A reconfigurable intelligent surfaces controller mechanism for geofencing

Abstract

Systems and methods are provided for geofencing using one or more reconfigurable intelligent surfaces (RISs) (and / or smart surfaces and / or smart wireless repeaters) to create a dynamic virtual geographic boundary for wireless communication services. The properties of an RIS can be tuned to change the propagation environment to support specific wireless communication goals. Embodiments provide a novel RIS controller mechanism that allows an RIS to dynamically shield a network service area of interest against outer wireless communication and / or provide enhanced wireless communication coverage in the area of interest (if desired). The controller mechanism can leverage RISs to manipulate beam management procedures and prevent or inhibit initial access.

Description

[0001] DESCRIPTION

[0002] A RECONFIGURABLE INTELLIGENT SURFACES CONTROLLER MECHANISM FOR GEOFENCING

[0003] CROSS-REFERENCE TO RELATED APPLICATION

[0004] This application claims the benefit of U.S. Provisional Application Serial No. 63 / 698,897, filed September 25, 2024, the disclosure of which is hereby incorporated by reference in its entirety, including all figures, tables, and drawings.

[0005] GOVERNMENT SUPPORT

[0006] This invention was made with government support under 2318798, 2326599, and 2412872 awarded by National Science Foundation. The government has certain rights in the invention.

[0007] BACKGROUND

[0008] Beam management is key to wireless systems that leverage highly directional transmission links, such as 5G and 6G mmWave, to acquire and maintain beam alignment between base stations (BSs) and user equipments (UEs). Beam management procedures involve the periodic transmission of reference signals over different beam directions to help determine the best beam alignment for communication (a procedure also known as beam sweeping).

[0009] BRIEF SUMMARY

[0010] Embodiments of the subject invention provide novel and advantageous systems and methods for geofencing using one or more smart wireless devices (e.g., reconfigurable intelligent surfaces (RISs), smart surfaces, and / or smart wireless repeaters) to create a dynamic virtual geographic boundary for wireless communication services, positioning, ranging, and / or sensing. RISs are programmable wireless relays whose properties (e.g., reflection, refraction, absorption) can be controlled dynamically. The properties of an RIS can be tuned to change the propagation environment to support specific wireless communication goals (e.g., extend network coverage). Embodiments provide a novel smart wireless device controller mechanism that allows a smart wireless device to dynamically

[0011] J:\VTI\103XClPCT\Application\Application -asfiled.doc\ke shield a network service area of interest (e.g., an indoor conference room) against external wireless communication and / or provide enhanced wireless communication coverage in the area of interest (if desired). The controller mechanism can leverage smart wireless devices to manipulate beam management procedures and prevent or inhibit initial access (procedures used to establish connections between transmitters and receivers in beamforming communication) and / or communications subsequent to the initial access. Turning off the controller can promptly re-enable wireless communication services within the network service area of interest (or return the service level to baseline).

[0012] In an embodiment, a system for generating a dynamic virtual geographic boundary for wireless services (e.g., communication services, positioning services, ranging services, and / or sensing services) can comprise: at least one smart wireless device (e.g., an RIS, a smart surface, and / or a smart wireless repeater) configured to absorb, refract, and / or reflect incident wireless signals (e.g., wireless communication signals, wireless positioning signals, wireless ranging signals, and / or wireless sensing signals); a processor; and a machine-readable medium in operable communication with the processor and having instructions stored thereon that, when executed by the processor, perform the following steps: i) smartly adjusts properties of the at least one smart wireless device to induce a first communication end point (e.g., a transmitter, sensor, or ranging device) and a second communication endpoint (e.g., a receiver) to establish connectivity via the at least one smart wireless device; and ii) manipulate the properties of the at least one smart wireless device during data transmission between the first communication end point and the second communication end point. The manipulating of the properties of the at least one smart wireless device can comprise: ii-a) setting the properties of the at least one smart wireless device to absorb (and / or not refract / reflect, and / or to refract / reflect at a desired phase) the incident wireless signals to hinder signals from propagating to the second communication endpoint; and / or ii-b) setting the properties of the at least one smart wireless device to reflect the incident wireless signals to enhance signals propagating to the second communication endpoint. The at least one smart device can comprise at least one RIS. Step i) and / or step ii) (i.e., the RIS controller mechanism) can comprise, for example, performing a static sequence algorithm (e.g., Algorithm 1 (as shown in Figure 7 A)) with or without direction optimization. Step i) and / or step ii) can comprise performing an adaptive sequence algorithm (e.g., Algorithm 2 (as shown in Figure 7B)) with or without direction optimization. After step ii), the signals

[0013] J:\VTI\103XClPCT\Application\Application -asfiled.doc / ke propagating to the second communication endpoint can have a (weakened) received signal strength of, for example, no more than -100 decibels-milliwatts (dBm). The at least one smart wireless device can be positioned to provide a stronger path for communication between the first communication endpoint and the second communication endpoint than the direct path between the first communication endpoint and the second communication endpoint (without the at least one smart device being present). In some embodiments, the second communication endpoint can be located within a building, such as within a room (e.g., a conference room), and the at least one smart wireless device can be disposed near (e.g., within 2 meters (m) of) a window of the room / building. The system can further comprise a physical device, which can comprise the processor and the machine-readable medium. The device can further comprise a display allowing a user to see results of control inputs. Alternatively, the processor and / or the machine-readable medium can be part of the at least one smart wireless device.

