Orchestration system and reader device for orchestrating backscatter communication

Abstract

The disclosure pertains to an orchestration system for orchestrating backscatter communication in a backscatter communication system comprising at least one backscatter device storing data to be read through the backscatter communication triggered by an excitation signal from an excitation source. The backscatter communication system may comprise at least a first reader device for reading the data from the backscatter device and a second reader device for reading the data from the backscatter device. The orchestration system may be configured to select the first reader device or the second reader device to read the data from the backscatter device by performing an energy efficiency optimization algorithm for the backscatter communication system. The orchestration system takes into account at least one of a first transmit power and a second transmit power of the excitation signal of the excitation source to trigger the backscatter communication to the first reader device and the second reader device, respectively, and a first data rate and a second data rate for transmitting the data from the backscatter device to the first reader device and the second reader device, respectively.

Description

[0001] Orchestration system and reader device for orchestrating backscatter communication

[0002] TECHNICAL FIELD

[0003] The present disclosure relates to an orchestration system for orchestrating backscatter communication in a backscatter communication system comprising at least one backscatter device comprising data to be read though the backscatter communication. In particular, the disclosure relates to such an orchestration system wherein a selection is made between at least a first reader device and a second reader device of the backscatter communication system.

[0004] BACKGROUND

[0005] Low-power networks are a crucial component of Internet-of-Things (loT) and machine-to- machine (M2M) communication. Low-power devices may, for example, rely on energy-harvesting, which requires that these devices must operate in an energy efficient manner. Such devices may be referred to as power-constrained devices, backscatter devices or simply as tags.

[0006] For example, 3GPP recently issued a study on ambient power-enabled loT devices, in Technical Recommendation 3GPP TR 22.840. The document discloses use cases and requirements for ambient power-enabled loT devices, being battery-less devices with limited energy storage capability (a capacitor may be included) wherein the energy is provided through the harvesting of radio waves, for example. Such ambient power-enabled loT devices are generally of low complexity.

[0007] Backscatter communication is one of the core-technologies to realize zero-power communication. Backscatter communication may involve an excitation source device generating an excitation signal powering a backscatter device and triggering a backscatter signal from this device. The backscattered signal may be modulated to carry data in the backscattered signal which may be received by a local reader device as a destination or hub for the data.

[0008] Energy efficiency of backscatter communication becomes increasingly relevant when multiple excitation signal source devices and / or reader devices are deployed in an area.

[0009] SUMMARY

[0010] The present disclosure provides for an orchestration system that orchestrates backscatter communication by selecting the most suitable reader device for reading the data based on energy efficiency considerations.

[0011] To that end, one aspect of the disclosure relates to an orchestration system for orchestrating backscatter communication in a backscatter communication system comprising at least one backscatter device storing data to be read through the backscatter communication triggered by an excitation signal from an excitation source. The backscatter communication system may comprise at least a first reader device for reading the data from the backscatter device and a second reader device for reading the data from the backscatter device. More reader devices may be deployed near the backscatter device and may be considered by the orchestration system for reading the data. The orchestration system may be configured to select the first reader device or the second reader device to read the data from the backscatter device by performing an energy efficiency optimization algorithm for the backscatter communication system. Preferably, the orchestration system selects only one of the first reader device and the second reader device, but in cases where more than two reader devices are deployed, at least two reader devices may be selected, for example when some redundancy is desired for additional reliability. The orchestration system takes into account at least one of a first transmit power and a second transmit power of the excitation signal of the excitation source to trigger the backscatter communication to the first reader device and the second reader device, respectively, and a first data rate and a second data rate for transmitting the data from the backscatter device to the first reader device and the second reader device, respectively.

[0012] Huang et al in RAScater: Achieving Energy-Efficient Backscatter Readers via Al-Assisted Power Adaptation have recently shown in 2022 IEEE / ACM Seventh International Conference on Internet-of-Things Design and Implementation (loTDI) that a maximum transmit power for an excitation source signal to trigger backscatter communication is often unnecessary and energy savings can be obtained by tuning the transmit power appropriately using a neural network model. A reduced transmit power for the excitation signal slows down the data rate but may improve the overall energy efficiency of the data transfer.

[0013] The inventors enhanced this approach by disclosing an orchestration system enabling energy optimization, for example energy reduction, for a complete backscatter communication system, wherein ultimately a reader device is selected for backscatter communication with a backscatter device based on energy efficiency optimization considerations. The orchestration system may take the transmit power of the excitation source signal and / or data rate for communication with the first reader device and second reader device into account in the energy efficiency optimization algorithm for the selection of the most appropriate reader device energy-wise. One measure for energy efficiency may be the ratio of the energy or power over the data rate or the inverse thereof. This may result in an energy consumption estimate for each reader enabling a selection of the most energy efficient reader device. It should be noted that the transmit power of the excitation signal relates directly or indirectly to the reader device when the excitation source device is integral to the reader device, respectively, when the reader device is connected to an external excitation source device.

[0014] In one embodiment, the orchestration system may be configured to apply a neural network to determine the first transmit power and second transmit power and / or the first data rate and second data rate in dependence on at least channel characteristics, also referred to as probing metrics herein, for the backscatter communication from the backscatter device to the first reader device and to the second reader device to select the first reader device or the second reader device. The energy efficiency optimization algorithm may be implemented at least in part in the neural network.

[0015] The application of a neural network facilitates more accurate estimation of the data rate and / or transmit power to be applied under practical circumstances by taking the channel characteristics into account to optimize energy efficiency. The neural network may provide a correlation between a desired throughput, or goodput, of the reader device, which is a constraint for optimizing energy efficiency, and the existing channel characteristics and the optimal transmit power and / or optimal data rate. In one embodiment, the desired throughput, or one or more parameters representing such throughput, and recent channel characteristics are input in the neural network and the optimal transmit power and optimal data rate result as output.

[0016] The optimal transmit power for transmission of the excitation signal may be a minimum transmit power, e.g. the minimum transmit power corresponding to the desired throughput or optimal data rate.

[0017] The orchestration system may determine and apply a plurality of neural networks when different device types, that account for different data sets, apply. For example, when reader devices are not of the same type, different channel metrics may apply that need to be obtained for each type of reader device. Also, available data rates may differ between different devices, for example.

[0018] In one embodiment, at least one of the first transmit power, the second transmit power, the first data rate and the second data rate are adaptable. The orchestration system is configured to control the at least one of the first transmit power, the second transmit power, the first data rate and the second data rate. Adjustability of one or more of these parameters provides more freedom for the orchestration system to find optimum settings to save energy.

[0019] The orchestration system may need to take one or more constraints into account when selecting a reader device using the energy efficiency optimization algorithm. This may occur, for example, via the transmit power and / or data rate.

[0020] Hence, in one embodiment, the first transmit power and the second transmit power and / or the first data rate and the second data rate may further be determined based on at least one of a time parameter for transmitting the data and a size parameter for the size of the data in the backscatter device.

[0021] The time parameter may indicate when the data should be transmitted to meet a delivery demand, for example, of the operator of the backscatter device.

[0022] The size parameter may indicate the amount of data to be transferred and can be used to estimate the minimum throughput required to obtain the data from the backscatter device.

[0023] These constraints are advantageously taken into account by the orchestration system to enable energy optimization while meeting data delivery requirements or demands, for example. Optionally, the time parameter and size parameter are used to determine a desired data throughput for the first reader device and second reader device. This may be input into the neural network, possibly in addition to the channel characteristics, to obtain the transmit power of the excitation signal and / or data rate.

[0024] By not using the maximum transmit power for the excitation signal, it may generally take longer for the data to be transmitted to the reader device, but this may optimize the overall energy efficiency for the backscatter communication system. On the other hand, it is not always the reader device with the maximum amount of time available to obtain the data from the backscatter device that is the most suitable reader device for energy efficient operation. The time parameter is thus a parameter to take into account for the orchestration. For example, the first reader device may be associated with first communication resources and the second reader device may be associated with second communication resources, wherein the first and second communication resources comprise a first time schedule and a second time schedule, for example, for receiving the data at the first reader device and the second reader device, respectively. The time parameter may be a time limit associated with the data. The orchestration system may be configured to select the first reader device or second reader device taking account of meeting the time limit in view of the first time schedule and second time schedule and the size parameter for the size of the data.

[0025] It should be appreciated that the time limit may, for example, be an ultimate time when the data needs to be transmitted to a reader device, be received by a reader device, be received at the orchestration system, be received at a data collection entity, etc. The orchestration system considers the time limit and size parameter for the size of the data in view of the time schedules to select the most appropriate reader device of the at least two reader devices. More particularly, the orchestration system may determine an available reading time from the time parameter and the communication resources and obtain a desired throughput taking the data size into account. The desired throughput may be an input parameter for the neural network.

[0026] It should also be appreciated that the time schedules may also be determined by available time slots for the excitation source device for transmitting the excitation signal, processor load of either device in the backscatter communication system, etc.

[0027] It should further be appreciated that, for example from an energy efficiency optimization perspective, it is not sufficient for selection of the reader device that it has sufficient time to obtain the data. The reader device may, for example, have an optimal transmit power itself, assuming the reader device has an integrated excitation signal transmitter, and the channel characteristics may influence data transfer efficiency as well.

[0028] In one embodiment, the orchestration system may further be configured to obtain the time parameter for transmitting the data by the backscatter device and / or for receiving the data by the reader device or orchestration system through at least one of the following: a request from a data service or data function connected to the orchestration system; information obtained from or in the first reader device and the second reader device; predetermined information of a required transmission time or expiration time of the data in the backscatter device.

