therefore may be omitted from candidate selection. UE 73 may be considered not close to target detection area 59 and therefore may be omitted from candidate selection. The locations of active UEs may be known or estimated based on recent data, while the locations of inactive UEs may be estimated based on historical data (e.g., stationary or relatively slow-moving UEs).

[0077] Dedicated sensing signals may impact communication performance and may consume additional resources. Where supported, it may be beneficial to avoid the use of dedicated sensing signals where possible. Instead, wireless signals with communication payload and / or communication reference signals may be used simultaneously for communication and sensing. In this case, the probability of detecting an object of interest in a target sensing area 59 depends at least on the location of the node and, optionally, the overlap between the coverage areas of the payload and reference signals and the target area 59.

[0078] The coverage areas 66-68 of three cell-specific SSB signals and the coverage areas 61-63 of three CSI-RS signals received by UEs 31-33 are shown in FIG. 5, respectively. Not all SSB beams in the SSB beam grid are necessarily considered for use in detection. This may depend on the beam-specific overlap of the SSB beams with the target detection area 59. In the example of FIG. 5, the SSB corresponding to coverage area 66 from base station 11 may be excluded.

[0079] In a more advanced implementation of step 151, the degree of coverage overlap of the reference signals with the target detection area 59 is taken into account when selecting candidates. In addition to the degree of overlap between the target detection area 59 and the coverage area of ​​the SSB and CSI-RS signals transmitted by the base station, the degree of overlap between the target detection area 59 and the coverage area of ​​the SRS signals transmitted by the UE may be taken into account. These coverage areas may be approximated by a circle of some radius around the UE location (not visualized in FIG. 5). Additionally, one or more steps of one or more of the embodiments of FIGS. 3 and 6 may be added to the embodiment of FIG. 4.

[0080] In the embodiment of Figure 4, static and dynamic parameters are obtained for all nodes in the set of nodes in step 105 before candidate nodes are selected in step 151. In an alternative embodiment, all parameters needed to perform step 151 are obtained for all nodes in the set of nodes in step 105, and all additional parameters needed to perform step 153 are obtained only for the candidate nodes in an additional step performed between steps 151 and 153.

[0081] A fourth embodiment of a method for enabling detection of one or more objects is shown in Figure 6. The fourth embodiment of Figure 6 is an extension of the first embodiment of Figure 1. In the embodiment of Figure 6, step 107 of Figure 1 is performed by steps 171, 173, 175, and 177, and, as in the embodiment of Figure 3, step 141 is performed between step 107 and step 109, and in the embodiment of Figure 6 is performed by step 179.

[0082] Step 171 includes forming a plurality of candidate node combinations from the set of nodes. Each of the plurality of node combinations includes a first subset and a second subset of the set of nodes. The first subset is assigned the role of transmitting wireless signals, and the second subset is assigned the role of receiving wireless signals. When the embodiment of Figure 6 is combined with the embodiment of Figure 4, the candidate node combinations include only the candidate nodes selected in step 151 of Figure 4.

[0083] First, a set of transmitters, denoted M, and a set of receivers, denoted N, may be determined based on the sensing capabilities of the node. These sensing capabilities may exclude certain roles for the node; for example, a particular node may only be capable of functioning as a receiver. Since the selected carrier frequency must be supported by both transmitters and receivers, the carrier frequencies assigned to the cell and the frequency bands supported by the UE may be considered in step 171; it is not possible for a UE to be assigned a transmit or receive role on a carrier in an unsupported frequency band.

[0084] In step 171, the node combinations are divided into a possible subset M s ⊆M and every possible subset N s ⊆N. For example, there may be multiple node combinations with the same node when different configurations are evaluated for one or more of the nodes. As a first example, a first cell of a base station may be considered for a first node combination, and a second cell of the base station may be considered for a second node combination. As a second example, a base station may transmit a dedicated sensing signal for a first node combination but not for a second node combination.

[0085] Step 173 includes determining, for each of the plurality of node combinations, at least one communication performance for at least one communication task and at least one sensing performance for at least one sensing task based on the information about each of the node sets obtained in step 105. The communication and sensing performance may be determined, for example, for all ongoing tasks and for any new tasks. Steps 101-109 may be repeated, for example, each time a new task is added and, optionally, each time a task is removed.

[0086] If there are no communication tasks at a particular moment, performing step 173 at this moment may include determining, for each of the combinations of multiple nodes, at least one sensing performance for at least one sensing task based on the information about each of the sets of nodes obtained in step 105, without determining any communication performance.

[0087] The detection performance may be determined in step 173 by determining, for each node combination among the plurality of node combinations, for each detection task among the at least one detection task, a detection probability based on the role assigned to the node in the node combination. The detection performance may be equal to the detection probability or may be a metric that integrates the detection probability under some conditions, for example, false alarm rate, detection accuracy, and / or detection time.

[0088] To determine the detection probability, the BS / cell and UE locations relative to the potential location of the detected object may be taken into account, since they affect the propagation loss, S(I)NR estimate, and therefore the detection probability. To determine the detection probability, the cell-specific direction angle / tilt / antenna aspect / maximum transmit power and the carrier frequency assigned to the cell may be taken into account, since these parameters affect the propagation loss, S(I)NR estimate, and therefore the detection probability. To determine the detection probability, the cell / UE receiver sensitivity / noise amount / other characteristics may be taken into account, since these parameters affect the S(I)NR estimate and therefore the detection probability.