[0014] In another embodiment, a method for generating a dynamic virtual geographic boundary for wireless services (e.g., communication services, positioning services, ranging services, and / or sensing services) can comprise: i) smartly adjusting (e.g., by a processor) properties of at least one smart wireless device (e.g., an RIS, a smart surface, and / or a smart wireless repeater) to induce a first communication end point (e.g., a transmitter, sensor, or ranging device) and a second communication end point (e.g., a receiver) to establish connectivity via the at least one smart wireless device, wherein the at least one smart wireless device is configured to absorb, refract, and / or reflect incident wireless signals (e.g., wireless communication signals, wireless positioning signals, wireless ranging signals, and / or wireless sensing signals); and ii) manipulating the properties of the at least one smart wireless device during data transmission between the first communication end point and the second communication end point. The manipulating of the properties of the at least one smart wireless device can comprise: ii-a) setting the properties of the at least one smart wireless device to absorb (and / or not refract / reflect, and / or to refract / reflect at a desired phase) the incident wireless signals to hinder signals from propagating to the second communication endpoint; and / or ii-b) setting the properties of the at least one smart wireless device to reflect the incident wireless signals to enhance signals propagating to the second communication endpoint. The at least one smart device can comprise at least one RIS. Step i) and / or step ii) (i.e., the RIS controller mechanism) can comprise, for example, performing a static sequence

[0015] J:\VTI\103XClPCT\Application\Application -asfiled.doc / ke algorithm (e.g., Algorithm 1 (as shown in Figure 7 A)) with or without direction optimization. Step i) and / or step ii) can comprise performing an adaptive sequence algorithm (e.g., Algorithm 2 (as shown in Figure 7B)) with or without direction optimization. After step ii), the signals propagating to the second communication endpoint can have a (weakened) received signal strength of, for example, no more than -100 dBm. The at least one smart wireless device can be positioned to provide a stronger path for communication between the first communication endpoint and the second communication endpoint than the direct path between the first communication endpoint and the second communication endpoint (without the at least one smart device being present. In some embodiments, the second communication endpoint can be located within a building, such as within a room (e.g., a conference room), and the at least one smart wireless device can be disposed near (e.g., within 2 m of) a window of the room / building.

[0016] BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 shows a diagram of an example of outdoor-to-indoor wireless communications with a reconfigurable intelligent surface (RIS), according to an embodiment of the subject invention.

[0018] Figure 2 shows four coverage maps of the indoor space in Figure 1 obtained with baselines and static and adaptive sequence algorithms. From left to right, the coverage maps are for (1) assistive RIS (i.e., RIS enhances outdoor-to-indoor communication), (2) no RIS, (3) static RIS controller (as in Algorithm 1, Figure 7A), and (4) adaptive RIS controller (combinatorial multi-armed bandit (CMAB)-based, as in Algorithm 2, Figure 7B, and Algorithm 3, Figure 7C). The received signal strength scale bar is in decibels-milliwatts (dBm).

[0019] Figure 3 shows a plot of average user spectral efficiency (in bits per second per Hertz (bits / s / Hz)) versus penetration loss on the direct path (r / d) (in decibels (dB)).

[0020] Figure 4 shows a plot of average user spectral efficiency (in bits / s / Hz) versus penetration losses on the direct path (r / d) (in dB). Figure 4 also shows the expected average user spectral efficiency as a function of penetration loss on the reflected path (zr) (in dB).

[0021] Figure 5 shows a plot of spatial outage (FR(^)) versus targe spectral efficiency (^) (in bits / s / Hz), showing spatial outage when z d = 60 dB and rj, G [10, 40] dB.

[0022] J:\VTI\103XClPCT\Application\Application -asfiled.doc / ke Figure 6A shows a diagram of an example of beam manipulation with an RIS, according to an embodiment of the subject invention. Figure 6 A shows the case where the RIS provides a less obstructed link, inducing user equipments (UEs) to establish links through beams that rely on the RIS.

[0023] Figure 6B shows a diagram of an example of beam manipulation with an RIS, according to an embodiment of the subject invention. Figure 6B shows the case where the RIS destroys the established link (e.g., absorbs all incident signals), severely limiting indoor- to-outdoor and outdoor-to-indoor communication.

[0024] Figure 7A shows a static sequence algorithm where the RIS reflects signals during beam sweeping and absorbs signals during data transmissions.

[0025] Figure 7B shows an adaptive sequence algorithm where the RIS dynamically controls which signals to reflect and / or absorb during beam sweeping and absorbs signals during data transmissions.

[0026] Figure 7C shows an example of an adaptive sequence algorithm based on CMAB.

[0027] Figure 8 shows a block diagram of a method for generating a dynamic virtual geographic boundary for wireless services, according to an embodiment of the subject invention.

[0028] DETAILED DESCRIPTION

[0029] Embodiments of the subject invention provide novel and advantageous systems and methods for geofencing using one or more smart wireless devices (e.g., reconfigurable intelligent surfaces (RISs), smart surfaces, and / or smart wireless repeaters) to create a dynamic virtual geographic boundary for wireless communication services, positioning, ranging, and / or sensing. RISs are (passive or active) programmable wireless relays whose properties (e.g., reflection, refraction, absorption) can be controlled dynamically. The properties of an RIS can be tuned to change the propagation environment to support specific goals, such as specific wireless communication goals (e.g., extend network coverage). Embodiments provide a novel smart wireless device controller mechanism that allows a smart wireless device to dynamically shield a network service area of interest (e.g., an indoor conference room) against outer wireless communication and / or provide enhanced wireless communication coverage in the area of interest (if desired). The controller mechanism can leverage smart wireless devices to manipulate beam management procedures and prevent or

[0030] J:\VTI\103XClPCT\Application\Application -asfiled.doc / ke inhibit initial access (procedures used to establish connections between transmitters and receivers in beamforming communication). Turning off the controller can promptly re-enable wireless communication services within the network service area of interest (or return the service level to baseline).

[0031] In embodiments of the subject invention, a controller mechanism can utilize two steps. During initial access, the controller can smartly adjust the properties of the smart wireless device (e.g., by switching between “reflection” and “absorption” during beam sweeping) to induce the transmitter and receiver to establish connectivity via the smart wireless device. During data transmissions, the properties of the smart wireless device can be set to “absorption” to hinder transmit signals from propagating to the receiver. Alternatively, during data transmissions, the properties of the smart wireless device can be set to “reflection” to boost transmit signals between the user equipments (UEs) and the receiver (or transmitter; e.g., a base station), thereby enhancing coverage if desired. If the controller is turned off, the transmitter and receiver can re-establish connectivity without relying on the smart wireless device during the next initial access procedure (e.g., typically not more than 20 milliseconds in 5G networks).