[0029] In one embodiment, the orchestration system may further be configured to obtain the size parameter for the size of the data in the backscatter device through at least one of the following: an estimate based on previous data transmissions; the size parameter for the size of the data is fixed or approximately fixed.

[0030] The embodiments facilitate obtaining information on the time parameter and size parameter to ensure that the data is collected at a suitable time by a suitable reader device. The information is further useful for selecting an energy-wise optimum reader device under these constraints. In one embodiment, the orchestration system may further be configured to select the first reader device or the second reader device in accordance with a device type for at least one of the first reader device and the second reader device, and the backscatter device.

[0031] The embodiment considers device types and / or device type combinations to be of relevance when selecting a suitable reader device for backscatter communication by a backscatter device. Device types, or indications thereof, may refer to one or more feature sets for a reader device or backscatter device, including capabilities (e.g. maximum transmit power, step size for adjusting transmit power, if adjustment is possible), properties and / or location of these devices (e.g. battery power and location of a mobile reader device, or location of a fixed, continuously powered reader device). Different neural networks may apply for different device types or device type combinations when determining optimal transmit power and optimal data rate.

[0032] In one embodiment, the orchestration system may be configured to obtain information from at least one of the first reader device, the second reader device and the backscatter device, wherein the information comprises at least one of the following: device capabilities, device properties, device location, device type. This information may be obtained for at least one of the first reader device, the second reader device and the backscatter device for use in the energy efficiency optimization algorithm. This information can be used fortraining the neural network. Training the neural network may be done repeatedly to account for changes in the backscatter communication system.

[0033] The orchestration system may be deployed at several places. In one embodiment, the orchestration system may be a centralized system in the network, for example in a 3GPP standard compliant network. The centralized system may be a base station, such as a gNb, of such a network. The centralized system may also comprise a specific backscatter orchestration function in the network. In another embodiment, the orchestration system may be a distributed system in a telecommunications network, wherein functionality of the orchestration system is distributed amongst systems or functions in the network. Different information for selecting the suitable reader device may, for example, be available at different systems in the network. For example, information regarding the time parameter may be available in the core network wherein information on the size parameter for the size of the data and / or the data rate may be available in the radio access network. On the other hand, one embodiment of the orchestration system may be downstream towards the backscatter device, for example by an integration of the orchestration system, at least in part, in one or more of the reader devices. In such an embodiment, the orchestrating system, as part of the reader device, may select itself as the most suitable reader device for backscatter communication with the backscatter device. For example, each reader device may determine its potential energy efficiency, possibly taking into account time and size constraints, whereas the selection may be performed by a single reader device or orchestration system. Yet another embodiment resides in the orchestration system comprising a stand-alone system connected to the first reader device and second reader device. The disclosure also pertains to any combination of these embodiments for deployment of the orchestration system.

[0034] A further aspect of the disclosure relates to a reader device configured to provide data from a backscatter device through backscatter communication for use with the orchestration system as described herein. The reader device may be configured to process a selection command from the orchestration system to receive the data from the backscatter device. This feature of the reader device enables the orchestration system to select a reader device based on energy efficiency optimization considerations. The processing of the reader device may include a trigger for transmitting an excitation signal (if the reader has an internal excitation source device) or instructing an external excitation source device to transmit the excitation signal with the applicable transmit power.

[0035] In one embodiment, the reader device may be configured, optionally in response to a request from the orchestration system, to provide information to the orchestration system enabling the orchestration system to determine at least one of a transmit power of the excitation signal of an excitation source to trigger the backscatter communication to the reader device and a data rate for transmitting the data from the backscatter device to the reader device. This information assists the orchestration system in determining appropriate parameters for an energy efficient transmission of the data to the appropriate reader device.

[0036] The information may include information regarding the backscatter device and / or information regarding the particular reader device.

[0037] In one embodiment, the reader device may be configured to provide further information regarding the backscatter device to the orchestration system. This information may include one or more of channel characteristics of a backscatter channel between the backscatter device and the reader; a device type of the backscatter device; a size parameter for the size of the data in the backscatter device; capabilities and / or features of the backscatter device, including, for example, adjustability of the data rate for sending the data through backscatter communication; location of the backscatter device etc. The reader device is a suitable device to collect the further information because of its proximity to the backscatter device. For collecting the information, the reader device may use an internal excitation signal source to receive the further information or collect the information when the backscatter device is triggered from an external excitation source to send the information.

[0038] In one embodiment, the reader device may be configured to provide further information regarding the reader device to the orchestration system. This information may include one or more of communication resources of the reader device, including a reader time schedule, for example; device type of the reader device; capabilities and / or features of the reader device and location of the reader device. This information may assist the orchestration system in selecting the appropriate reader device as disclosed herein.

[0039] In one embodiment, the reader device may include at least a part of the orchestration system as disclosed herein. The reader device may then be selectable by the, at least in part, integrated orchestration system.

[0040] In one embodiment, the reader device may comprise at least one of an integrated excitation source for transmitting an excitation signal to trigger backscatter communication from the backscatter device and a feedback connection to an external excitation source for transmitting an excitation signal to trigger backscatter communication from the backscatter device. Optionally, the reader device may be configured to receive a control signal from the orchestration system to control adjustment of the transmit power for the integrated, resp. external, excitation source device. This may assist in lower energy requirements for the data communication.

[0041] Another aspect of the disclosure involves a method in an orchestration system for backscatter communication in a backscatter communication system comprising at least one backscatter device storing data to be read through the backscatter communication triggered by an excitation signal from an excitation source. The backscatter communication system may comprise at least a first reader device for reading the data from the backscatter device and a second reader device for reading the data from the backscatter device. The method may involve the step of selecting the first reader device or the second reader device to read the data from the backscatter device by performing an energy efficiency optimization algorithm for the backscatter communication system. The method may also involve the step of taking into account at least one of a first transmit power and a second transmit power of the excitation signal of the excitation source to trigger the backscatter communication to the first reader device and the second reader device, respectively, and a first data rate and a second data rate for transmitting the data from the backscatter device to the first reader device and the second reader device, respectively in the energy efficiency optimization algorithm.

[0042] A further aspect of the disclosure relates to a method in a reader device configured to provide data from a backscatter device through backscatter communication for use with the orchestration system as described herein. The method involves processing a selection command from the orchestration system to receive the data from the backscatter device. The processing of the reader device may include a trigger for transmitting an excitation signal (if the reader has an internal excitation source device) or instructing an external excitation source device to transmit the excitation signal with the applicable transmit power.

[0043] Still other aspects of the disclosure involve a computer program comprising software code portions configured, when run on a computer system, to execute one or more steps of the method in the orchestration system and the reader device, respectively, as well as a carrier comprising such a computer program.

[0044] Another aspect of the disclosure pertains to a backscatter communication system comprising at least an orchestration system and two reader devices.

[0045] The orchestration system may be configured to select the first reader device or the second reader device to read the data from a backscatter device by performing an energy efficiency optimization algorithm for the backscatter communication system. The orchestration system takes into account at least one of a first transmit power and a second transmit power of the excitation signal of the excitation source to trigger the backscatter communication to the first reader device and the second reader device, respectively, and a first data rate and a second data rate for transmitting the data from the backscatter device to the first reader device and the second reader device, respectively. The orchestration system may further generate a selection command for the selected reader device. The reader device may be configured to provide data from a backscatter device through backscatter communication for use with the orchestration system as described herein. The reader device may be configured to process the selection command from the orchestration system to receive the data from the backscatter device. This feature of the reader device enables the orchestration system to select a reader device based on energy efficiency optimization considerations. The processing of the reader device may include a trigger for transmitting an excitation signal (if the reader has an internal excitation source device) or instructing an external excitation source device to transmit the excitation signal with the applicable transmit power.

[0046] As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, 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, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Functions described in this disclosure may be implemented as an algorithm executed by a processor / microprocessor of a computer. Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied, e.g., stored, thereon.

[0047] Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A 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 a computer readable storage medium may include, but are not limited to, the following: 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 connection with an instruction execution system, apparatus, or device.

[0048] A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, 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, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0049] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber, 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 an object-oriented programming language 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 person’s computer, partly on the person's computer, as a stand-alone software package, partly on the person’s computer and partly on a remote computer, or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the person’s computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0050] 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 present 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 may be provided to a processor, in particular a microprocessor or a central processing unit (CPU), of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer, other programmable data processing apparatus, or other devices create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0051] These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function / act specified in the flowchart and / or block diagram block or blocks.

[0052] The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0053] The flowchart and block diagrams in the figures Illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). 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 upon the functionality involved. It will 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 special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

[0054] Moreover, a computer program for carrying out the methods described herein, as well as a non- transitory computer readable storage-medium storing the computer program are provided.

[0055] Elements and aspects discussed for or in relation with a particular embodiment may be suitably combined with elements and aspects of other embodiments, unless explicitly stated otherwise. Embodiments of the present invention will be further illustrated with reference to the attached drawings, which schematically will show embodiments according to the invention. It will be understood that the present invention is not in any way restricted to these specific embodiments.

[0056] BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Aspects of the invention will be explained in greater detail by reference to exemplary embodiments shown in the drawings, in which:

[0058] FIG. 1 is a schematic illustration of a backscatter communication system comprising an orchestration system, a plurality of reader devices and a plurality of backscatter devices;

[0059] FIG. 2 is a schematic illustration of a backscatter device;

[0060] FIG. 3 is a schematic diagram illustrating reader device selection according to some principles of the disclosure;

[0061] FIG. 4 illustrates some steps for operating a backscatter communication system as disclosed herein;

[0062] FIGS. 5A-5C are detailed embodiments associated with the operating steps of FIG. 4;

[0063] FIG. 6 illustrates some steps of an embodiment of operating the orchestration system; and

[0064] FIG. 7 depicts an example of a processing system according to an embodiment of an orchestration system or a reader device or a part thereof.