[0089] The detection probability may be calculated by first applying radar equations at the pixel (portion of the target detection area) level and then integrating these over the entire target detection area. An example of how the detection probability may be calculated is given below. To estimate the detection probability, the target detection area is divided into a set of non-overlapping pixels in two- or three-dimensional space, depending on the dimensionality of the target detection area, as shown in FIG. 7.

[0090] 7 shows a 3D pixel 81 at a particular location within the target detection area in addition to base stations 11-12 and 14-15 and UEs 31-33 and 72 of FIG. 5. The detection probability for each node combination can first be estimated for each pixel of the target detection area as follows:

[0091] i.N s All receivers from the target 3D pixel (R R,j ) to calculate / estimate the distance between ii. M s All transmitters from 3D Pixel (R T,i ) to calculate / estimate the distance between

[0092] iii. Calculate / estimate the received signal power for all pairs.

[0093]

number

[0094] [Table 1] iv. The combined SNR, given the total number of receivers and transmitters in a given set, further depends on whether the signals are combined (a) coherently or (b) non-coherently.

[0095] ■ Assuming a perfectly synchronized system operating coherently, the combined SNR (for a particular pixel and a given set of transmitters and receivers) is

[0096]

number

[0097] Alternatively, combining the signals non-coherently would result in a somewhat lower overall SNR (for a given set of particular pixels and transmitters and receivers), which

[0098]

number

[0099] [Table 2] v. Convert the total SNR to a probability of detection (using a probability of detection vs. SNR chart).

[0100] In the above calculations (of detection probability), it was assumed to have signals (e.g., IQ samples, plot-level information) from all receivers available at the sensing fusion center for aggregation. There are different schemes for calculating detection probability that may be appropriate in some scenarios, such as when there are not signals (IQ samples) from all receivers at the fusion center and the receivers can process the detection information locally. For example, by assuming that the receivers independently determine their receiver-specific detection probabilities, it is possible to calculate P using the steps above. detection,j can be calculated. Nevertheless, in this case, appropriate adjustments of the equations in steps (iii) and (iv-a) must be made, i.e., S i,j →S i ,σ i,j →σ i ,

[0101]

number

[0102] The central wavelength, transmit power of the i-th transmitter, antenna gain, form factor, losses, distance, equivalent system temperature, and (noise) bandwidth at the j-th receiver used in the above calculations can be determined from the information obtained in step 105. Typically, the receiver manufacturer specifies the system noise temperature (or equivalent noise quantity / factor, which can be converted to noise temperature as Fs=1+Ts / 290). The (bistatic) RCS of a given pair (i, j) can be determined from the detection requirements obtained in step 101. For example, the detection requirements may indicate the average / minimum / range of RCS values ​​for a given detection task. Tables exist in the literature with average RCS values ​​for specific objects, such as humans and airplanes.

[0103] The received signal power is calculated / estimated in step iii) for each transmitter and receiver pair under the assumption that specific beams are transmitted. These beams may include beams for transmitting wireless signals with communication payloads, beams for transmitting reference signals (e.g., SSB, CSI-RS, and / or SRS), and / or beams for transmitting dedicated sensing signals. Antenna gain and / or loss may be determined based on the beam characteristics of these beams. Even if the transmitter transmits dedicated sensing signals, the antenna gain and loss will typically vary among pixels in the target sensing area.

[0104] 8 shows a 3D pixel 81 at a particular location in target detection area 59, in addition to base stations 11, 14, and 15 and UEs 31-33 and 74 of FIG. 5. FIG. 8 further shows coverage areas 66-68 of the three cell-specific SSB signals of FIG. 5 and coverage areas 61-63 of the three CSI-RS signals of FIG. 5. If base station 11 is selected as the detection transmitter and UE 31 is selected as the detection receiver, the detection probability of 3D pixel 81 may be calculated at the moment base station 11 transmits a wireless signal with a communication payload, a CSI-RS signal with coverage area 61, or an SSB signal with coverage area 67.

[0105] Once the pixel-specific detection probabilities have been estimated, the overall probability of detection for the entire target detection area is then determined, for example, by simple averaging of the pixel-specific detection probabilities. Alternatively, weighted averaging may be used, for example, if the target object is more likely to be present near the center of the target detection area and therefore a high detection probability in more central pixels is more important.

[0106] The overall detection probability for the entire target detection area is preferably estimated during a window of observation during which multiple attempts to detect the object may be made. The detection probability then increases with the number of attempts, as every additional attempt provides an additional chance for successful detection. n , the estimated probability on trial n is 1-(1-p1)*(1-p2)*…*(1-p N ) can be used as the estimated probability after N trials. If a receiver receives a first beam with first beam characteristics from a transmitter at a first instant, and a second beam with second beam characteristics from the transmitter at a second instant, the detection probabilities will likely be different.