[0032] Beam management procedures can be susceptible to manipulation, such as by smartly injecting signals during beam sweeping to produce beam misalignment or an unwanted beam alignment with a third party (see also, e.g., [1] - [4]). A lower-cost, easier-to-conceal form of beam manipulation is through the use of RISs (e.g., a passive RIS or an active RIS). As a reflective relay, an RIS may exhibit a lower energy footprint and tends to preserve characteristics of legitimate reflected signals compared to conventional relays. RISs can adjust reflected signals so that they cancel out legitimate signals at the receiver (see also, e.g., Lyu et al., “IRS-based wireless jamming attacks: When jammers can attack without power,” IEEE Wireless Communications Letters, vol. 9, no. 10, pp. 1663-1667, 2020; which is hereby incorporated by reference herein in its entirety). This cancellation procedure is difficult to trigger because it requires collecting channel state information for all channels involved. RISs can also exploit vulnerabilities in wireless protocols with limited or no channel state information (see also, e.g.; Huang et al., “Illegal intelligent reflecting surface based active channel aging: When jammer can attack without power and CSI,” IEEE Transactions on Vehicular Technology, 2023; Zhang et al., “Disco intelligent reflecting surfaces: Active channel aging for fully passive jamming attacks,” IEEE Transactions on

[0033] J:\VTI\103XClPCT\Application\Application -asfiled.doc / ke Wireless Communications, 2023; and de Sena et al., “Malicious RIS versus massive MIMO: Securing multiple access against RIS-based jamming attacks,” IEEE Wireless Communications Letters, 2024; all three of which are hereby incorporated by reference herein in their entireties). Embodiments of the subject invention can use RISs to control how incident signals are absorbed, refracted, and / or reflected to exploit beam management procedures to control beam alignment even without channel state information. That is, systems and methods of embodiments of the subject invention can function with and / or without channel state information.

[0034] Beam management procedures needed to support highly directional transmission links in wireless systems have been shown to be susceptible to relay attacks that can induce beam alignment failure. Embodiments of the subject invention can provide relay attacks to manipulate beam management procedures using one or more smart wireless devices (e.g., RISs, such as passive RISs and / or active RISs). The beam manipulation can be launched by, for example, an RIS controller (e.g., a static sequence algorithm or an adaptive sequence algorithm (e.g., based on a combinatorial multi-armed bandit (CMAB)-based adversarial RIS controller)) that controls which and how reference signals enter a certain indoor network service area to manipulate indoor UEs into poor beam selection. The RIS-based beam manipulation can degrade outdoor-to-indoor communication by several orders of magnitude, thereby disrupting indoor communication.

[0035] Embodiments of the subject invention provide systems and methods for beam manipulation based on one or more smart wireless devices (e.g., RISs, smart services, and / or smart wireless repeaters). Figure 1 shows a diagram of an example of beam manipulation with an RIS, according to an embodiment of the subject invention. Referring to Figure 1, an RIS strategically deployed near a window can manipulate UEs into poor beam selection and degrade outdoor-to-indoor communication by controlling which and how signals enter the indoor space (e.g., are absorbed, refracted, and / or reflected) during beam sweeping and data transmissions. The RIS controller mechanism can be, for example, a static sequence algorithm that reflects all incident signals during beam sweeping and absorbs all incident signals during data transmissions (e.g., Algorithm 1 in Figure 7A), which is shown to hinder outdoor-to-indoor communication. A more powerful form of manipulation can be achieved by adaptive sequence algorithms (e.g., Algorithm 2 in Figure 7B), for example, by leveraging the reinforcement learning CMAB framework to generate adaptive functions and thus smartly

[0036] J:\VTI\103XClPCT\Application\Application -asfiled.doc / ke control which signals are reflected and / or absorbed during beam sweeping (e.g., Algorithm 3 in Figure 7C). Such an RIS controller mechanism can severely degrade (and potentially disrupt) outdoor-to-indoor communication with or without direct optimization, for example, by optimizing RIS phase coefficients or setting them at random, which may or may not require knowledge of channels between a base station (BS), an RIS, and UEs. Conversely, the RIS can also enhance outdoor-to-indoor communication, if desired, by continuing to reflect incident signals during data transmissions. The complementary ability to inhibit and / or enhance communication allows the RIS to control outdoor-to-indoor communication. For instance, the conference room shown in Figure 1 can be easily changed from a “strongly covered network service area” to “an out-of-service network service area” by simply changing the RIS controller mechanism and thus how it reflects, refracts, and / or absorbs signals during beam sweeping and data transmission periods. This is a useful property in scenarios where coverage is desired to be controlled; for example, the conference room can host events that require mobile coverage as well as events that forbid the use of mobile devices, such as confidential or classified meetings or school exams.

[0037] When considering the downlink of the directional communication system illustrated in Figure 1, the outdoor BS can be equipped with a linear antenna array of size AT. Then C = {ci, C2, CL} is the codebook of size L employed at the BS, where each codeword c corresponds to a different beam steering direction defined as a complex- valued vector. U = {m, U2, uu} is the set of indoor users, each of which is equipped with an isotropic antenna. The / / -element RIS is represented by the diagonal matrix 0 = diag(^7eA(j6b), ..., EeA(j / / ;)), where G [0, 1 ] and 0k G [0, 2K) are the reflection and phase coefficients for the Zr-th element (it is noted that this matrix design applies only to a passive RIS, and any active RIS, nondiagonal RIS, smart surface, or smart repeater will have other parameters as well). At any user w, the received signal is a sum of signals propagated through direct (i.e., BS-UE) and reflected (i.e., BS-RIS-UE) communication paths. The received power for a codeword c and RIS coefficients 0 can be expressed as Equation 1 :

[0038] J:\VTI\103XClPCT\Application\Application -asfiled.doc / ke

[0039] where Abs-ue G CMxl, Hbs-ris 6 CNxM, and Aris-ue 6 CNxlrepresent the channels between BS-UE, BS-RIS, and RIS-UE, whose entries follow a complex Gaussian distribution with zero mean and unit variance (see also, e.g.; Lyu et al., supra. ([5]); Huang et al., supra. ([6]); Zhang et al., supra. ([7]); and de Sena et al., supra. ([8])). Superscript H denotes the conjugate transpose operation. The path loss follows p<>r with po denoting the path loss at the reference distance of 1 meter (m), and r and a the distances and path loss exponents (see also, e.g., Lyu et al., supra. ([5])). The variables rjd and rp denote the outdoor-to-indoor penetration losses on the direct communication path and the reflected communication path, respectively. The antenna gain towards the direction r(hat) when the BS uses codeword c is given by G(c, r(hat)). An antenna array model can be adopted, for example, the antenna array model adopted by the Third Generation Partnership Project (3GPP) (see also; 3GPP, “Technical specification group radio access network; study on channel model for frequencies from 0.5 to 100 GHz,” 3GPP, Tech. Rep. 38.901, 12 2019, version 16.1.0; which is hereby incorporated by reference herein in its entirety).