[0065] DETAILED DESCRIPTION OF THE DRAWINGS

[0066] FIG. 1 is a schematic illustration of a backscatter communication system 1 . Backscatter communication system 1 comprises an orchestration system 10, a plurality of reader devices 20, numbered 20A, 20B, 20C in FIG. 1 , and a plurality of backscatter devices 30 distributed over an area of the backscatter communication system 1. The backscatter devices 30, hereinafter also referred to as tags 30, may be used by a data collecting entity DCE interested in data stored in or gathered by the tags 30. Communication between the orchestration system 10 and the reader devices 20A, 20B, 20E may be wireless or wired.

[0067] Backscatter communication is a low-power, battery-less data transmission method, wherein tags 30 receive an excitation signal that may power the tag 30 and trigger the tag to transmit data. The excitation signal may be transmitted from an excitation source Tx, see FIG. 3, which may be integral to a reader device (20D in FIG. 3) or external (as for reader device 20E in FIG. 3).

[0068] FIG. 2 is a schematic illustration of a passive wireless communication device 30. Passive wireless transmission devices 30 are power-restricted devices, such as ambient power-enabled loT devices. Such devices may also be referred to as passive loT devices, ambient loT devices or simply tags. Such devices may be battery-less devices with limited energy storage capability (a capacitor may be included) wherein the energy is provided through the harvesting of radio waves, light, motion, heat or any other power source that could be suitable. Thus, energy is a very scarce resource in this context, and its usage is preferably optimized by limiting computations and / or the number and size of exchanged messages. Additionally, a passive wireless communication device may remain passive for extended periods of time before receiving a wake-up signal and starting to send data.

[0069] The passive wireless communication device 30 may be configured to receive and process a wireless transmission, such as radio signal from an excitation source device Tx. The device 30 comprises a processing part 31 , a storage part 32 and a power harvesting part 33. Storage part 32 may be configured to store data, such as data from one or more sensors 34 and / or data about the tag etc. Other data that may be stored include a device identifier of the device 30, a device type identifier, capabilities of the tag 30, etc. The device 30 may also comprise a transmitter part 35 for wireless transmissions. The device 30 may comprise further parts or functions, such as at least one sensor 34 (or a connector therefore). It should be appreciated that device 30 may comprise a plurality of sensors 34 or connectors therefore. Examples of sensors include a location sensor, a temperature sensor, a humidity sensor, a light sensor, a pressure sensor, a motion sensor etc.

[0070] The device 30 is configured to harvest power to activate at least the processing part 31 and, optionally, the other parts, such as at least one of the storage part 32, transmitter part 35 and sensor 34. Power supply lines to these parts are indicated by the solid lines in FIG. 2. The processing part 31 is configured to process wireless transmissions received from one or more excitation source device Tx, for example to detect a request for information. Signal lines for such action(s) are indicated by the dashed-dotted lines in FIG. 2.

[0071] It should be appreciated that devices 30 may comprise more or fewer parts. Essentially, the device 30 is a battery-less device with limited, if any, energy storage capability. In one embodiment, the power harvesting part 33 and transmitter part 35 are combined, at least in part, when the device 30 gathers energy from wireless radio transmissions and communicates via such transmissions as well.

[0072] FIG. 3 is a schematic diagram illustrating selection of a reader device 20D according to some principles of the disclosure.

[0073] An excitation source device Tx / Rx typically transmits at full power to ensure activation and high data throughput of data from the tag 30. This is shown in FIG. 3 by the bold arrow between an excitation source device and a tag 30, wherein data from the tag 30 is transferred from the tag 30 to the reader Rx. This backscatter communication of data was found to be energetically inefficient since much of the power of the excitation signal is unnecessarily absorbed or dissipated by the tag 30.

[0074] More efficient communication can be achieved by reducing the transmit power of the excitation signal.

[0075] The present disclosure enables analyzing the energy expenditure for various selections of reader device 20A, 20B, 20C, resp. 20D, 20E, wherein the transmit power of the excitation signal, that thus does not have to be maximal, and / or data rate is taken into account in order to select a reader device. In FIG. 3, reader device 20D is selected from orchestrating system 10, which is energetically more efficient to obtain the data from the tag 30 than when using the maximum power for the excitation signal, as shown by the thin arrows between the orchestrating system 10 and the reader device 20D and between the reader device 20D and the tag 30. Reader device 20D includes an excitation source device Tx as shown. If reader device 20E was selected, it could have used external excitation signal source device Tx, to which the reader device 20D is connected, as shown in FIG. 3. The excitation source device Tx may also be connected directly to the orchestration system 10 as shown by the dashed line, in which case the orchestration system may control a source device - reader device pair.

[0076] To that end, orchestration system 10 contains a processor 11 connected to a data storage 12 and a communication module 13 for communicating with reader devices 20D, 20E.

[0077] Reader device 20D includes a processor 21 , a data storage 22 and a communication module 23 for communicating with the orchestrating system 10. Reader device 20E contains the same components (not shown). As mentioned above, reader device 20D contains an excitation signal source device Tx and is configured to receive a backscatter signal from a tag 30 via receiver Rx.

[0078] Orchestration system 10 is configured for performing the energy efficiency optimization algorithm, assisted by processor 11 , in order to select a reader device 20D, 20E. To that end, reader devices 20D, 20E may provide information to the orchestration system 10 using communication modules 13 and 23.

[0079] The orchestration system 10 may be deployed at several places, for example as a centralized system in a telecommunications network, for example in a 3GPP standard compliant network. The centralized system may be a base station, such as a gNb, of such a network. The centralized system may also comprise a specific backscatter orchestration function in the network. In another embodiment, the orchestration system 10 may be a distributed system in a telecommunications network, wherein functionality of the orchestration system 10 is distributed amongst systems or functions in the network.

[0080] On the other hand, in one embodiment of the orchestration system 10, this system may be located more downstream towards the backscatter devices 30, for example by an integration of the orchestration system 10, at least in part, in one or more of the reader devices 20A, 20B, 20C, resp., 20D, 20E. In such an embodiment, the orchestrating system 10, as part of the reader device 20D, for example, may select itself as the most suitable reader device for backscatter communication with the backscatter device from an energy efficiency optimization perspective. For example, each reader device 20A, 20B, 20C may determine its potential energy efficiency, possibly taking into account time and size constraints, whereas the selection may be performed by a single reader device or orchestration system 10. Yet another embodiment resides in the orchestration system 30 comprising a stand-alone system connected to the reader devices 20D, 20E (as shown in FIG. 1 , when orchestration system 10 is not viewed as being integrated in a network). In FIG. 3, the orchestration system 10 is configured to orchestrate backscatter communication by selecting a first reader device 20D or a second reader device 20E for reading data from a tag 30. More reader devices 20, not shown, may be deployed near the tag 30 and may be considered by the orchestration system 10 for reading the data.

[0081] The orchestration system 10 is configured to select the first reader device 20D or the second reader device 20E by performing an energy efficiency optimization algorithm for the backscatter communication system 1 . The orchestration system 10 takes into account at least one of a first transmit power and a second transmit power of the excitation signal of the excitation source Txto trigger the backscatter communication to the first reader device 20D and the second reader device 20E, respectively, and a first data rate and a second data rate for transmitting the data from the backscatter device to the first reader device and the second reader device, respectively. The orchestration system 10 makes use, amongst other, of the insight that a maximum transmit power for an excitation source signal to trigger backscatter communication from a tag 30 is often unnecessary and energy savings can be obtained by tuning the transmit power appropriately. A reduced transmit power for the excitation signal slows down the data rate but may improve or optimize the overall efficiency of the data transfer. This may result in an energy consumption estimate for each reader device enabling a selection of the most energy efficient reader device.

[0082] The reader device 20D, 20E may, optionally, be configured to provide data from a tag 30 through backscatter communication for use with the orchestration system 10 as described herein. The reader device 20D, 20E is also configured to process a selection command from the orchestration system 10 to receive the data from the backscatter device. This feature of the reader device 20D, 20E enables the orchestration system 10 to select a reader device 20D based on energy efficiency optimization considerations. The processing of the reader device 20D, 20E, using processor 21 , for example, may include a trigger for transmitting an excitation signal (if the reader has an internal excitation source device) or instructing an external excitation source device to transmit the excitation signal with the applicable transmit power.

[0083] The orchestration system 10 may, for example, be configured to apply a neural network. Embodiments of using a neural network are explained in further detail with reference to FIG. 4 and / or by reference to FIGS. 5A-5C. The neural network may be used to determine the first transmit power and second transmit power of the excitation signal and / or the first data rate and second data rate. The neural network may determine one or more of these in dependence on at least channel characteristics for the backscatter communication from the tag 30 to the first reader device 20D and to the second reader device 20E to select one of these.

[0084] The application of a neural network, which may be run by processor 21 , facilitates more accurate estimation of the data rate and / or transmit power to be applied under practical circumstances by taking the channel characteristics into account. The neural network may provide a correlation between a desired throughput, or goodput, of the reader device 20D, 20E, which is a constraint for minimizing energy consumption, and the existing channel characteristics and the optimal transmit power of the excitation signal and / or optimal data rate. In one embodiment, the desired throughput, or one or more parameters representing such throughput, and recent channel characteristics are input in the neural network and the optimal transmit power of the excitation signal and optimal data rate result as output.