[0107] The communication performance may be estimated, for example, based on the average channel gain on the wireless link between the transmitting node and the receiving node and based on the cell load. This communication performance may be degraded if a node is deprived of transmission opportunities due to being assigned the role of a sensing receiver, i.e., when the BS functions as a sensing receiver in a downlink slot or when the UE functions as a sensing receiver in an uplink slot. While the node is listening to wireless signals for sensing, the node cannot transmit wireless signals for communication.

[0108] Communication performance may be degraded based on the impact of a lost transmission opportunity. The impact of a lost transmission opportunity may depend, for example, on cell load, traffic priority, and / or latency tolerance. Communication performance may also be degraded when a node is instructed to transmit a dedicated sensing signal or a modified communication payload or reference signal for sensing.

[0109] When determining the impact of supporting a new sensing task on communication performance, the current set of actively transmitted CSI-RS per cell may be taken into consideration, for example, to determine whether currently inactive CSI-RS signals or dedicated sensing signals would be needed to cover a currently uncovered area of ​​the cell, and therefore whether additional transmission resources would be needed. When determining the impact of supporting a new sensing task on communication performance, the mode of the UE (active or inactive) may also be taken into consideration, since inactive UEs require additional signaling, and therefore transmission resources, to engage in sensing tasks.

[0110] Optionally, step 173 further includes, for each node combination of the plurality of node combinations, determining a processing cost for the first subset of each node combination based on the information obtained in step 105. These processing costs may be determined based on, for example, one or more of the following parameters:

[0111] ● BS and UE detection (tx / rx) capability ● Processing power of BS and UE ● Battery level and energy usage or efficiency of the UE and battery power cells ● Current UE / BS processing load for communication / sensing tasks - The current processing load may affect the amount of processing resources that a node can make available for requested sensing tasks.

[0112] Step 175 includes determining, for each of the plurality of node combinations, whether the communication requirements obtained in step 103 and the sensing requirements obtained in step 101 can be met based on the at least one communication performance and the at least one sensing performance determined in step 173. Thus, step 175 includes comparing the at least one communication performance with the communication requirements and the at least one sensing performance with the sensing requirements. Steps 175 and 177 may be combined.

[0113] If there is no communication task at a particular moment, performing step 175 at this moment may involve determining, for each of a plurality of node combinations, whether the sensing requirements obtained in step 101 can be met based on at least one sensing performance determined in step 173, without determining whether the communication requirements can be met.

[0114] Step 177 includes selecting a combination of nodes from the plurality of node combinations as a set of nodes based on one or more of the at least one communication performance and the at least one sensing performance determined in step 173, based on whether the communication requirements and sensing requirements as determined in step 175 can be met, and, if applicable, based on the processing cost determined in step 173.

[0115] If there is no communication task at a particular moment, performing step 177 at this moment may involve selecting a combination of nodes from the plurality of node combinations as the set of nodes based on at least one sensing performance determined in step 173, based on whether sensing requirements as determined in step 175 can be met, and, if applicable, based on processing costs determined in step 173, without selecting a combination of nodes based on any communication performance or whether any communication requirements can be met.

[0116] In step 177, the goal is to find the optimal set M according to applicable operator policies, which typically specify the optimization of detection and / or performance tasks under certain constraints. s,opt and N s,opt It may be to find.

[0117] The operator policy can take various forms. The estimated communication performance of communication task j is the QoS. C,j and the corresponding minimum requirement (or maximum acceptable level, if this is a "lower is better" KPI) is the QoS C,j * The estimated detection performance of detection task j is expressed as QoS S,j and the corresponding minimum requirement (or maximum acceptable level, if this is a "lower is better" KPI) is the QoS S,j * , the operator policy can be specified, for example, as follows:

[0118] ■ QoS for all other tasks (y,j) y,j * Consider the conditions for QoS y,j QoS for a single (communication or sensing) task (x, j), optionally imposing a constraint on the processing cost so that it does not exceed some maximum level. x,j Optimize.

[0119] ■ QoS for all (communication or sensing) tasks (x,j), optionally imposing a constraint on the processing cost so that it does not exceed some maximum level. x,j ≧αQoS x,j * Maximize α under the condition that

[0120] ■ QoS for all (communication or sensing) tasks (x, j) x,j * Consider the conditions for QoS x,j , and optionally constraining the processing cost so that it does not exceed some maximum level, i.e., β C,1 QoS C,1 +β C,2 QoS C,2 +…+β S,1 QoS S,1 +β S,2 QoS S,2 +..., to maximize.

[0121] For example, QoS C,j may be throughput, latency, reliability level, or some combination thereof, and QoS S,j may be the probability of detection, or a metric that integrates the probability of detection under some conditions on false alarm rate, detection accuracy, and / or detection time. Combinations of the above are also possible. The above formulas assume "higher is better" for each QoS metric. For "lower is better" QoS metrics, e.g., latency-based metrics, the formula should be modified appropriately, e.g., by replacing the QoS metric and the corresponding requirement with its inverse.

[0122] The above approach should yield a (near) optimal solution with respect to operator policy. If sensing and communication performance is determined under the assumption that only unadjusted existing communication signals are used and no feasible solution or a solution with excessive processing cost is found, additional action may need to be taken, such as utilizing dedicated sensing signals or reconfiguring / adjusting existing communication signals. Such action would potentially degrade communication performance.

