Efficient near-field localization aided with reconfigurable intelligent surface using geometric dilution of precision

Reconfigurable intelligent surfaces (RIS) have the ability to steer the electromagnetic (EM) waves to a desired direction. This enables the improvement of the wireless link performance by allowing the illumination of receivers otherwise shadowed by buildings or hills. In this paper, a standards-compliant link-level simulator is developed to study the performance improvement offered by a RIS in 5G New Radio (NR) uplink operating at sub-6 GHz bands. At these frequencies the direct channel between the user and base station is rarely completely blocked, but given the stringent power restrictions of devices, the RIS is utilized for enhancing the coverage performance in the uplink direction. In the studied cases, the transmitter (TX) is close to the RIS and a line-of-sight (LoS) path between the TX and RIS is assumed. The channel between the TX and receiver (RX) is modeled as a non-line-of-sight (NLoS) channel with 5G NR clustered delay line A (CDL-A) profile. Both LoS and NLoS channels between the RIS and RX are considered. Under state-of-the-art system settings, the RIS is shown to increase the symbol error rate link performance by 6 dB. When the performance is measured with coded bit error rate, the performance gain in simulated cases is 1 dB. The coverage enhancement is measured with the throughput as a function of the distance between the TX and RX. The distance at which the maximum possible throughput can be achieved is increased about 5%. The coverage can be further extended if a lower than the maximum throughput is accepted.

Geometric dilution of precision (GDOP) is defined as the ratio of the root-mean-square position determination error to the root-mean-square measurement error. Based on the Cramer-Rao lower bound (CRLB), new mathematical expressions of GDOP are presented in Time-of-Arrival (TOA) and Angle-of-Arrival (AOA) positioning systems in this paper. The expressions obviously reveal that the geometrical shape of the anchor nodes make a significant influence on GDOP. Then the influence of adding a new anchor node at different locations is analyzed. Simulations show that in both positioning systems, two optimal placement angles exist to make the GDOP smallest, when the original anchor nodes are no uniformly scattered. However, when uniformly scattered, the GDOP keeps constant no matter what angle the new anchor node is placed at. In AOA positioning systems, the GDOP is also affected by the distance between the newly added anchor node and the target, and increases when the distance increases. Meanwhile, the GDOP is always reduced when more anchor nodes are used.

In this paper, we explore the use of reconfigurable intelligent surface (RIS) in unmanned aerial vehicle (UAV) based multiuser downlink communications, where a flying UAV serves multiple single antenna users through multiple RISs mounted on various buildings. More specifically, we consider the selection of RISs based on the outdated and imperfect channel state information (CSI) of the composite UAV-RIS-User channels at the UAV. After selection process, the UAV communicates to the user via the selected RISs and also with the direct link. Particularly, we derive an infinite series based expression for selection probability of RISs under both the outdated and imperfect CSI of composite channels based selection scheme. We also derive the statistical distribution of instantaneously received signal-to-noise ratio (SNR) under outdated and imperfect CSI conditions of both the direct and composite links at the user. Next, using the derived statistics, we analyze the network’s performance in terms of the average coverage probability (ACP) and average bit error rate (ABER) over the complete UAV flight time. Moreover, we discuss the behavior of ACP and ABER for very small and very large values of UAV transmit power, respectively. It is depicted through numerical results that selecting more RISs from a group of small-sized RISs may not be as advantageous as selecting fewer RISs from a group of large-sized RISs. Moreover, we also demonstrate the effect of several system parameters such as number of RIS reflecting elements, number of selected RISs, the severity of UAV-RIS and RIS-User links, and the severity of imperfect and outdated CSI on the network’s performance. The analytical results are corroborated with Monte-Carlo simulations.

A High-Efficiency and Versatile Reconfigurable Intelligent Surface Design Paradigm with Novel Topological Representation

This paper presents field test results of mobile positioning with signals of opportunity (SOOP) in urban and urban canyon environments and the lessons learned. The particular SOOP considered in this paper is the digital television (DTV) signals available in the United States, namely, ATSC-8VSB. The field tests include runs in downtown San Mateo and San Francisco Financial District, representing typical urban and urban canyon environments. DTV signals from six DTV stations together with IMU and GPS data are recorded aboard a ground vehicle. The field tests show that DTV signals are abundant in urban and urban canyon environments, contrary to a popular concern about signal availability due to blockage by high-risers. Positioning geometry is also not a problem even though the number of transmitters may be limited because the ranges to signal sources are relatively short and the resulting geometric dilution of precision (GDOP) is acceptable especially for the two-dimensional solutions. However, multipath is omnipresent, having two detrimental effects on ranging and positioning. Severe mobile fading is frequent that disrupts continuous tracking and non-line of sight (NLOS) signals introduce large errors to correlation peak based timing. To process multipath-dominant signals, a signal parameter estimation methodology is developed. In this approach, periodic signal patterns (field sync segments at 41 Hz) are searched for via correlation using a constant false alarm rate (CFAR) detector and their times of arrival (TOA) are extracted using the orthogonal matched pursuit (OMP) algorithm amidst multipath to form pseudorange measurements. Both standalone SOOP solutions and integrated SOOP/IMU solutions are generated for the test trajectories, which are then compared to GPS for performance evaluation. The study indicates that the processing algorithms presented in the paper can successfully detect the first arrival of SOOP in urban and urban canyon environments and extract its TOA precisely when the signals are available (out of fading or blockage). However, the timing information carried by such first arrivals, good enough to serve the primary purpose of communications, may not be so for ranging because of NLOS. As such, timing of first arrivals is not sufficient by itself for positioning and has to be used in conjunction with other data such as IMU, which is used in this paper. Yet, distinct and stable multipath signatures may be exploited, together with an environment map for instance, for persistent positioning in urban and urban canyon environments, which is a direction of our future research.