[0085] The orchestration system 10 may determine and / or apply a plurality of neural networks when different device types, that account for different data sets, apply. For example, when reader devices 20D, 20E are not of the same type, different channel metrics may apply that need to be obtained for each type of reader device. Also, available data rates may differ between different devices, i.e. between a reader device and a tag, for example. The data rate of the tag 30 may be adjustable. Alternatively, or in addition, the reader device may have a limited data rate at which it can read incoming data. One or both of these rates may be taken into account.

[0086] In one embodiment, at least one of the first transmit power of the excitation signal, the second transmit power of the excitation signal, the first data rate for data transfer from the tag 30 to the first reader device 20D and the second data rate for data transfer from the tag 30 to the second reader device 20E are adaptable. The orchestration system 10 is configured to control the at least one of the first transmit power, the second transmit power, the first data rate and the second data rate. Adjustability of one or more of these parameters provides more freedom for the orchestration system 10 to find optimum settings to save energy.

[0087] The orchestration system 10 may need to take one or more constraints into account when selecting a reader device 20D, 20E using the energy efficiency optimization algorithm. This may occur, for example, via the transmit power and / or data rate. Therefore, the first transmit power and the second transmit power and / or the first data rate and the second data rate may further be determined based on at least one of a time parameter Tp for transmitting the data and a size parameter Sp for the size of the data in the tag 30, for example stored in storage part 32. The time parameter T p may indicate when the data should be transmitted to meet a delivery demand, for example, of the operator of the tag 30, such as the operator of the data collecting entity DCE in FIG. 1 . The size parameter Sp may indicate the amount of data to be transferred and can be used to estimate the minimum throughput required to obtain the data from the backscatter device.

[0088] These constraints are advantageously taken into account by the orchestration system 10 to enable energy optimization while meeting data delivery requirements or demands, for example. Optionally, the time parameter Tp and size parameter Sp are used to determine a desired data throughput for the first reader device 20D and second reader device 20E. This may be input into the neural network, possibly in addition to the channel characteristics, to obtain the transmit power of the excitation signal and / or data rate. By not using the maximum transmit power for the excitation signal, it may generally take longer for the data to be transmitted to the reader device, but this may improve the overall energy efficiency for the backscatter communication system. On the other hand, it is not always the reader device with the maximum amount of time available to obtain the data from the backscatter device that is the most suitable reader device for energy efficient operation. The time parameter is thus a parameter to take into account for the orchestration. The first reader device 20D may be associated with first communication resources and the second reader device 20E may be associated with second communication resources, for example first and second time schedules, for receiving the data from the tag 30 at the first reader device 20D and the second reader device 20E, respectively. The time parameter Tp may thus be a time limit associated with the data. The orchestration system 10 may be configured to select the first reader device 20D or second reader device 20E taking account of meeting the time limit in view of the first time schedule and second time schedule and the size parameter Sp for the size of the data. The time limit may represent an ultimate time when the data needs to be transmitted to a reader device, an ultimate time for the data to be received by a reader device 20D, 20E, the ultimate time for the data to be received at the orchestration system 10, the ultimate time for the data to be received at a data collection entity DCE (FIG. 1), etc. The orchestration system 10 considers the time limit and size parameter for the size of the data in view of the time schedules to select the most appropriate reader device of the at least two reader devices 20D, 20E. More particularly, the orchestration system 10 may determine an available reading time from the time parameter Tp and the communication resources and obtain a desired throughput taking the data size represented by the size parameter Sp into account. The desired throughput may be an input parameter for the neural network as mentioned above. It should also be appreciated that the time schedules may also be determined by available time slots for the excitation source device for transmitting the excitation signal, processor load of either device in the backscatter communication system, etc.

[0089] It should further be appreciated that, for example from an energy consumption perspective, it is not sufficient for selection of the reader device 20D, 20E that it has sufficient time to obtain the data. The reader device 20D, 20E may, for example, have an optimal data rate itself and the channel characteristics may influence data transfer efficiency as well. As mentioned above, the data rate of the tag 30 may be adjustable. Alternatively, or in addition, the reader device may have a limited data rate at which it can read incoming data. One or both of these rates may be taken into account.

[0090] The orchestration system 10 may further be configured to obtain the time parameter Tp for transmitting the data using a request from a data service or data function connected to the orchestration system 10, such as the DCE in FIG. 1 . The time parameter Tp may also be obtained from the first reader device 20D and the second reader device 20E, using communication modules 13 and 23 from the orchestration system 10 and the reader devices 20D, 20E, respectively. The time parameter Tp may also be stored, for example in storage 12, as predetermined information of a required transmission time or expiration time of the data in the tag 30.

[0091] The orchestration system 10 may further be configured to obtain the size parameter Sp for the size of the data in the tag 30 based on, for example, an estimate based on previous data transmissions. The size parameter Sp representing the size of the data may also be fixed or approximately fixed, and therefore prestored in storage 12, for example.

[0092] Information gathering is facilitated in this manner and may be used to ensure that the data is collected at a suitable time by a suitable reader device. The information is further useful for selecting an energy-wise optimum reader device 20D, 20E under these constraints. The orchestration system 10 may further be configured to select the first reader device 20D or the second reader device 20E in accordance with a device type of these reader devices and / or the device type of the tag 30. By considering device types and / or device type combinations, selecting a suitable reader device 20D, 20E for backscatter communication by a tag 30 may be facilitated. Device types, or indications thereof, may refer to one or more feature sets for a reader device 20D, 20E or tag 30, including capabilities (e.g. maximum transmit power, step size for adjusting transmit power, if adjustment is possible), properties and / or location of these devices (e.g. battery power and location of a mobile reader device, or location of a fixed, continuously powered reader device). This information may be stored in storage 22 of the reader devices 20D, 20E and / or in storage part 32 of tag 30. Different neural networks may apply for different device types or device type combinations when determining optimal transmit power and optimal data rate.

[0093] In order for the orchestration system 10 to conduct the energy efficiency optimization analyses, reader devices 20D, 20E, may be configured, optionally in response to a request from the orchestration system 10, to provide information to the orchestration system 10 enabling the orchestration system 10 to determine at least one of a transmit power of the excitation signal of an excitation source to trigger the backscatter communication to the reader device and a data rate for transmitting the data from the backscatter device to the reader device. This information assists the orchestration system 10 in determining appropriate parameters for an energy efficient transmission of the data to the appropriate reader device. The information may include information regarding the tag 30 and / or information regarding the particular reader device 20D, 20E as mentioned above. Examples include, one or more of channel characteristics of a backscatter channel between the backscatter device and the reader; a device type of the backscatter device; a size parameter for the size of the data in the backscatter device; capabilities and / or features of the backscatter device, including, for example, adjustability of the data rate for sending the data through backscatter communication; location of the backscatter device etc. The reader device 20D, 20E is a suitable device to collect the further information because of its proximity to the tag 30. For collecting the information, the reader device 20D, 20E may use an internal excitation signal source, such as for reader device 20D in FIG. 3, to receive the further information or collect the information when the tag 30 is triggered from an external excitation source to send the information, as for reader device 20E in FIG. 3.

[0094] A reader device 20D, 20E may be configured to provide further information regarding the reader device to the orchestration system 10. This information may include one or more of communication resources of the reader device 20D, 20E, including a reader time schedule, for example; device type of the reader device; capabilities and / or features of the reader device and location of the reader device. This information may assist the orchestration system 10 in selecting the appropriate reader device 20D, 20E.

[0095] The o rch estrato r system 10 makes the total energy expenditure and resource management within the backscatter communication system 1 more efficient by allocating energy-efficient, yet protracted processes, to extract data from the tags 30 to the most suitable reader devices 20. A system, such as a base station, with valuable resources, may act as an orchestration system 10, to appoint other devices (reader device 20, for example), with available resources, to read data from the tag(s) 30 using backscatter communication, in the most energy-efficient way possible. Specifically, this energy-efficient approach reduces the energy required of the reader device 20 but at a lower throughput, i.e slower.

[0096] The orchestration system 10 allocates the protracted backscatter communication task to the optimal reader device 20, such that the total energy expenditure and resource management within a network is made more efficient.

[0097] The orchestrator system 10 may apply a neural network for selecting the most suitable reader device 20A, 20B, 20C resp. 20D, 20E using energy optimization. The orchestrating system uses the insight that the power of the excitation signal typically used to communicate with backscatter tag 30 is not efficiently used. However, more energy-efficient methods of communication require protracted processes, which can waste resources. Using protracted yet energy-efficient backscatter communication processes may desirably be carried out at the most suitable reader device 20 in order to substantially maximize network energy and resource efficiency. The advantage is that backscatter systems may now adopt a more energy-efficient backscatter communications method while maintaining efficient management of resources. In one embodiment, an optimized system that allows for energy-efficient communication to backscatter tags 30 is provided by offloading backscatter communication tasks within a network. The optimized system identifies the most suitable reader device 20, based on communication schedules and communication energy, to carry out protracted yet energy-efficient communication with backscatter tag 30s to maximize network resource efficiency.

[0098] The orchestration system 10 is configured such that the process of obtaining data from a tag 30 may be achieved at a lower throughput rate to minimize the energy expenditure of reader devices 20 at the cost of a longer duration. The selection of the most appropriate reader device 20, from this perspective for the backscatter communication task is dependent upon at least one of the baseline energy cost of communications to the tag 30 (i.e. the theoretical energy cost), the maximum time resources available to the reader device and / or the channel quality

[0099] FIG. 4 illustrates some steps for operating a backscatter communication system as disclosed herein.

[0100] The orchestrator system 10 may apply a neural network for selecting the most suitable reader device 20A, 20B, 20C resp. 20D, 20E using energy optimization. The application of the neural network may be preceded by initialization and training of the neural network, as shown by phase P1.