[0123] Step 179 includes assigning a first subset of the node combinations selected in step 177, as formed in step 171, to a first set, and a second subset of the node combinations selected in step 177, as formed in step 171, to a second set. Step 109 includes instructing one or more nodes of the set of nodes to participate in detecting one or more objects. Additionally, one or more steps of one or more of the embodiments of Figures 3 and 4 may be added to the embodiment of Figure 6. Step 109 may, for example, be performed by step 143 of Figure 3.

[0124] 9 is a block diagram of a first embodiment of a communication network including a system 1 for enabling detection of one or more objects, and base stations 11 and 12 and UEs 31-32 and 34-35 for participating in the detection of one or more objects. In this first embodiment, system 1 is separate from the base stations and UEs and may be located, for example, within a radio access network. Base stations 11 and 12 may include multiple distributed units sharing a common centralized unit, for example, in a centralized RAN (C-RAN) architecture. In the embodiment of FIG. 9, three UEs 31-33 are connected to base station 11, and three UEs 34-36 are connected to base station 12.

[0125] System 1 comprises a receiver 3, a transmitter 4, a processor 5, and a memory 7. Processor 5 is configured to obtain detection requirements for detecting one or more objects, e.g., object 9, obtain communication requirements, obtain information about each of a set of nodes, select a set of nodes from the set of nodes based on the detection requirements, the communication requirements, and the information about each of the set of nodes, and instruct one or more nodes of the set of nodes, e.g., via base stations 11 and 12, to participate in detecting the one or more objects. At least one node of the set of nodes will transmit a wireless signal, and at least one node of the set of nodes will receive the wireless signal.

[0126] 9 embodiment, base stations 11 and 12 each comprise a receiver 23, a transmitter 24, a processor 25, and a memory 27. Processor 25 is configured to receive instructions from system 1 via receiver 23 to engage in detecting one or more objects, and to transmit (via transmitter 24) and / or receive (via receiver 23) wireless signals to detect the one or more objects based on the instructions. The received wireless signals comprise received versions of the transmitted wireless signals. The received wireless signals reflect the impact of one or more objects on the transmitted wireless signals.

[0127] 9 embodiment, UEs 31-32 and 34-35 each include a receiver 43, a transmitter 44, a processor 45, and a memory 47. Processor 45 is configured to receive instructions from system 1 via receiver 43 to engage in detecting one or more objects, and to transmit (via transmitter 44) and / or receive (via receiver 43) wireless signals for detecting one or more objects based on the instructions. Received wireless signals that include received versions of the transmitted wireless signals that reflect the impact of one or more objects on the transmitted wireless signals are suitable for detection.

[0128] In the example of FIG. 9, UEs 33 and 36 are not configured similarly to UEs 31-32 and 34-35, and system 1 does not have the capability to instruct UEs 33 and 36 to participate in the detection of one or more objects. Nevertheless, base stations 11 and 12 and UEs 31-32 and 34-35 can be instructed to receive wireless signals transmitted by UEs 33 and 36. Because UEs 33 and 36 can be selected as part of a set of nodes but cannot be instructed, UEs 33 and 36 can only be assigned a transmit role (in which role UEs 33 and 36 transmitted unconditioned communication signals). When UEs 33 and / or UEs 36 are assigned a transmit role, UEs 33 and / or UEs 36 do not and need not change their behavior. In an alternative example, all nodes selected by system 1 as part of a set of nodes are capable of receiving and executing instructions from system 1 as described with respect to base stations 11 and 12 and UEs 31-32 and 34-35.

[0129] Instructions that may be received by base stations 11-12 and UEs 31-32 and 34-35 from system 1 may specify whether the nodes should transmit, receive, or transmit and receive wireless signals to detect one or more objects. Processor 25 of base stations 11-12 and processor 45 of UEs 31-32 and 34-35 may be configured to transmit, receive, or transmit and receive wireless signals in response to the instructions.

[0130] In the embodiment shown in FIG. 9, system 1 includes one processor. In alternative embodiments, system 1 includes multiple processors. Processor 5 may be, for example, a general-purpose processor, such as an Intel or AMD processor, or an application-specific processor. Processor 5 may include, for example, multiple cores. Processor 5 may run, for example, a Unix-based or Windows operating system. Memory 7 may include, for example, solid-state memory, such as one or more solid-state disks (SSDs) made from, for example, flash memory, or one or more hard disks.

[0131] The receiver 3 and the transmitter 4 can communicate with the base stations 11 and 12 using one or more wired or wireless communication technologies. The receiver 3 and the transmitter 4 can communicate with other systems, for example, in the radio access network or in the core network, using one or more communication technologies (wired or wireless). The receiver 3 and the transmitter 4 may be combined in a transceiver. The system 1 may comprise other components typical of components in a mobile communication network, for example a power supply.