[0040] Beam management procedures are required to acquire and maintain beam alignment between the outdoor BS and indoor LEs in Figure 1; otherwise, the downlink communication is susceptible to beam misalignment, which, in turn, can prevent or inhibit LEs from effectively communicating to the BS. Beam management involves a set of procedures that occur with a pre-defined periodicity to allow LEs and BS to establish and maintain connections, including beam sweeping, beam measurement, and beam reporting (see also; “Technical specification group radio access network; study on new radio access technology physical layer aspects,” 3GPP, Tech. Rep. 38.802, 09 2017, version 14.2.0; which is hereby incorporated by reference herein in its entirety).

[0041] With respect to beam sweeping, the BS broadcasts reference signals for each beam direction c in its codebook C. With respect to beam measurement, each UE assesses characteristics of the received reference signals (e.g., signal strength). With respect to beam

[0042] J:\VTI\103XClPCT\Application\Application -asfiled.doc / ke reporting, each UE selects the beam direction based on the beam measurements performed during beam sweeping and reports its choice to the BS. It can be assumed that a user u selects the beam that corresponds to the codeword with the highest received power, i.e., where 0Cdenotes the RIS coefficients for the beam direction corresponding to codeword c.

[0043] Downlink data transmissions occur between the completion and restart of this set of procedures. During downlink data transmissions, the BS uses the reported codeword csuto communicate to user u. Let ©down denote the RIS coefficients during downlink data transmissions. This way, w’s respective received power is given by yu(cSu, ©down).

[0044] The objective of the RIS controller mechanism is to manipulate beam management procedures to control (e.g., inhibit) outdoor-to-indoor communication. One way of pursuing this goal is to manipulate UEs into selecting beam directions that strongly rely on the reflected link BS-RIS-UE and then silence the RIS during data transmissions (i.e., incident signals are absorbed, = 0, V / L E ©down), making data transmissions exclusively dependent on the misaligned direct link BS-UE. Formally, this can be achieved by selecting a sequence Sopt= of RIS coefficients to be used during beam sweeping that manipulates UEs into selecting beam directions that minimize the expected received power during downlink data transmissions over the set of indoor users U, i.e., where Q is the search space containing all possible combinations of sequences of RIS coefficients.

[0045] Finding Soptcan be challenging for two reasons. First, without knowledge about channels between BS, RIS, and UE, which can be challenging to acquire, it is challenging to find 0c to optimize yM(c, 0C) for any arbitrary user u and codeword c. Second, even if channels are known, it is challenging to explore the search space Q because of the combinatorial nature of S = { 0C / ,0C2 , ...,0CL }. For instance, if 0c is discretized into Q levels, the cardinality of Q is given by Typical millimeter-wave (mmWave) systems’ codebook sizes are in the order of L = 64, which makes exploring the search space

[0046] J:\VTI\103XClPCT\Application\Application -asfiled.doc / ke challenging even if Q = 2. Following is discussion of two approaches to cope with these challenges to address the objective set forth in Equation 3, specifically a static sequence RIS controller and an adaptive sequence RIS controller.

[0047] With respect to a static sequence RIS controller (e.g., Algorithm 1 in Figure 7A), if the RIS is strategically deployed to offer a less-obstructed communication path for outdoor- to-indoor communication, as in Figure 1, where the RIS is strategically deployed near the conference room’s window, UEs are likely to select beam directions that rely on the reflected path BS-RIS-UE for subsequent communication. During beam sweeping and without channel state information to optimize RIS coefficients (i.e., no steering direction optimization), phase coefficients can, for example, be set at random with a uniform distribution, i.e., 6k = uniformfO, 2K) for any 6k G 0C, Vc G C. In order to keep the reflected path active, all RIS reflection coefficients can be set to one, i.e., > / .- = 1 for any Pk G 0c, Vc G C. During downlink data transmissions, the RIS can be silenced, i.e., incident signals are absorbed (pk = 0, V Pk G 0down). Despite the simple way of addressing the objective in Equation 3, the results in the Examples demonstrate that a static sequence RIS controller can still significantly hinder outdoor-to-indoor communication.

[0048] An adaptive sequence RIS controller (e.g., Algorithm 2 in Figure 7B) can provide an even better solution to the objective set forth in Equation 3. Particularly, the adaptive sequence algorithm can be based on the reinforcement learning CMAB framework (e.g., Algorithm 3 in Figure 7C) to smartly control which reference signals are reflected or absorbed during beam sweeping to further minimize the received power during downlink data transmissions compared to the static sequence algorithms (see also; Chen et al., “Combinatorial multi-armed bandit: General framework and applications,” in International Conference on Machine Learning. PMLR, 2013, pp. 151-159; which is hereby incorporated by reference herein in its entirety). Compared to other multi-armed bandits, CMAB defines a super-arm (5 in the context discussed herein) as a sequence of arms (0Cin the context discussed herein). The Action and Reward of the CMAB will now be discussed.

[0049] Action. For each arm 0Cduring beam sweeping, an action corresponds to the decision of reflecting (P' = 1) or absorbing (P' = 0) incident signals, a decision shared by all RIS elements, i.e., Pk = P', wPk G 0C. Action selection follows the gradient bandit approach, in which actions are

[0050] J:\VTI\103XClPCT\Application\Application -asfiled.doc / ke selected at random according to a soft-max distribution with probability mass function itcifi) (see also; Sutton et al., Reinforcement learning: An introduction, MIT press, 2015; which is hereby incorporated by reference herein in its entirety). As in the native adversarial RIS, phase coefficients are set at random, i.e., 6k = uniformfO, 2K) for any 6k G 0C.

[0051] Reward. The RIS is silenced during downlink data transmissions, i.e., = 0, V ft G ©down. The reward is collected with respect to an arbitrary user and defined as minus the received power during downlink data transmissions, i.e.,

[0052] This way, the CMAB-based adversarial RIS seeks to minimize the expected received power (or, equivalently, maximize the long-term expected reward) for a set of indoor users of interest, as specified in Equation 3.