[0101] In this phase P1 , the orchestration system 10 is tasked with obtaining data from a tag 30 via backscatter communication, and the cooperating reader devices 20 are allocated. The orchestration system 10 gathers features of the reader devices 20 and the features of the tag 30. The orchestration system 10 uses the features of the reader device 20 and tag 30 to obtain the energy cost of communications between each reader device 20 and tag 30. The orchestration system 10 may then communicate with the reader device 20 with the lowest energy cost to begin querying the tag 30 using backscatter communications, under various channel conditions, to obtain the throughput and probing metrics, such as channel response for various transmit powers of the excitation signal. In phase P1 , the orchestration system 10 also trains a neural network using a training algorithm in which the probing metrics throughputs are entered as inputs. The optimal transmit power and optimal data rate for the tag 30 may then be used as labelled neural network outputs. The orchestration system 10 uses the optimal transmit power and optimal data rate of tag 30 as inputs to an energy efficiency optimizer algorithm. This algorithm is configured to determine the optimal efficiency of the reader device 20, where efficiency is a metric of throughput per unit of transmit power of the excitation signal. In one embodiment, the peak efficiency throughput may be derived.

[0102] Phase P2 pertains to the subsequent phase of reader selection.

[0103] In this phase P2, the orchestration system 10 uses the known time parameter Tp, for example a data deadline which will be used as an example here below, in an available reading time algorithm to obtain the available reading time for the reader devices 20 from the available reader device communication schedules, respectively.

[0104] The orchestration system 10 may also use the size parameter Sp, also referred to as the known data size here below, of the data in the tag 30 in a minimum throughput algorithm of a reader device 20 to obtain the desired throughput for reader device 20D and 20E, for example, from the available reading time for these reader devices 20D, 20E, respectively.

[0105] Using the trained neural network, the orchestration system 10 may be configured to input the desired throughput of the reader devices, calculated previously, along with some recent probing metrics, if available, to obtain the optimal data rate of tag 30 and corresponding optimal transmit power of the excitation signal for each reader device 20D, 20E.

[0106] In one embodiment, the orchestration system 10 may use a comparison algorithm to determine if the desired throughput of either reader device 20D, 20E is below the peak efficiency throughput, in which case the optimal transmit power and optimal data rate may be overwritten by the corresponding values that generate the peak efficiency throughput.

[0107] The orchestration system 10 may use the energy cost and the optimal transmit powers of the reader device in a device energy estimation algorithm to obtain an energy estimate for each reader device 20D, 20E. The orchestration system 10 may then use the available energy estimates of the reader devices 20D, 20E in a reader selection algorithm to allocate the reading task of a tag 30 to a selected reader device 20D, such that network energy and resources are used in the most efficient manner.

[0108] Phase P3 pertains to the phase of data retrieval from the tag 30 by the selected reader device 20D.

[0109] In this phase P3, the orchestration system 10 instructs the selected reader device 20D to perform an energy-optimized reading on the tag 30. The selected reader device 20D communicates via backscatter communication with the tag 30 using the optimal transmit power of the internal excitation source device for the transmission of the excitation signal and the optimal data rate for the tag 30 to obtain the data. This tag data is then communicated to the orchestration system 10 for delivery to the data collecting entity DCE, for example. The phases P1 , P2, P3 may be re-iterated through in order to update parameters, serve new reader devices 20 and allocate backscatter communications to the most appropriate device based on current network parameters.

[0110] FIGS. 5A-5C are detailed embodiments of the orchestration system 10 and reader devices 20 associated with the operating steps of phases P1-P3 of FIG. 4. FIG. 6 shows several details of some operating steps.

[0111] FIG. 5A is a schematic illustration of a backscatter communication system 1 comprising an orchestrating system 10, reader device 20D, 20E and a tag 30. Reader devices 20D, 20E have processor 21 , a storage 22 and a communication module 23.

[0112] Tag 30 has a processing part 31 , a storage part 32 and a combined power-harvesting and communication part 33 as described with reference to FIG. 2 for backscatter communication with reader devices 20D, 20E.

[0113] In particular, a tag 30 is configured for modulating an incident ambient signal, an excitation signal, with local data and (re)transmitting the modulated signal. The tag 30 may be configured to backscatter data at a certain rate, the tag data rate. The tag data rate may be variable and controlled via wirelessly communicated instructions, for example from the orchestration system 10 or from a reader device. Each tag 30 may possess information related to when the data of the tag 30 must be obtained (the “time parameter Tp). An example of the time parameter is a data deadline that may include a periodic interval in which the data on the tag 30 is obsolete or wiped due to memory constraints.

[0114] The tag 30 may be of a specific type, a device type, and the tag 30 may store this information in the storage part 32. The tag 30 may have a size parameter Sp, for example a known data size, for each communication interval. Examples of where a tag 30 may have a known data size include where the tag 30 is passive, and the data on the tag 30 is fixed; where the tag 30 reports specific sensor data of a similar size, e.g. humidity, temperature, Boolean values, or where the tag 30 is instructed to compress all data to a specific size.

[0115] The tag 30 may have a set of features describing the capabilities and properties of a tag 30 with respect to its communication and / or processing rates. Examples of these features may include the data rate of the tag and, where the tag 30 is able to transmit at different data rates, each rate of data is provided along with the commands to instruct the tag 30 to adjust its data rate. Other features may include the position of the tag 30, such as spatial coordinates or the relative location to other tag 30s and reader devices 20D, 20E. This may be determined via conventional localization methods such as triangulation, trilateration, radio frequency fingerprinting, etc.

[0116] The reader devices 20D, 20E may each have a controllable transmit power for transmitting the excitation signal, either through an internal excitation source device (as for reader device 20D) or via a connectable external excitation source device (as for reader device 20E). Each reader device 20D, 20E may have a description of upcoming communication tasks, for example a communication schedule. In one embodiment, each reader device 20D, 20E may have a metric used to quantify the value of its communication resources. Like for the tag 30, each reader device 20D, 20E may be of a specific device type. This information may be stored in the local storage 22. Each reader device 20D, 20E may further have a set of features describing the capabilities and properties of the reader device 20D, 20E with respect to its communication and processing rates, for example. Examples of these features include the reader device communication schedule, the position of the reader device 20D, 20E (such as spatial coordinates or the relative location to other reader devices and / r tags 30), communication capabilities of the reader devices, such as the maximum transmit power and, if enabled, the increments in which power may be increased. Further information may include the device type and energy restraints, such as the power source of the reader device and the current energy available

[0117] Orchestration system 10 is shown with a processor 11 having several modules, embodied in software and / or hardware. The orchestration system 10 may be a centralized node within a wireless sensor network, such as a base station or a temporarily designated reader device 20 within a typically decentralized network, for example.

[0118] In step S1 of FIG. 6, the orchestration system 10 is tasked with obtaining data from a set of tags 30 via backscatter communication and allocation of the reader devices 20D, 20E to obtain this data, using communication modules 13 and 23, for example. The orchestration system 10 is configured to gather these features of the reader devices 20D, 20E and the features of the tags 30 that may have stored these in storages 22 and 32, respectively.

[0119] The reader devices 20D, 20E may provide these feature upon request by the orchestration system 10. Alternatively, the orchestration system 10 may have access to a database of features of reader device 20D, 20E stored elsewhere, for example in the network. Likewise, the tag 30 may provide their features upon request by the orchestration system 10. Again, alternatively, the orchestration system 10 may have access to a database of features stored elsewhere, for example in the network.

[0120] The orchestration system 10 may further have obtained the time parameter Tp, such as data deadline information. This information may also be delivered from the tag 30 itself, for example, or this may be provided from an external application requiring fixed updates from the tag 30, for example, such as from the data collection entity DCE in FIG. 1.

[0121] The orchestration system 10 may store the information in storage 12.

[0122] Orchestration system 10 is configured with a baseline energy mapping algorithm, BEMA which determines the typical energy cost of communications between two devices using known parameters of the two devices and their efficiencies. The orchestration system 10 uses the obtained reader features and tag features within the baseline energy mapping algorithm BEMA in step S2. The BEMA is used to generate baseline energy cost of reader device 20D and 20E, describing the energy cost of communications between each reader and the tag. Examples of calculations or features considered within the baseline energy mapping algorithm may include the communication range of the two devices, given their spatial coordinate features provided in the reader device 20D, 20E, or tag 30, previous empirically obtained communication energy costs, the efficiencies of the transmitters and receivers of both devices, etc. In step S3, the orchestration system 10 signals the reader device 20D with the lowest baseline energy cost to begin querying the tag 30 using backscatter communications, under various channel conditions, to obtain the throughput and probing metrics of the return channel, which may include the channel frequency response and other numeric channel metrics for incremental transmit powers between zero power and maximum power. If tag 30 has a variable data rate, the data rate may be adjusted to achieve a maximum throughput. This may be achieved during conventional backscatter communications with the tag 30 as normally tasked.

[0123] Alternatively, also shown as step S3 in FIG. 6, probing metrics may be obtained by multiple reader devices 20D, 20E to maximize the variety of channel characteristics. The scheduling of reader device-to-tag communications may be selected at random to maximize the variety of channel characteristics.

[0124] If the reader devices 20D, 20E are not of the same device type, a reader device 20D, 20E of each device type may be instructed by the orchestration system 10 to collect the probing metrics. This results in a reader-device-type-specific set of probing metrics, i.e. probing metrics are obtained for each type of reader device 20D, 20E when communicating with the tag 30. Optionally, in order to accelerate the data-gathering process and improve the variety of channel conditions, readers of the same device type may work cooperatively to query the tag 30. The probing metrics obtained at various reader devices may be labelled with the device type of reader device 20D, 20E before being transmitted to the orchestration system 10 and stored in the orchestration system 10s’ local data storage device 12. If multiple reader devices 20D, 20E have obtained probing metrics with the same labelling, the probing metric sets may be merged.