[0132] In the embodiment shown in Figure 9, base stations 11 and 12 include one processor. In alternative embodiments, one or more of base stations 11 and 12 include multiple processors. The processors of base stations 11 and 12 may be, for example, general-purpose processors, such as Intel or AMD processors, or application-specific processors. The processors may include, for example, multiple cores. The processors may run, for example, a Unix-based or Windows operating system. Memory 27 may include, for example, solid-state memory, such as one or more solid-state disks (SSDs) made from, for example, flash memory, or one or more hard disks.

[0133] The receiver 23 and the transmitter 24 can communicate with the UEs 31-36 using one or more wireless communication technologies, such as Wi-Fi, LTE, and / or 5G new radio. The receiver 23 and the transmitter 24 can communicate with other systems in the radio access network or the core network, for example, using one or more communication technologies (wired or wireless). The receiver 23 and the transmitter 24 may be combined in a transceiver. The base station may include other components typical of components in a mobile communication network, such as a power supply. In the embodiment shown in FIG. 9, each of the base stations may include, for example, a single unit or a central unit and one or multiple distributed units.

[0134] 9, UEs 31-32 and 34-35 each include one processor 45. In an alternative embodiment, one or more of UEs 31-32 and 34-35 include multiple processors. Processor 45 may be a general-purpose processor, such as an ARM or Qualcomm processor, or an application-specific processor. Processor 45 may run, for example, Google Android or Apple iOS as an operating system.

[0135] The receiver 43 and transmitter 44 of the UEs 31-32 and 34-35 may communicate with a base station using one or more wireless communication technologies, such as Wi-Fi, LTE, and / or 5G new radio. The receiver 43 and transmitter 44 may be combined in a transceiver. The UEs 31-32 and 34-35 may include other components typical of user equipment, such as a battery and / or a power connector.

[0136] A UE may also be referred to by those skilled in the art as a mobile station (MS), subscriber station, mobile unit, subscriber unit, wireless unit, wireless terminal, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal (AT), mobile terminal, remote terminal, handset, terminal, user agent, mobile client, client, or some other suitable terminology.

[0137] 10 is a block diagram of a second embodiment of a communication network including a system for enabling detection of one or more objects and nodes for participating in the detection of one or more objects. FIG. 10 illustrates a cellular network including a (Cloud / Distributed) Radio Access Network ((C / D-)RAN) 221 and a Core Network (CN) 211. The RAN 221 includes a User Equipment (UE) 223 and a Base Station (BS) 231. The CN 211 includes different CN-specific functions, including a Communication Application Function (C-AF) 214 and a Sensing Application Function (S-AF) 213. The aforementioned application functions (i.e., C-AF 214 and S-AF 213) process corresponding applications. The BS 231 may include multiple distributed units that share a common centralized unit in, for example, a Centralized RAN (C-RAN) architecture. Although FIG. 10 shows only one base station in RAN 221, RAN 221 would typically include multiple base stations.

[0138] BS 231 is given a sensing task upon receiving a trigger for this sensing task from S-AF 213. BS 231 then implements the method shown in Figure 1 by using different units / functions: information collector 235, node selector 238, radio resource manager 237, sensing data collector 234, and sensing data processor 233. In the embodiment of Figure 10, information collector 235, sensing data processor 233, and node selector 238 are internal to BS 231. In alternative embodiments, one or more of these units / functions are implemented outside BS 231, for example in a separate device.

[0139] The information collector 235 collects information from relevant entities in the network in an information collection phase (including steps 101-105 in FIG. 1). The collected information may include the following information: ● From S-AF 213: Detection requirements, such as target area, target direction, target object, and detection performance requirements, can be collected from S-AF 213. In addition, detection task priorities can also be specified, for example, by the network operator in the operator policy. ● From C-AF214: Communication requirements, e.g., QoS requirements, type of service, are collected from C-AF214. In addition, communication task priorities may also be specified, e.g., by the network operator in an operator policy. These priorities should preferably be defined to have the correct relative meaning, e.g., detection priority level 1 would be treated as a higher priority level than communication priority level 2. These detection task priorities and communication task priorities may be used, for example, to determine to what extent excess communication performance (i.e., communication performance beyond the minimum requirements) is sacrificed in favor of detection performance, and vice versa. ● From BS231's CM and PM information: For example, information indicating BS231's location, cell-specific antenna configuration, cell-specific carrier frequency, cell load, current set of actively transmitted reference signals, maximum transmit power, receiver characteristics, and average channel gain on the radio link between two nodes may be included in the CM (Configuration Management) or PM (Performance Management) data. The CM and PM data may be stored and collected locally at BS231, for example to / from memory 236. Alternatively, the BS231's CM and PM data may be stored non-locally, for example in a "domain OAM server" or "central OAM server." ● From UE 223: For example, information indicating UE location, UE receiver characteristics, and frequency bands supported by the UE may be collected. The information collector 235 may rely on UE information already available at BS 231, collected for different purposes. Information collection may be event-triggered (e.g., handover) or periodic. If the required information is not available at BS 231, the information collector 235 sends a request for new information (e.g., CSI) to all UEs or to a selected group of UEs. In the latter case, UEs may be selected, for example, according to UE location. For example, UEs (both active and inactive) that are within a target detection area may be selected. Inactive UEs may be triggered, for example, by a broadcast message from BS 231 and possibly other BSs. ● From CM and PM information of neighboring base stations (not shown in Figure 10): For example, information indicating the base station location, cell-specific antenna configuration, cell-specific carrier frequency, cell load, the current set of actively transmitted reference signals, maximum transmit power, receiver characteristics, and the average channel gain on the radio link between the two nodes may be collected from neighboring base stations. Neighboring base stations may be queried about the active UEs currently served by them. ● From a network planning tool (not shown in Figure 10): In order to estimate the coverage overlap between a given cell and a target detection area, the information collector 235 may be configured to obtain information from a network planning tool that is capable of estimating such overlap.