[0053] Algorithm 3, as shown in Figure 7C, describes in detail a CMAB-based adaptive sequence RIS controller that can be used with embodiments of the subject invention. Referring to Figure 7, Tables in line 2 are used for action selection and learned during training. For each beam-sweeping procedure, CMAB selects a sequence of actions corresponding to the sequence of RIS coefficients S = {0cy ,0C2 , ...,0CL} to be used during beam sweeping (lines 6-9). During downlink data transmissions, the RIS is silenced as in line 11. If training is in progress, the reward is collected with respect to an arbitrary user u G U and tables are updated according to the gradient bandit approach (lines 12-28).

[0054] In Algorithm 3, the RIS is assumed to know the received power yu(cSu, ©down) during training. This can be obtained by feeding the RIS with feedback information from a set of UEs purposely deployed for training. Once the RIS is trained, it no longer requires feedback from UEs, as it can solely rely on the knowledge acquired during training for future decisionmaking (i.e., the learned adaptive functions obtained from Algorithm 3 can be used in Algorithm 2).

[0055] Figures 6 A and 6B show diagrams of beam manipulation with an RIS, according to an embodiment of the subject invention. Figure 6 A shows the case where the RIS provides a less obstructed link, inducing UEs to select beams that rely on the RIS, and Figure 6B shows the case where the RIS destroys an alternative link (e.g., absorbs all incident signals), severely

[0056] J:\VTI\103XClPCT\Application\Application -asfiled.doc / ke limiting indoor-to-outdoor and outdoor-to-indoor communication between the UEs and the BS.

[0057] Figure 8 shows a block diagram of a method for generating a dynamic virtual geographic boundary for wireless services. Referring to Figure 8, in a first step, for each beam during beam sweeping, a response can be selected (e.g., reflect or absorb), and direction optimization can be generated with or without channel state information, and these steps can be repeated if necessary. In a second step, after data transmission, the response can be set to either inhibit communication (e.g., absorption) or enhance communication (e.g., reflection) if desired.

[0058] Embodiments of the subject invention provide systems and methods for beam manipulation based on RISs (e.g., passive RISs and / or active RISs). An adaptive sequence algorithm (e.g., based on CMAB) can manipulate UEs into poor beam selection by smartly controlling how signals are relayed during beam sweeping, causing severe beam misalignment during data transmissions, when the RIS is set to absorption, and thereby hindering outdoor-to-indoor communication. Further, the RIS can also enhance outdoor-to- indoor communication by reflecting signals during data transmissions. This can be beneficial in scenarios where indoor coverage is desired to be controllable; for example, an RIS can easily change an indoor network service area from “strongly covered” to “strongly shielded” by simply changing which signals are reflected during beam sweeping, allowing the indoor space (e.g., a conference room) to host a variety of events, from events that require mobile network coverage to events that may forbid the use of mobile devices (e.g., classified meetings or school exams).

[0059] Embodiments of the subject invention can be utilized in scenarios where network coverage is desirable to be controllable over time and space. For instance, a property owner may be interested in a controller to control outdoor-to-indoor network coverage. An RIS, smart surface, or wireless repeater can be deployed in a facility to enhance mobile network coverage within the property. In addition to this, a controller as disclosed herein can allow the property owner to hinder wireless communication services in certain locations during particular events, such as preventing or inhibiting mobile phone use within a conference room when the room hosts classified meetings or school exams. Systems and methods of embodiments of the subject invention can be useful for, e.g., RIS manufacturers, telecommunications equipment vendors, network operators (e.g., to offer geofencing as a

[0060] J:\VTI\103XClPCT\Application\Application -asfiled.doc / ke service), cybersecurity infrastructure companies (e.g., to control wireless communication services over time and space), and / or property owners.

[0061] The methods and processes described herein can be embodied as code and / or data. The software code and data described herein can be stored on one or more machine-readable media (e.g., computer-readable media), which may include any device or medium that can store code and / or data for use by a computer system. When a computer system and / or processor reads and executes the code and / or data stored on a computer-readable medium, the computer system and / or processor performs the methods and processes embodied as data structures and code stored within the computer-readable storage medium.

[0062] It should be appreciated by those skilled in the art that computer-readable media include removable and non-removable structures / devices that can be used for storage of information, such as computer-readable instructions, data structures, program modules, and other data used by a computing system / environment. A computer-readable medium includes, but is not limited to, volatile memory such as random access memories (RAM, DRAM, SRAM); and non-volatile memory such as flash memory, various read-only-memories (ROM, PROM, EPROM, EEPROM), magnetic and ferromagnetic / ferroelectric memories (MRAM, FeRAM), and magnetic and optical storage devices (hard drives, magnetic tape, CDs, DVDs); network devices; or other media now known or later developed that are capable of storing computer-readable information / data. Computer-readable media should not be construed or interpreted to include any propagating signals. A computer-readable medium of embodiments of the subject invention can be, for example, a compact disc (CD), digital video disc (DVD), flash memory device, volatile memory, or a hard disk drive (HDD), such as an external HDD or the HDD of a computing device, though embodiments are not limited thereto. A computing device can be, for example, a laptop computer, desktop computer, server, cell phone, or tablet, though embodiments are not limited thereto.

[0063] When the term module is used herein, it can refer to software and / or one or more algorithms to perform the function of the module; alternatively, the term module can refer to a physical device configured to perform the function of the module (e.g., by having software and / or one or more algorithms stored thereon).

[0064] When ranges are used herein, combinations and subcombinations of ranges (including any value or subrange contained therein) are intended to be explicitly included. When the term “about” is used herein, in conjunction with a numerical value, it is understood that the

[0065] J:\VTI\103XClPCT\Application\Application -asfiled.doc / ke value can be in a range of 95% of the value to 105% of the value, i.e. the value can be + / - 5% of the stated value. For example, “about 1 kg” means from 0.95 kg to 1.05 kg.

[0066] A greater understanding of the embodiments of the subject invention and of their many advantages may be had from the following examples, given by way of illustration. The following examples are illustrative of some of the methods, applications, embodiments, and variants of the present invention. They are, of course, not to be considered as limiting the invention. Numerous changes and modifications can be made with respect to embodiments of the invention.