[0125] If there are multiple tags 30s of different device types, a reader device 20D, 20E of each device type may be instructed by the orchestration system 10 to collect the probing metrics for each different type of tag 30. Probing metrics are obtained for each type of reader device 20D, 20E when communicating with each type of tag 30. Again, optionally, in order to accelerate the data-gathering process and improve the variety of channel conditions, reader devices of the same type may work cooperatively to query tags 30 of the same type. Labelling of probing metrics must also include the device type of the tag 30.

[0126] The reader device 20D, 20E tasked with querying the tag 30, returns the throughput, probing metrics, transmit powers and data rates, for example, to the orchestration system 10. The data may be stored in the orchestration system 10s’ data storage device 12.

[0127] The orchestration system 10 further contains a neural network training algorithm, NNTA which trains a neural network NN in step S4 using the probing metrics and desired throughput obtained in step S3 as inputs. The respective optimal transmit power and optimal data rate of tag 30 are then used as output labels to train the neural network.

[0128] The probing metrics include the channel frequency response and possibly other numeric channel metrics. Examples of such numeric channel metrics may include the received signal strength, the power-up delay of a tag 30, noise levels, etc. Such numeric channel metrics may be obtained at the reader device 20D, 20E during backscatter communications with a tag 30. The desired throughput is the measure of throughput obtained from a tag 30 using backscatter communications for a given transmit power and data rate of tag 30. The optimal transmit power is the lowest transmit power at the reader device 20D, 20E required to obtain a desired throughput from the tag 30 using backscatter communications and the optimal tag 30 data rate is the data rate of the tag 30, used in conjunction with the optimal transmit power, to obtain the desired goodput.

[0129] The neural network architecture may be monolithic or modular, as described by Huang et al. The result of the neural network training algorithm NNTA is that for a desired throughput and channel quality, as given by the probing metrics, the trained neural network provides the necessary optimal transmit power of the reader device 20D, 20E and the optimal data rate required for tag 30. i.e. it is possible to determine the optimal transmit power and data rate required to achieve a desired goodput given certain probing metrics. Where a tag 30 has only a single data rate, the optimal tag data rate is fixed to the value of the data rate of the tag 30.

[0130] If there may be multiple sets of probing metrics related to individual pairings of reader device types, a separate neural network may be trained using this data set to obtain the optimal transmit power and optimal data rate for a tag of the specific reader device type. Likewise, if there are multiple tags of different device types, a separate neural network may be trained using this data set to obtain the optimal transmit power and optimal tag data rate of the specific reader and tag device type.

[0131] The orchestration system 10 further comprises an energy efficiency optimizer algorithm, EEOA. The orchestration system 10 uses the optimal transmit power and optimal data rate of tag 30 as inputs to the EEOA, which is designed to determine the optimal reader efficiency in step S5, where efficiency is a metric of throughput per unit of transmit power. Subsequently, the peak efficiency throughput may be derived. The desired throughput per unit of transmit power is used to determine the reader efficiency, where an optimal transmitter efficiency is observed, the respective level of throughput is noted as the peak efficiency throughput. Preferably, if the desired throughput is less than the peak efficiency throughput, the system increases the desired throughput to the peak efficiency throughput, for increased reader efficiency. Where a tag 30 has only a single tag data rate, the optimal tag data rate is fixed to the value of the tag data rate.

[0132] If there are multiple sets of probing metrics related to individual pairings of reader device types, a separate energy efficiency optimizer algorithm, EEOA, may be computed using this dataset to obtain the transmitter efficiency and peak efficiency throughput of the specific reader device type. If there are multiple tags of different device types, there may be multiple sets of probing metrics related to individual pairings of reader device type and tag device type. A separate energy efficiency optimizer algorithm may be trained using this data set to obtain the transmitter efficiency and peak efficiency throughput of the specific reader and tag device type.

[0133] After step S5, phase P1 of initializing the orchestration system and training the neural network may be considered as complete. It is to be noted that these steps may be taken again if needed.

[0134] Phase P2 of selecting the energy-wise most appropriate reader device 20D, 20E may start with step S6. FIG. 5B is a schematic embodiment of the orchestration system 10 for phase P2. To that end, the orchestration system 10 may have an available reading time algorithm, ARTA, to obtain an available reading time for the reader devices 20D, 20E. More specifically, ARTA may determine the available time of a reader device 20D, 20E, given the communication schedule and the data deadline for the data of the tag 30. i.e. how much free time does the reader device 20D, 20E have available, for backscatter communications, before the tag 30 data deadline expires. The available time of the reader device may factor in the known communication time required to relay information back to the orchestration system 10, given the compression / modulation / communication capabilities and the known size of the data through size parameter Sp.

[0135] For example, the data deadline for the tag 30 describes when the orchestration system 10 must obtain the tag data due to requests from connected services or functions. Examples of how this may be obtained may include the following cases. The tag 30 may have a periodic transmission window that the orchestration system 10 learns or knows. The tag data may, alternatively or in addition, be requested at specific periodic or systematic intervals from a connected service or function. Also, a service or system may have recently requested data from the tag 30, and as such, the orchestration system 10 determines the tag data deadline given the level of urgency required by the system or service. It is noted that some services, such as healthcare, may be more time critical as opposed to other services, such as warehouse asset tracking.

[0136] The orchestration system 10 may periodically query the reader devices 20D, 20E for updated reader communication schedules. Where the orchestration system 10 is to collect data from multiple tags 30, the available reading time may be determined for each reader device and tag. This process may be computed asynchronously, given the possible asynchronous sampling rate or request of each tag’s data.

[0137] Alternatively, the orchestration system 10 may distribute the data deadline of the tag(s) to the reader devices in which they locally calculate their own available reading time. This may then be transmitted to the orchestration system 10 for processing or, alternatively, be used in step S7 before it is shared with the orchestration system 10.

[0138] In step S7 a minimum reader throughput algorithm, MRTA, is used to obtain the desired throughputs of reader devices 20D, 20E. MRTA may particularly determine the lowest possible throughput given the known data size from storage 12 and the available reading time output from step S6. For example, a reader device 20D may have one second of available reading time to obtain 100kb of data; therefore, the desired throughput is at least 100kbps.

[0139] For example, the known data size may represent the data size of the expected data packet. Examples of how this is obtained may include that the orchestration system 10 may be configured to estimate this based on the sizes of previous data packets from the tag. In one example, the orchestration system 10 may make an overestimate to ensure ample buffer space. Alternatively, the tag 30 may have a fixed data packet size, known to the orchestration system.10 or the tag 30 may be instructed by the orchestration system 10 to fix data packets to a pre-determined amount. As in step S6, the orchestration system 10 may instead distribute the tags’ known data size to the reader devices in which they locally calculate their own desired throughput. This may then be transmitted to the orchestrator.

[0140] In step S8, the orchestration system 10 uses the neural network NN for assisting in the selection of the reader device 20D, 20E. The orchestration system 10 inputs the desired throughput of the reader devices 20D, 20E of the previous step S7 along with recent probing metrics (stored in storage 12, for example) to obtain the optimal data rate of the tag and corresponding optimal transmit power for the excitation signal for each reader device 20D, 20E to optimize the energy efficiency. Recent probing metrics may be obtained, for example, by the orchestrating system 10 using the most recently obtained probing metrics or requiring reader devices 20D, 20E to provide updated probing metrics by individually querying the tag 30 or estimating the relevant probing metrics from recent communications. The orchestrating system 10 may estimate probing metrics based on a digital twin or virtual channel estimation system.

[0141] Again, if the reader’s device types are not of the same device type, individual reader device type neural networks and relevant parameters may be obtained as described above for this case. In this case, the relevant device type trained neural network and energy efficiency optimizing parameters are to be used for estimating the optimal data rate of the tag 30 and corresponding optimal transmit power for specific reader device type communications to the tag 30. If there are multiple tags 30, the method step is repeated for each tag 30. If the tag device types are not of the same device type, individual reader device-tag device type neural networks and relevant parameters may be obtained as described above. In this case, the relevant device type trained neural network and energy efficiency optimizing parameters are to be used for estimating the optimal tag data rate and corresponding optimal transmit power for reader communications to the tag.

[0142] In a distributed fashion, the orchestration system may share the trained neural network with the reader devices 20D, 20E to calculate their own optimal tag data rate and corresponding optimal transmit power. This may be shared with the orchestrating system 10 for processing. Alternatively, this may be used in the following method step S9, and a later dataset is shared with the orchestrating system 10.

[0143] In step S9 of FIG. 6, orchestration system 10 may run a comparison algorithm, CA, which determines if the desired throughput of a reader device 20D, 20E is below the peak efficiency throughput determined from the energy efficiency optimizer algorithm, EEOA, in which case the optimal transmit power and optimal data rate may be overwritten by the corresponding values that generate the peak efficiency throughput.

[0144] Orchestration system 10 is configured to run a device energy estimation algorithm, DEEA, in step S10 which determines an estimate of the overall energy use (an energy estimate) for backscatter communications given the baseline energy cost and the optimal transmit power. The energy estimate may be calculated by directly summing the baseline energy cost and the optimal transmit power. Where a reader device 20D, 20E may have a priority weighting metric, this may be used to increase the energy estimate value such that the likelihood of the device being used for the reading task is minimized.

[0145] In particular, the orchestration system 10 uses the reader’s baseline energy costs and reader’s optimal transmit powers within the device energy estimation algorithm DEEA to obtain an energy estimate for reader device 20D and for reader device 20E. The baseline energy cost and optimal transmit power may be combined to represent the estimated energy expenditure for low-power backscatter communications with the tag 30. An example of how this may be achieved is through the simple addition of the two values.