[0140] 1 , the information about each of the set of nodes may be obtained, for example, from local information 236, from UE 223, and / or from neighboring base stations. This information may also be aggregated, for example, at a domain level and / or a central level. The information about each of the set of nodes may indicate, for example, one or more of node location, cell-specific antenna configuration, cell-specific carrier frequency, cell load, current set of actively transmitted reference signals, maximum transmit power, receiver characteristics, supported frequency bands, and average channel gain on the wireless link between the two nodes.

[0141] To collect information about sensing requirements from the S-AF 213 when the information collector 235 is part of the BS 231, there are two main options: 1. Information is pushed by S-AF 213 to BS 231 via information collector 235; for example, in the case of a unique sensing task, S-AF 213 forwards the requirements to a pre-assigned BS, e.g., BS 231, to perform the sensing. If there are updates to the requirements of an ongoing sensing task, the updates can be pushed to the assigned BS, e.g., BS 231. This is the preferred option.

[0142] 2. Information is pulled from the S-AF 213 by the information collector 235, for example, the BS 231 can proactively / periodically check for requirement updates. Sensory measurements collected by sensory data collector 234 may be shared with S-AF 213 (optionally via information collector 235) as follows.

[0143] 1. The sensing data collector 234 shares raw data, for example, when the BS 231 is a simple base station with insufficient processing capabilities (e.g., in an embodiment different from that of FIG. 10 , there is no dedicated sensing data processor 233) or when raw data from multiple base stations needs to be fused / combined or otherwise processed together. In this implementation, the BS 231 enables the S-AF 213 to determine one or more physical properties of one or more sensed objects. In this implementation, the S-AF 213 is a data processing system that determines one or more physical properties for each of the one or more objects based on characteristics of the received signal acquired by the BS 231. For example, the sensing data processor 233 may be included in the S-AF 213 rather than the BS 231.

[0144] 2. The sensing data processor 233 shares the (partially) processed data, for example, if the BS 231 has sufficient processing power (e.g., when there is a dedicated sensing data processor 233 as shown in FIG. 10) or in case of limited backhaul capacity. In this implementation, the processor 233 of the BS 231 determines one or more physical properties for each of the one or more objects based on characteristics of the received signals.

[0145] The interface between C-AF 214 and BS 231 may be 3GPP-compliant (e.g., LTE, 5G). Considering 5G technology, assuming a protocol data unit (PDU) session is already active, device-terminating (in other words, network-originating) QoS flow establishment has the following steps: (i) C-AF 214 first submits a flow establishment request to Policy Control Function (PCF) 215, which acts as a coordinator during flow establishment; and (ii) checks with BS 231 for acceptability from the RAN perspective and with User Plane Function (UPF) 217 ​​for acceptability from the core network perspective via Session Management Function (SMF) 216. As part of the process, BS 231 will page one of the target UEs, e.g., UE 223, to establish a signaling connection to assist in the acceptability check. For device-originated QoS flow establishment, the UE first establishes a signaling connection and then signals the QoS flow establishment request to the PCF 215, which again coordinates the process in the same way as it did for establishing a device-terminated QoS flow.

[0146] Based on the collected information, node selector 238 performs steps 107 and 109 of the method of Figure 1. One of the selected nodes may be BS 231 itself. In this case, node selector 238 instructs another component of BS 231. Optionally, radio resource manager 237 then performs step 111 of the method of Figure 1 by making scheduling and beam management decisions. These decisions are used by BS 231 to perform step 113 of Figure 1. Sensory data collector 234 then performs step 115 of Figure 1, and sensory data processor 233 then performs step 117 of Figure 1.

[0147] FIG. 11 depicts a block diagram illustrating an exemplary data processing system that may implement the methods as described with reference to FIGS. 11 , data processing system 300 may include at least one processor 302 coupled to a memory element 304 through a system bus 306. Thus, the data processing system may store program code in the memory element 304. Further, processor 302 may execute program code accessed from the memory element 304 via the system bus 306. In one aspect, the data processing system may be implemented as a computer suitable for storing and / or executing program code. Nevertheless, it should be appreciated that data processing system 300 may be implemented in the form of any system including a processor and memory capable of performing the functions described herein.

[0148] The storage element 304 may include one or more physical memory devices, such as, for example, a local memory 308 and one or more bulk storage devices 310. Local memory may refer to random access memory or other non-persistent memory devices typically used during the actual execution of program code. The bulk storage device may be implemented as a hard drive or other persistent data storage device. The processing system 300 may also include one or more cache memories (not shown) that provide temporary storage of at least some program code to reduce the number of times the program code must be retrieved from the bulk storage device 310 during execution.