[0067] MATERIALS AND METHODS

[0068] For evaluation of static and adaptive sequence RIS controller algorithms as disclosed herein, a two-dimensional network was considered that corresponds to the scenario depicted in Figure 1. System-level simulations were performed to assess the downlink with respect to users located within the conference room. The outer BS was located at (0, 0), and the conference room corresponded to the square given by (100, 5), (110, 5), (100, -5), and (110, - 5). An RIS of size K = 1024 was strategically deployed near the window on the upper left of the conference room as depicted in Figure 1 (i.e., at location (100, -5)), which can provide an alternative, less-obstructed path for communication. The antenna array model from 3GPP was adopted (see also, 3GPP, supra. ([9]). Considering a carrier frequency of 30 gigahertz (GHz), a linear antenna array of size M = 64 was considered and a codebook of size L = 64 was considered in which angles were spaced evenly from -45 to +45 degrees in the azimuth plane (see also; Baron -Hyppolite et al., “Adaptive beam management for secure mmWave communications using software-defined radios,” in MILCOM 2023-2023 IEEE Military Communications Conference (MILCOM), IEEE, 2023, pp. 243-244; which is hereby incorporated by reference herein in its entirety. The following parameters were set: transmit power Pt= 35 decibel-milliwatts (dBm); reference noise level ZdBm = “85 dBm, which was obtained considering a noise spectral efficiency of -174 decibel-milliwatts per Hertz (dBm / Hz) over 100 megahertz (MHz) and an UE noise figure of 9 dB; path loss at the reference distance of 1 m po = 30 decibels (dB); and path loss exponents «bs -ue ^bs-ris ^ris-ue = 4.5. For training, 50 users were considered uniformly distributed across the conference room, and five hundred beam-sweeping procedures were used to train the CMAB-based adaptive RIS controller. For each beam-sweeping procedure, a user was selected at random

[0069] J:\VTI\103XClPCT\Application\Application -asfiled.doc / ke with a uniform distribution to obtain the reward. The system’s performance was assessed based on downlink data transmissions with respect to a new set of users. Training (CMAB- based algorithm only) and evaluation was repeated over multiple independent sets of users to capture the performance across multiple network realizations. The learning rate c of the CMAB adversarial RIS was empirically selected out of a range of {0.0001, 0.001, 0.01, 0.1, 1 }, from which e = 0.01 yielded the lowest average user spectral efficiency when rjd = 60 dB and Tjr= 10 dB.

[0070] The static and adaptive RIS controllers were contrasted with two baselines, assistive RIS and no RIS. With respect to assistive RIS, the RIS provides an alternative, less- obstructed path for communication. Reflection coefficients were set to one during beam sweeping and downlink data transmissions, i.e., = 1, V L in any 0Cand ©down. Phase coefficients were set at random with a uniform distribution in [0, 2K). Compared to static and adaptive RIS controllers, the assistive RIS manipulates UEs into selecting beam directions that rely on the reflected link BS-RIS-UE but sustains the reflected link during downlink data transmissions. With respect to no RIS, the reflected path BS-RIS-UE is destroyed during beam sweeping and downlink data transmissions, such that the RIS absorbs all incident signals, i.e., / L = 0 for any 0Cand ©down. This way, outdoor-to-indoor communication is exclusively dependent on the direct communication path BS-UE.

[0071] EXAMPLE 1

[0072] In order to illustrate the different performances yielded by the different RIS controllers and baselines, a grid of 50 x 50 users was considered evenly distributed across the conference room, with penetration losses rjd = 60 dB (wall) and rj, = 10 dB (window). Figure 2 shows the resulting coverage maps for the different modes of operation of the RIS. As a reference, the RIS is located near the conference room’s window at the left top corner (as depicted in Figure 1), as highlighted in the leftmost coverage map in Figure 2, and the BS on the outer left-hand side (not shown in Figure 2). Within a coverage map, each small square’s color represents the received power perceived by the respective user at that location.

[0073] The assistive RIS provides an alternative, less-obstructed path for outdoor-to-indoor communication through the window, substantially enhancing indoor network coverage compared

[0074] J:\VTI\103XClPCT\Application\Application -asfiled.doc / ke to no RIS, in which outdoor-to-indoor communication exclusively relies on the obstructed communication path through the wall. The static sequence RIS controller manipulates UEs into selecting beam directions that rely on the reflected link BS-RIS-UE but subsequently silences the RIS, causing beam misalignment to most of the users within the conference room. Beam misalignment is milder for users located at the bottom of the conference room because the selected beam is similar to what would be selected otherwise, resulting in similar received powers to no RIS. The CMAB-based adaptive sequence RIS controller adversarial RIS more homogeneously and strongly degrades coverage by manipulating UEs into poorer beam selection compared to the static sequence RIS. Figure 2 shows that coverage over the entire area can be changed from “very strong” to “very weak” by simply changing the RIS’ mode of operation from assistive to adaptive sequence controller. This flexibility is particularly useful if the conference room hosts a variety of events, from events that require network coverage to events that forbid the use of mobile devices (e.g., classified meetings or school exams).

[0075] EXAMPLE 2

[0076] The performance of static and adaptive RIS controllers and baselines depends on the degree of obstruction of direct (z d) and reflected (zr) communication paths. If rjd ~ an RIS may have limited control over UEs’ beam selection, limiting its manipulation power. Further, in assistive RISs, it may no longer offer an alternative, less-obstructed communication path, marginally (if at all) enhancing outdoor-to-indoor communication. In order to analyze the impact of rjd and zr, the average user spectral efficiency can be considered: where = {yu(csu, ©down), Vi / E F} is a random set of the downlink received powers of 50 users uniformly distributed across the conference room. One hundred (100) independent sets were generated, and the sample mean of the average user spectral efficiency was reported with a 95% confidence interval (shaded error bands; notice that bands are narrow, e.g., CMAB RIS in Figure 3, or even imperceptible, e.g., other curves in Figure 3, because of the log-scale and high confidence of estimates).