[0146] If a reader device, such as reader device 20D, has additional capabilities that make its communications a highly valuable resource, such as beamforming, high connectivity, sensing abilities, advanced modulation techniques, etc., the reader device may have a priority weighting metric. This may be combined with the energy estimate to decrease the potential usage of the device for the reading task. The orchestration system 10 may obtain the priority weighting metric of connected readers during information gathering as described above or alternatively obtain this from the features of the reader device(s) stored in storage 12. Where there are multiple tags 30, the method step is repeated for each tag-to-reader device combination.

[0147] In a distributed fashion, the orchestration system 10 may share the relevant baseline energy cost and optimal transmit power parameters with the reader devices in order to calculate their own energy estimate locally. Alternatively, if the reader devices already have their own baseline energy cost and optimal transmit power values, the orchestration system 10 may directly request an energy cost calculation. This is then shared to the orchestration system 10 for processing.

[0148] As a final step of phase P2, reader selection is provided for by using a reader allocation algorithm, RAA, in step S11 . The RAA uses the energy estimate for each reader device 20D, 20E to determine which reader device 20D, 20E should use backscatter communication to communicate with the tag 30 to maximize energy and resource efficiency for the backscatter communication system 1 . The selected reader device 20D may be chosen by selecting the device with the lowest energy estimate. If there are multiple tags 30, the reading allocation algorithm RAA may consider allocating reader devices such that overall network energy is minimized. This may be achieved by ensuring the summation of the energy estimate values of all selected devices is minimized.

[0149] Phase P3 pertains to the retrieval of data by the selected reader device 20D from the tag 30. FIG. 5C provides a detailed embodiment of the orchestration device 10, reader device 20D and tag 30 for this purpose.

[0150] The orchestration system 10 is configured to instruct the selected reader device 20D to perform an energy-optimized reading on the tag 30. This is shown in step S12 in FIG. 6.

[0151] The communications to the selected reader device 20D may include the details of the tag 30 from which the selected reader device 20D is to obtain data via backscatter communications and a schedule of when the data must be obtained and / or shared with the orchestration system 10. If the data on the tag 30 is encrypted, the orchestration system 10 may communicate to the tag 30 to approve the communication of data between the tag 30 and reader device 20D. Alternatively, the reader device 20D may obtain encrypted data for the orchestration system 10 and pass this on directly.

[0152] The orchestration system 10 may also provide a copy to reader device 20D (and 20E) for online learning.

[0153] In step S13, the selected reader device 20D communicates with tag 30 via backscatter communication using the determined optimal transmit power for the excitation signal and optimal data rate for the tag 30 as determined in phase P2.

[0154] If the tag 30 has a variable and controllable data rate, the selected reader device 20D communicates with the tag 30 to adjust its data rate to the optimal data rate for the tag 30 for low- power communications.

[0155] The backscatter communications may continue to obtain real-time probing metrics. These are used to update the transmit power of the selected reader device 20D and optimal data rate of tag 30 to ensure the desired throughput is met.

[0156] Online learning may be used by the reader device 20D to refine the trained neural network with real-time backscatter channel measurements when the current backscatter throughput deviates from the required throughput.

[0157] In step S14, the selected reader device 20D obtained the data from the tag 30 through backscatter communications. This data is then communicated to the orchestration system 10. The obtained tag data may be stored on the storage 22 of the selected reader device 20D. The data may be compressed by the selected reader device 20D to be transmitted in a more efficient manner to the orchestration system 10. Any changes to the trained neural network from online learning may be shared and used to update the neural network NN of the orchestration system 10.

[0158] The steps within or between phases P1-P3 may be reiterated in order to update parameters, to serve new reader devices 20 and / or tag devices 30 and allocate backscatter communications to the most appropriate device reader device based on current network parameters. This is shown by the returning arrows in FIG. 6. It should be noted that the process may return to other steps than shown.

[0159] As mentioned above, the orchestration system may be configured for backscatter communication with a tag 30 by acting as a reader device 20. In such an embodiment, the capabilities and functions of the orchestration system 10 and reader device 20 may be combined and redundant modules and functions may be removed as will be appreciated by the skilled person.

[0160] Where the orchestration system 10 itself is capable of backscatter communications the orchestration system 10 may store a set of features, which describe the energy and communication capabilities of the device. Examples of such features may include the position of the orchestration system 10, such as spatial coordinates or the relative location to other devices, such as other reader devices 20 and tags 30. This may be determined via conventional localization methods such as triangulation, trilateration, radio frequency fingerprinting, etc. Communication capabilities of the orchestration system 10 may now include its maximum transmit power and the increments in which power may be increased. Also, an orchestration system device type may be registered as well as energy factors of the orchestration system 10, such as the power source (e.g. battery powered, energy harvesting or mains supply) and the current energy available. The orchestration system 10 may have a description of its upcoming communication tasks.

[0161] The orchestration system 10 serving as a reader device may also have a priority metric used to quantify the value of its communication resources. For example, if the orchestration system 10 is a base station with many devices to serve and advanced modulation techniques, it may have a higher priority metric than a low-power device. This value may be a given value dictated by the system owner or may be generated using the features of the orchestration system 10 as quantitative metrics for the prioritization of resources. This value may be correlated to a network hierarchy of devices.

[0162] In view of the method steps of FIG. 6, similar steps are taken for an orchestration system 10 being integrated in a reader device 20. The orchestration system 10 may replace reader device 20D or 20E and their actions and data with its own equivalent actions or data. As such, where data of reader device 20D is shared with the orchestration system 10, or the orchestration system 10 gives instructions to a reader device, no such transmission is required when the orchestration system 10 and the given reader device 20 are the same. For example, if the orchestration system 10 is selected as the selected reader device, no instructions need to leave the orchestration system 10.

[0163] Another embodiment pertains to a reader device 20 not having an integrated excitation source device, as is the case for device 20E in FIG. 3. In such an embodiment, the excitation source device Tx is added as a system component.

[0164] The baseline energy mapping algorithm BEMA, shown in FIG. 5A, in the orchestration system 10 may estimate the total energy of backscatter communications between any source-tag-reader device combination as opposed to only estimating the energy of backscatter communications between a reader device 20 and tag 30. Also, the available reading time algorithm ARTA, shown in FIG. 5B, originally considers the available time that the reader device 20 has to perform the backscatter data collection (reading) task. With the addition of the excitation source device Tx, ARTA may now consider the mutually available time between the source device and the reader device 20 since they are both required to perform backscatter communications on the tag 30. The comparison algorithm CA and reading allocation algorithm RAA may also consider the throughput and energy of a source-reader device 20 pair, respectively. The energy efficiency optimizing algorithm EEOA may also take source device, reader device and tag into account

[0165] In particular, the transmit power of the excitation source device Tx may be controllable and information on the communication schedule of the excitation source device may be taken into account by the orchestration system 10. Similar information of the excitation source device may play a role, such as device type, priority metric, source features describing capabilities and properties of the source device with respect to its communication and processing. Examples of the such features include the source communication schedule, the position of the source device , such as spatial coordinates or the relative location to other devices (this may be determined via conventional localization methods such as triangulation, trilateration, radio frequency fingerprinting), communication capabilities of the source, including the maximum transmit power and the increments in which power may be changed, the source device type and energy restraints, such as the power source and current available energy.

[0166] In the method as shown in FIG. 6, the orchestration system 10 in step S1 may also gather the source features along with the reader device 20 and tag 30 features. In step S2, the orchestration system 10 additionally considers the source features within the baseline energy mapping algorithm BEMA to compute the baseline energy costs of backscatter communications for each possible source- tag-reader device communication channel. In step S3, the probing metrics are gathered from backscatter communications using the source-tag-reader device combination with the lowest estimated baseline energy cost.

[0167] In general, where the backscatter communication system 1 contains multiple readers, sources, or tags that are each not of the same device type, probing metrics may be obtained for each combination of devices, and its various device types. The orchestration system 10 may instruct a device of each device type to collect probing metrics, i.e. where there may be two different types of source devices, a different set of backscatter communications probing metrics may be obtained for both source device types.

[0168] In step S4, the transmit parameters (optimal data rate and optimal transmit power) are related to the excitation source device since the source transmits the excitation signal for backscatter communications. In step S5, the efficiency parameters are related to the transmit power of the excitation source device since this device transmits the excitation signal for backscatter communications. This would conclude phase P1 for a reader device with an external excitation source device.

[0169] For phase P2 of selecting a reader device, in step S6, the available reading time is related to the mutually available time between the source device and reader, in relation to the time parameter Tp of the tag 30, such as the data deadline. Therefore, the communication schedules of both the excitation source device and the reader device 20 are considered in the available reading time algorithm ARTA. Within steps 7-11 ., the communication parameters described are related to a source device-reader device pair as opposed to the reader device alone. Within step S11 ., the selected devices describe both the source device and reader device whose backscatter communications are expected to be most energy and resource-efficient.

[0170] For phase P3, in step S12, the orchestration system 10 may share information relating to the other device in the source-reader device pair required to establish communications between the source device and reader device. This enables either the source device or reader device to establish a feedback channel used during backscatter communications, as shown in FIG. 3. Within step 13., using a feedback channel between the source device Tx and reader device 20, the reader device 20 may relay real-time probing metrics or transmission power updates to the source device in order to maintain optimal efficiency. The reader device 20 may transmit raw probing metrics and allow the source device to use the trained neural network to determine its own optimal transmit power. Alternatively, the reader device 20 may locally compute the source transmit power using the probing metrics and relay the output to the source. FIG. 7 depicts a block diagram illustrating an exemplary processing system according to a disclosed embodiment, e.g. an orchestration system 10 or reader device 20 for use in a backscatter communication system 1 . As shown in FIG. 7, the processing system 70 may include at least one processor 71 coupled to memory elements 72 through a system bus 73. As such, the processing system may store program code within memory elements 72. Further, the processor 71 may execute the program code accessed from the memory elements 72 via a system bus 73. In one aspect, the processing system may be implemented as a computer system that is suitable for storing and / or executing program code. It should be appreciated, however, that the processing system 70 may be implemented in the form of any system including a processor and a memory that is capable of performing the functions described within this specification.