[0149] Input / output (I / O) devices, depicted as input devices 312 and output devices 314, may optionally be coupled to the data processing system. Examples of input devices may include, but are not limited to, a keyboard, a pointing device such as a mouse, or the like. Examples of output devices may include, but are not limited to, a monitor or display, speakers, or the like. Input and / or output devices may be coupled to the data processing system directly or through intervening I / O controllers.

[0150] In one embodiment, the input and output devices may be realized as a combined input / output device (illustrated in FIG. 11 by the dashed lines surrounding input device 312 and output device 314). An example of such a combined device is a touch-sensitive display, sometimes referred to as a "touchscreen display" or simply a "touchscreen." In such an embodiment, input to the device may be provided by movement of a physical object, such as a stylus or a user's finger, on or near the touchscreen display.

[0151] Network adapters 316 may also be coupled to the data processing system to enable the data processing system to become coupled to other systems, computer systems, remote network devices, and / or remote storage devices through intervening private or public networks. A network adapter may comprise a data receiver for receiving data transmitted to data processing system 300 by the systems, devices, and / or networks, and a data transmitter for transmitting data from data processing system 300 to the systems, devices, and / or networks. Modems, cable modems, and Ethernet cards are examples of different types of network adapters that may be used with data processing system 300.

[0152] As depicted in FIG. 11 , the storage element 304 may store an application 318. In various embodiments, the application 318 may be stored in the local memory 308, one or more bulk storage devices 310, or may be separate from the local memory and the bulk storage devices. It should be understood that the data processing system 300 may further execute an operating system (not shown in FIG. 11 ) that may facilitate the execution of the application 318. The application 318, embodied in the form of executable program code, may be executed by the data processing system 300, for example, by the processor 302. In response to executing the application, the data processing system 300 may be configured to perform one or more operations or method steps described herein.

[0153] Various embodiments of the present invention may be implemented as a program product for use with a computer system, the program of the program product defining the functions of the embodiments (including the methods described herein). In one embodiment, the program may be embodied in various non-transitory computer-readable storage media; as used herein, the expression "non-transitory computer-readable storage media" includes all computer-readable media, with the sole exception of transitory propagating signals. In another embodiment, the program may be embodied in various transitory computer-readable storage media. Exemplary computer-readable storage media include, but are not limited to, (i) non-writable storage media in which information is permanently stored (e.g., a read-only memory device in a computer, such as a CD-ROM disk readable by a CD-ROM drive, a ROM chip, or any type of solid-state nonvolatile semiconductor memory), and (ii) writable storage media in which changeable information is stored (e.g., flash memory, a floppy disk in a diskette drive or hard disk drive, or any type of solid-state random-access semiconductor memory). The computer program may be executed on the processor 302 described herein.

[0154] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise. It will be further understood that the terms "comprises" and / or "comprising," as used herein, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0155] The corresponding structure, material, acts, and equivalents of all means or step and functional elements in the following claims are intended to include any structure, material, or acts for performing a function in combination with other claim elements as specifically claimed. The description of the embodiments of the present invention has been presented for illustrative purposes, but is not intended to be exhaustive or limited to the implementation in the form disclosed. Many modifications and variations will be apparent to those skilled in the art without departing from the scope of the invention. The embodiments were chosen and described to best explain the principles and some practical applications of the invention, and to enable others skilled in the art to understand the invention for various embodiments with various modifications as suited to the particular uses envisioned.

Claims

1. A system (1, 231) for enabling the detection of one or more objects (9), comprising: - obtaining detection requirements for detecting said one or more objects (9); - obtaining communication requirements; obtaining information about each of the set of nodes (11-12, 31-32, 34-35, 223, 231); selecting a set of nodes from said set of nodes (11-12, 31-32, 34-35, 223, 231) based on said sensing requirement, said communication requirement and said information about each of said set of nodes; instructing one or more nodes of said set of nodes to participate in detecting said one or more objects (9), wherein at least one node of said set of nodes transmits a wireless signal and at least one node of said set of nodes receives said wireless signal; A system (1, 231) comprising at least one processor (5) configured to:

2. The at least one processor (5) - obtaining a characteristic of the received wireless signal, the received wireless signal comprising a received version of the transmitted wireless signal, the received wireless signal reflecting an impact of the one or more objects (9) on the transmitted wireless signal; determining, or enabling another system to determine, one or more physical properties for each of said one or more objects (9) based on said characteristics of said received wireless signals; and The system (1, 231) of claim 1, configured to:

3. 3. The system (1, 231) of claim 1 or 2, wherein the information for each of the set of nodes indicates one or more of node location, cell-specific antenna configuration, cell-specific carrier frequency, cell load, a current set of actively transmitted reference signals, a maximum transmit power, receiver characteristics, supported frequency bands, and an average channel gain on a wireless link between two nodes.

4. 4. The system (1, 231) of claim 1, wherein the at least one processor (5) is configured to assign each respective node of the set of nodes to a first set of transmitting nodes and / or a second set of receiving nodes, the first set of transmitting nodes transmitting the wireless signals and the second set of receiving nodes receiving the wireless signals.