[0077] J:\VTI\103XClPCT\Application\Application -asfiled.doc / ke Figure 3 shows the average user spectral efficiency as a function of z d (i.e., penetration loss of the conference room’s wall). The penetration loss on the window is fixed at rj, = 10 dB. As a reference, single-layer glass, two-layer glass, and wood exhibit a penetration loss between 5 and 10 dB at 30 GHz. For small rjd (e.g., no more than 20 dB), an RIS has little impact on hindering outdoor-to-indoor communication. However, as rjd increases, an RIS can induce UEs to poor beam selection, resulting in beam misalignment and reducing the average user spectral efficiency. Notably, the CMAB-based adaptive RIS controller outperforms the static RIS controller by manipulating UEs into poorer beam selection. At the rjd = 60 dB mark (e.g., a concrete wall has a penetration loss of at least 60 dB at 30 GHz), the RIS controller reduced the average user spectral efficiency by more than one order of magnitude compared to the static RIS controller, two orders of magnitude compared to no RIS, and five orders of magnitude compared to the assistive RIS.

[0078] Figure 4 shows the expected average user spectral efficiency for different values of rj, for assistive and CMAB-based adaptive RIS controller. Penetration losses of typical window materials were considered, from low rj, = 10 dB (e.g., single-layer glass, two-layer glass, and wood) to high T]r= 40 dB (e.g., solar glass). The higher the penetration loss zr, the less manipulation power the CMAB-based adaptive RIS controller had, and the less the assistive RIS can enhance outdoor-to-indoor communication. Figure 4 confirms this by showing that the average user spectral efficiency increases with for the CMAB-based adaptive RIS controller and decreases with for the assistive RIS. Yet, at rjd = 60 dB and rj, = 40 dB, the difference between them is nearly three orders of magnitude.

[0079] EXAMPLE 3

[0080] Another way of contrasting the CMAB-based adaptive RIS controller with the assistive RIS is to consider the distribution of the user spectral efficiency throughout the conference room, as opposed to its expectation in Equation 5. Spatial outage can be defined as the empirical cumulative distribution function of the user spectral efficiency:

[0081] J:\VTI\103XClPCT\Application\Application -asfiled.doc / ke i.e., the fraction of indoor users that experience a spectral efficiency of less than bits per second per Hertz (bits / s / Hz). As in Example 2, 100 independent sets of 50 users uniformly distributed across the conference room were considered, and the sample mean of the spatial outage is reported.

[0082] Figure 5 shows the spatial outage for the same range of rj, as Figure 4 when rjd = 60 dB. At the rj, = 20 dB mark, the CMAB-based adaptive RIS controller can induce beam misalignment such that 80% of the users throughout the conference room are expected to experience a spectral efficiency of less than 0.0001 bits / s / Hz, or nearly all users are expected to experience a spectral efficiency of less than 0.001 bits / s / Hz (left-hand side of the (red) arrow in Figure 5). As a reference, a minimum downlink user spectral efficiency of 0.12 bits / s / Hz is required to support enhanced mobile broadband (eMBB) services (as per the 5th percentile user spectral efficiency requirement; see also ITU-R, “Minimum requirements related to technical performance for IMT-2020 radio interface(s),” International Telecommunication Union (ITU), Tech. Rep. ITU-R M.2410-0, 11 2017; which is hereby incorporated by reference herein in its entirety). Under the same conditions, the assistive RIS can guarantee that nearly no user experiences a spectral efficiency of less than 1 bits / s / Hz (right-hand side of the (red) arrow in Figure 5).

[0083] It should be understood that the examples and embodiments described herein are for illustrative purposes only and that various modifications or changes in light thereof will be suggested to persons skilled in the art and are to be included within the spirit and purview of this application.

[0084] All patents, patent applications, provisional applications, and publications referred to or cited herein (including in the “References” section, if present) are incorporated by reference in their entirety, including all figures and tables, to the extent they are not inconsistent with the explicit teachings of this specification.

[0085] J:\VTI\103XClPCT\Application\Application -asfiled.doc / ke REFERENCES

[0086] [1] B. Kim, Y. Sagduyu, T. Erpek, and S. Ulukus, “Adversarial attacks on deep learning based mmWave beam prediction in 5G and beyond,” in 2021 IEEE Statistical Signal Processing Workshop (SSP), 2021, pp. 590-594.

[0087] [2] S. Dinh-Van, T. M. Hoang, B. B. Cebecioglu, D. S. Fowler, Y. K. Mo, and M. D. Higgins, “A defensive strategy against beam training attack in 5G mmWave networks for manufacturing,” IEEE Transactions on Information Forensics and Security, 2023.

[0088] [3] D. Darsena and F. Verde, “Anti-jamming beam alignment in millimeterwave MIMO systems,” IEEE Transactions on Communications, vol. 70, no. 8, pp. 5417-5433, 2022.

[0089] [4] J. Li, L. Lazos, and M. Li, “SecBeam: Securing mmWave beam alignment against beamstealing attacks,” arXiv preprint arXiv:2307.00178, 2023.

[0090] [5] B. Lyu, D. T. Hoang, S. Gong, D. Niyato, and D. I. Kim, “IRS-based wireless jamming attacks: When jammers can attack without power,” IEEE Wireless Communications Letters, vol. 9, no. 10, pp. 1663-1667, 2020.

[0091] [6] H. Huang, Y. Zhang, H. Zhang, C. Zhang, and Z. Han, “Illegal intelligent reflecting surface based active channel aging: When jammer can attack without power and CSI,” IEEE Transactions on Vehicular Technology, 2023.

[0092] [7] H. Huang, Y. Zhang, H. Zhang, Y. Cai, A. L. Swindlehurst, and Z. Han, “Disco intelligent reflecting surfaces: Active channel aging for fully passive jamming attacks,” IEEE Transactions on Wireless Communications, 2023.

[0093] [8] A. S. de Sena, J. Kibilda, N. H. Mahmood, A. Gomes, and M. Latvaaho, “Malicious RIS versus massive MIMO: Securing multiple access against RIS-based jamming attacks,” IEEE Wireless Communications Letters, 2024.

[0094] [9] 3 GPP, “Technical specification group radio access network; study on channel model for frequencies from 0.5 to 100 GHz,” 3rd Generation Partnership Project (3GPP), Tech. Rep. 38.901, 12 2019, version 16.1.0.