[0171] The memory elements 72 may include one or more physical memory devices such as, for example, local memory 74 and one or more bulk storage devices 75. The local memory may refer to random access memory or other non-persistent memory device(s) generally used during actual execution of the program code. A bulk storage device may be implemented as a hard drive or other persistent data storage device. The processing system 70 may also include one or more cache memories (not shown) that provide temporary storage of at least some program code in order to reduce the number of times program code must be retrieved from the bulk storage device 75 during execution.

[0172] Input / output (I / O) devices depicted as an input device 76 and an output device 77 optionally can be coupled to the processing system. Examples of input devices may include, but are not limited to, a space access 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 a display, speakers, or the like. Input and / or output devices may be coupled to the processing system either directly or through intervening I / O controllers.

[0173] In an embodiment, the input and the output devices may be implemented as a combined input / output device (illustrated in FIG. 7 with a dashed line surrounding the input device 76 and the output device 77). An example of such a combined device is a touch sensitive display, also sometimes referred to as a “touch screen display” or simply “touch screen” that may be provided with the UE. In such an embodiment, input to the device may be provided by a movement of a physical object, such as e.g. a stylus or a finger of a person, on or near the touch screen display.

[0174] A network adapter 78 may also be coupled to the processing system to enable it to become coupled to other systems, computer systems, remote network devices, and / or remote storage devices through intervening private or public networks. The network adapter may comprise a data receiver for receiving data that is transmitted by said systems, devices and / or networks to the processing system 70, and a data transmitter for transmitting data from the processing system 70 to said systems, devices and / or networks. Modems, cable modems, and Ethernet cards are examples of different types of network adapter that may be used with the processing system 70.

[0175] As pictured in FIG. 7, the memory elements 72 may store an application 79. In various embodiments, the application 79 may be stored in the local memory 74, the one or more bulk storage devices 75, or apart from the local memory and the bulk storage devices. It should be appreciated that the processing system 70 may further execute an operating system (not shown in FIG. 7) that can facilitate execution of the application 79. The application 79, being implemented in the form of executable program code, can be executed by the processing system 70, e.g., by the processor 71 . Responsive to executing the application, the processing system 70 may be configured to perform one or more operations or method steps described herein.

[0176] In one aspect of the present invention, one or more components of the orchestrating system as disclosed herein may represent processing system 60 as described herein.

[0177] Various embodiments of the invention may be implemented as a program product for use with a computer system, where the program(s) of the program product define functions of the embodiments (including the methods described herein). In one embodiment, the program(s) can be contained on a variety of non-transitory computer-readable storage media, where, as used herein, the expression “non-transitory computer readable storage media” comprises all computer-readable media, with the sole exception being a transitory, propagating signal. In another embodiment, the program(s) can be contained on a variety of transitory computer-readable storage media. Illustrative computer-readable storage media include, but are not limited to: (i) non-writable storage media (e.g., read-only memory devices within a computer such as CD-ROM disks readable by a CD-ROM drive, ROM chips or any type of solid-state non-volatile semiconductor memory) on which information is permanently stored; and (ii) writable storage media (e.g., flash memory, floppy disks within a diskette drive or hard-disk drive or any type of solid-state random-access semiconductor memory) on which alterable information is stored. The computer program may be run on the processor 61 described herein.

[0178] 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 "th" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprise" and / or "comprising” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0179] The corresponding structures, materials, acts, and equivalents of all means or step plus function elements in the claims below are intended to include any structure, material, or act for performing the function in combination with other claimed elements as specifically claimed. The description of embodiments of the present invention has been presented for purposes of illustration but is not intended to be exhaustive or limited to the implementations in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope of the claims. The embodiments were chosen and described in order to best explain the principles and some practical applications of the present invention, and to enable others of ordinary skill in the art to understand the present invention for various embodiments with various modifications as are suited to the particular use contemplated.

Claims

CLAIMS1 . An orchestration system for orchestrating backscatter communication in a backscatter communication system comprising at least one backscatter device storing data to be read through the backscatter communication triggered by an excitation signal from an excitation source, wherein the backscatter communication system comprises at least: a first reader device for reading the data from the backscatter device; a second reader device for reading the data from the backscatter device; wherein the orchestration system is configured to select the first reader device or the second reader device to read the data from the backscatter device by performing an energy efficiency optimization algorithm for the backscatter communication system taking into account: a first transmit power and a second transmit power of the excitation signal of the excitation source to trigger the backscatter communication to the first reader device and the second reader device, respectively; and a first data rate and a second data rate for transmitting the data from the backscatter device to the first reader device and the second reader device, respectively.

2. The orchestration system according to claim 1 , wherein the orchestration system is configured to apply a neural network to determine the first transmit power and second transmit power and / or the first data rate and second data rate in dependence on at least channel characteristics for the backscatter communication from the backscatter device to the first reader device and to the second reader device to select the first reader device or the second reader device.

3. The orchestration system according to claim 1 or claim 2, wherein at least one of the first transmit power, the second transmit power, the first data rate and the second data rate are adaptable, and wherein the orchestration system is configured to control the at least one of the first transmit power, the second transmit power, the first data rate and the second data rate.

4. The orchestration system according to one or more of the preceding claims, wherein the first transmit power and the second transmit power and / or the first data rate and the second data rate are further determined based on at least one of: a time parameter for transmitting the data; and a size parameter for the size of the data in the backscatter device, wherein the time parameter and size parameter are optionally used to determine a desired data throughput for the first reader device and second reader device in the orchestration system.

5. The orchestration system according to claim 4, wherein the first reader device is associated with first communication resources and the second reader device is associated with second communication resources, wherein the first and second communication resources comprise a first time schedule and a second time schedule for receiving the data at the first reader device and the second reader device, respectively, wherein the time parameter is a time limit associated with the data, and wherein the orchestration system is configured to select the first reader device or second reader device taking account of meeting the time limit in view of the first time schedule and second time schedule and the size parameter for the size of the data.

6. The orchestration system according to claim 4 or 5, wherein the orchestration system is configured to obtain the time parameter for transmitting the data through at least one of the following: a request from a data service or data function connected to the orchestration system; information obtained from or in the first reader device and the second reader device; predetermined information of a required transmission time or expiration time of the data in the backscatter device.

7. The orchestration system according to one or more of the preceding claims 4-6, wherein the orchestration system is configured to obtain the size parameter for the size of the data in the backscatter device through at least one of the following: an estimate based on previous data transmissions; the size parameter for the size of the data is fixed or approximately fixed.

8. The orchestration system according to one or more of the preceding claims, wherein the orchestration system is further configured to select the first reader device or the second reader device in accordance with a device type for at least one of the first reader device and the second reader device, and the backscatter device.

9. The orchestration system according to one or more of the preceding claims, wherein the orchestration system is configured to obtain information from at least one of the first reader device, the second reader device and the backscatter device, wherein the information comprises at least one of the following: device capabilities device properties device locationdevice type for at least one of the first reader device, the second reader device and the backscatter device for use in the energy efficiency optimization algorithm.

10. The orchestration system according to one or more of the preceding claims, wherein the orchestration system is at least one of: a centralized system in a telecommunications network; a distributed system in a telecommunications network; a system integrated, at least in part, in the first reader device and / or the second reader device; a stand-alone system connectable to the first reader device and a second reader device.

11. A reader device configured to provide data from a backscatter device through backscatter communication for use with the orchestration system according to one or more of the preceding claims, wherein the reader device is configured to process a selection command from the orchestration system to receive the data from the backscatter device.

12. The reader device according to claim 11 , wherein the reader device is configured, optionally in response to a request from the orchestration system, to provide information to the orchestration system enabling the orchestration system to determine at least one of a transmit power of the excitation signal of an excitation source to trigger the backscatter communication to the reader device and a data rate for transmitting the data from the backscatter device to the reader device.

13. The reader device according to claim 12, wherein the reader device is further configured to provide further information regarding the backscatter device to the orchestration system, including one or more of: channel characteristics of a backscatter channel between the backscatter device and the reader device; device type of the backscatter device; a size parameter for the size of the data in the backscatter device capabilities and / or features of the backscatter device, including, for example, adjustability of the data rate for sending the data through backscatter communication; location of the backscatter device.

14. The reader device according to claim 12 or 13, wherein the reader device is further configured to provide further information regarding the reader device to the orchestration system, including one or more of: communication resources of the reader device, including a reader device time schedule, for example; device type of the reader device; capabilities and / or features of the reader device; location of the reader device.

15. The reader device according to one or more of the preceding claims 11-14, wherein the reader device includes at least a part of the orchestration system according to one or more of the claims 1-10 and is selectable by the orchestration system.

16. The reader device according to one or more of the preceding claims 11-15, wherein the reader device comprises at least one of: an integrated excitation source for transmitting an excitation signal to trigger backscatter communication from the backscatter device; a feedback connection to an external excitation source for transmitting an excitation signal to trigger backscatter communication from the backscatter device, wherein the reader device is, optionally, configured to receive a control signal from the orchestration system to control adjustment of the transmit power for the integrated, resp. external, excitation source device.

Images