5. The system (1, 231) of claim 4, wherein the at least one processor (5) is configured to instruct the second set of receiving nodes to receive the wireless signals for the sole or additional purpose of detecting the one or more objects (9).

6. The system (1, 231) of claim 4 or 5, wherein the at least one processor (5) is configured to instruct the first set of transmitting nodes to transmit the wireless signals for the sole or additional purpose of detecting the one or more objects (9).

7. 7. The system (1, 231) of claim 6, wherein the wireless signal comprises a wireless communication signal conditioned for detecting the one or more objects (9) and / or a dedicated detection signal.

8. The at least one processor (5) forming a plurality of candidate node combinations from the set of nodes (11-12, 31-32, 34-35, 223, 231), each of the plurality of node combinations comprising a first subset and a second subset of the set of nodes (11-12, 31-32, 34-35, 223, 231), the first subset being assigned the role of transmitting the wireless signal and the second subset being assigned the role of receiving the wireless signal; - determining, for each of said plurality of node combinations, at least one communication performance for at least one communication task and at least one sensing performance for at least one sensing task based on said information for each of said sets of nodes (11-12, 31-32, 34-35, 223, 231); determining, for each of the plurality of node combinations, whether the communication and sensing requirements can be met based on the at least one communication performance and the at least one sensing performance; selecting a combination of nodes from the plurality of node combinations as the set of nodes based on one or more of the at least one communication capability and the at least one sensing capability and based on whether the communication and sensing requirements can be met; assigning said first subset of said selected node combinations to said first set and said second subset of said selected node combinations to said second set; The system (1, 231) according to any one of claims 4 to 7, configured to:

9. The system (1, 231) of claim 8, wherein the at least one processor (5) is configured to determine the detection performance by determining, for each node combination among the plurality of node combinations and for each detection task among the at least one detection task, a detection probability based on the role assigned to the node in the node combination.

10. The at least one processor (5) for each node combination of the plurality of node combinations, determining a processing cost for the second subset of the respective node combinations based on the information for each of the sets of nodes; selecting said combination of nodes as said set of nodes further based on said processing cost; 10. The system (1, 231) according to claim 8 or 9, configured to:

11. The at least one processor (5) selecting a plurality of candidate nodes from said set of nodes (11-12, 31-32, 34-35, 223, 231) based on said information for each of said set of nodes; selecting said set of nodes from said plurality of candidate nodes based on said sensing requirements, said communication requirements, and said information; The system (1, 231) according to any one of claims 1 to 10, configured to:

12. 12. The system (1, 231) of claim 11, wherein the information about each of the set of nodes (11-12, 31-32, 34-35, 223, 231) indicates the willingness and / or ability of each node to participate in the detection of the one or more objects and / or indicates the proximity of each node to an area of ​​interest, the area of ​​interest being specified in the detection requirements, and wherein the at least one processor (5) is configured to select the plurality of candidate nodes based on the willingness and / or ability of the nodes to participate in the detection and / or based on the proximity of the nodes to the area of ​​interest.

13. a node (11-12, 31-32, 34-35, 223, 231) for participating in the detection of one or more objects (9), receiving a command from a system (1, 231) for enabling the detection of one or more objects (9) to participate in detecting said one or more objects (9); - transmitting and / or receiving, based on said instructions, wireless signals for detecting said one or more objects (9), said received wireless signals comprising received versions of said transmitted wireless signals, said received wireless signals reflecting an impact of said one or more objects on said transmitted wireless signals; a node (11-12, 31-32, 34-35, 223, 231) including at least one processor (25, 45) configured to perform the following:

14. The node (11-12, 31-32, 34-35, 223, 231) of claim 13, wherein the instructions specify whether the node (11-12, 31-32, 34-35, 22, 2313) should transmit, receive, or transmit and receive the wireless signals to detect the one or more objects (9), and the at least one processor (25, 45) is configured to transmit, receive, or transmit and receive the wireless signals in response to the instructions.

15. 1. A method for enabling detection of one or more objects, comprising: - obtaining (101) detection requirements for detecting said one or more objects; a step of obtaining communication requirements (103), - obtaining information about each of the set of nodes (105); - selecting (107) a set of nodes from said set of nodes based on said sensing requirements, said communication requirements and said information about each of said set of nodes; instructing one or more nodes of said set of nodes to participate in detecting said one or more objects (109), wherein at least one node of said set of nodes transmits a wireless signal and at least one node of said set of nodes receives said wireless signal; A method comprising:

16. 1. A method involving the detection of one or more objects, comprising: - receiving (121) an instruction from a system for enabling the detection of one or more objects to participate in detecting said one or more objects; - transmitting and / or receiving (123) wireless signals for detecting the one or more objects based on the instructions, the received wireless signals comprising received versions of the transmitted wireless signals, the received wireless signals reflecting an impact of the one or more objects on the transmitted wireless signals; A method comprising:

17. 17. A computer program or suite of computer programs comprising at least one software code portion, or a computer program product storing at least one software code portion, said computer program or suite of computer programs or computer program product being configured to perform the method according to claim 15 or 16 when said software code portion is executed on a computer system.

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