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[0010] - , “Technical specification group radio access network; study on new radio access technology physical layer aspects,” 3rd Generation Partnership Project (3GPP), Tech. Rep. 38.802, 09 2017, version 14.2.0.

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[0011] - , “5G NR; physical layer procedures for control,” 3rd Generation Partnership

[0097] Project (3GPP), Tech. Rep. 138.213, 05 2022, version 17.1.0.

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[0012] W. Chen, Y. Wang, and Y. Yuan, “Combinatorial multi-armed bandit: General framework and applications,” in International conference on machine learning. PMLR, 2013, pp. 151-159.

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[0013] R. S. Sutton and A. G. Barto, Reinforcement learning: An introduction. MIT press, 2015.

[0014] A. Baron-Hyppolite, J. V. Abreu, J. F. Santos, L. A. DaSilva, and J. Kibilda, “Adaptive beam management for secure mmWave communications using software-defined radios,” in MILCOM 2023-2023 IEEE Military Communications Conference (MILCOM). IEEE, 2023, pp.

[0100] 243-244.

[0015] 3GPP, “Additional considerations on building penetration loss modeling for 5G system performance evaluation,” 3rd Generation Partnership Project (3GPP), Tech. Rep. Rl-165398, 4 2016, 3 GPP TSG RAN WG1 Meeting.

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[0016] ITU-R, “Minimum requirements related to technical performance for IMT-2020 radio interface(s),” International Telecommunication Union (ITU), Tech. Rep. ITU-R M.2410-0, 11 2017.

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Claims

CLAIMSWhat is claimed is:

1. A system for generating a dynamic virtual geographic boundary for wireless services, the system comprising: at least one smart wireless device configured to absorb incident wireless signals, reflect incident wireless signals, or both; a processor; and a machine-readable medium in operable communication with the processor and having instructions stored thereon that, when executed by the processor, perform the following steps: i) smartly adjusts properties of the at least one smart wireless device to induce a first communication end point and a second communication end point to establish connectivity via the at least one smart wireless device; and ii) manipulate the properties of the at least one smart wireless device during data transmission between the first communication end point and the second communication end point, wherein the at least one smart device comprises at least one of a reconfigurable intelligent surface (RIS), a smart surface, and a smart wireless repeater, and wherein the manipulating of the properties of the at least one smart wireless device comprises at least one of the following: ii-a) setting the properties of the at least one smart wireless device to absorb the incident wireless signals to hinder signals from propagating to the second communication end point; and ii-b) setting the properties of the at least one smart wireless device to reflect the incident wireless signals to enhance signals propagating to the second communication end point.J:\VTM03XClPCT pplication\Application -asfiled.doc\ke2. The system according to claim 1, wherein the wireless signals are wireless communication signals, wireless positioning signals, wireless ranging signals, or wireless sensing signals.

3. The system according to any of claims 1-2, wherein the at least one smart device is a static sequence RIS.

4. The system according to any of claims 1-3, wherein at least one of step i) and step ii) comprises using a combinatorial multi-armed bandit (CMAB).

5. The system according to any of claims 1-4, wherein at least one of step i) and step ii) comprises performing a static sequence algorithm or an adaptive sequence algorithm.

6. The system according to any of claims 1-5, wherein steps i) and ii) are performed without any channel state information.

7. The system according to claim 6, wherein the at least one smart device comprises an RIS, and wherein steps i) and ii) are performed without any search of a search space ( ) containing all possible combinations of sequences of RIS coefficients.

8. The system according to any of claims 1-5, wherein the at least one smart device comprises an RIS, and wherein steps i) and ii) are performed without any search of a search space ( ) containing all possible combinations of sequences of RIS coefficients.

9. The system according to any of claims 1-8, wherein, after step ii), the signals propagating to the second communication end point have a received signal strength of no more than -100 decibels-milliwatts (dBm).J:\VTM03XClPCTApplication\Application -asfiled.doc / ke10. The system according to any of claims 1-9, wherein the second communication end point is located within a building.

11. A method for generating a dynamic virtual geographic boundary for wireless services, the method comprising: i) smartly adjusting properties of at least one smart wireless device to induce a first communication end point and a second communication end point to establish connectivity via the at least one smart wireless device, wherein the at least one smart wireless device is configured to absorb and / or reflect incident wireless signals; and ii) manipulating the properties of the at least one smart wireless device during data transmission between the first communication end point and the second communication end point, wherein the at least one smart device comprises at least one of a reconfigurable intelligent surface (RIS), a smart surface, and a smart wireless repeater, and wherein the manipulating of the properties of the at least one smart wireless device comprises at least one of the following: ii-a) setting the properties of the at least one smart wireless device to absorb the incident wireless signals to hinder signals from propagating to the second communication end point; and ii-b) setting the properties of the at least one smart wireless device to reflect the incident wireless signals to enhance signals propagating to the second communication end point.

12. The method according to claim 11, wherein the wireless signals are wireless communication signals, wireless positioning signals, wireless ranging signals, or wireless sensing signals.

13. The method according to any of claims 11-12, wherein the at least one smart device is a static sequence RIS.J:\VTM03XClPCTApplication\Application -asfiled.doc / ke14. The method according to any of claim 11-13, wherein at least one of step i) and step ii) comprises using a combinatorial multi-armed bandit (CMAB).

15. The method according to any of claims 11-14, wherein at least of step i) and step ii) comprises performing a static sequence algorithm or an adaptive sequence algorithm.

16. The method according to any of claims 11-15, wherein steps i) and ii) are performed without any channel state information.

17. The method according to claim 16, wherein the at least one smart device comprises an RIS, and wherein steps i) and ii) are performed without any search of a search space (£2) containing all possible combinations of sequences of RIS coefficients.

18. The method according to any of claims 11-15, wherein the at least one smart device comprises an RIS, and wherein steps i) and ii) are performed without any search of a search space (Q) containing all possible combinations of sequences of RIS coefficients.

19. The method according to any of claims 11-18, wherein, after step ii), the signals propagating to the second communication end point have a received signal strength of no more than -100 decibels-milliwatts (dBm).

20. The method according to any of claims 11-19, wherein the second communication end point is located within a building.J:\VTM03XClPCTApplication\Application -asfiled.doc / ke

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