In this article, the physical layer security (PLS) is investigated for reconfigurable intelligent surface (RIS)-aided wireless communication systems, where one RIS is deployed to assist the communications between a pair of transmitter (Alice) and receiver (Bob), under a passive eavesdropper (Eve) attack. For the Eve, different from the bounded channel state information uncertainty model, the distribution of the Eve's location is introduced into the wiretap link. In the proposed system, considering that the Eve can overhear signals transmitted from Alice or reflected by the RIS, two scenarios are studied for RIS-aided secure communication systems: one is that the Eve distributes close to Alice without the RIS orientation, and the other is that the Eve locates close to Bob and in the presence of the RIS. After investigating the probability distribution functions of the Eve's location and the wiretap link, the novel cumulative density functions (CDFs) of the received signal-to-noise ratios (SNRs) at the Eves are, respectively, derived for the two considered scenarios, taking into account the effects of RIS reflection coefficients, pathloss, and Eve's location distribution. The closed-form expressions for the probability of the nonzero secrecy capacity and the ergodic secrecy capacity are obtained, providing insights into the impact of the Eve's location uncertainty and the RIS design on the secrecy performance. Moreover, based on the derived CDFs for received SNRs at Eves, the secrecy outage probabilities are, respectively, analyzed. Specifically, under the constraint of the secrecy outage probability, the closed forms of the minimum required SNRs at Bob and the number of RIS elements are also obtained. Simulation and analytical results corroborate the derived expressions and reveal the tradeoff between the system's energy efficiency and the number of RIS elements.

In order to improve the accuracy and engineering feasibility of four-Satellite localization system, the frequency difference measurement is introduced to the four-Satellite TDOA (Time Difference of Arrival) localization algorithm. The TDOA/FDOA (Frequency Difference of Arrival) localization algorithm is used to optimize the GDOP (geometric dilution of precision) of four-Satellite localization. The simulation results show that the absolute position measurement accuracy has little influence on TDOA/FDOA localization accuracy as compared with TDOA localization. Under the same conditions, TDOA/FDOA localization has better accuracy and its GDOP shows more uniform distribution in diamond configuration case. The localization accuracy of four-Satellite TDOA/FDOA is better than the localization accuracy of four-Satellite TDOA.

In this paper, a novel framework for guaranteeing ultra-reliable millimeter wave (mmW) communications using multiple artificial intelligence (AI)-enabled reconfigurable intelligent surfaces (RISs) is proposed. The use of multiple AI-powered RISs allows changing the propagation direction of the signals transmitted from a mmW access point (AP) thereby improving coverage particularly for non-line-of-sight (NLoS) areas. However, due to the possibility of highly stochastic blockage over mmW links, designing an intelligent controller to jointly optimize the mmW AP beam and RIS phase shifts is a daunting task. In this regard, first, a parametric risk-sensitive episodic return is proposed to maximize the expected bitrate and mitigate the risk of mmW link blockage. Then, a closed-form approximation of the policy gradient of the risk-sensitive episodic return is analytically derived. Next, the problem of joint beamforming for mmW AP and phase shift control for mmW RISs is modeled as an identical payoff stochastic game within a cooperative multi-agent environment, in which the agents are the mmW AP and the RISs. Two centralized and distributed controllers are proposed to control the policies of the mmW AP and RISs. To <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">directly</i> find a near optimal solution, the parametric functional-form policies for the controllers are modeled using deep recurrent neural networks (RNNs). The deep RNN-based controllers are then trained based on the derived closed-form gradient of the risk-sensitive episodic return. It is proved that the gradient update algorithm converges to the same locally optimal parameters as the deep RNN-based centralized and distributed controllers. Simulation results show that the error between the policies of the optimal and the RNN-based controllers is less than 1.5%. Moreover, the variance of the achievable rates resulting from the deep RNN-based controllers is 60% less than the variance of the risk-averse baseline.

Optimizing resource allocation for enhanced urban connectivity in LEO-UAV-RIS networks

Reconfigurable Intelligent Surface (RIS) has been considered as a promising technology for 6G networks, which is capable of directionally reflecting the incident signal by adjusting phase shift of its reflecting elements, and thus to achieve beamforming. In this paper, we investigate the potential of employing RIS in dual-functional radar-communication (DFRC) vehicular networks. Considering a vehicle-to-infrastructure (V2I) communication in non-line-of-sight(N-LoS) scenario, where RIS is deployed to establish sensing and communication links, we propose a scheme to optimize the beamforming based on the detected vehicle position for the sake of avoiding the relatively large channel estimation overhead. More specifically, we build a codebook to maintain the optimal phase shift of RIS corresponding to each candidate angle offline, which can be used for detecting the direction of vehicle in N-LoS scenario. In addition, the position-based channel state information (CSI) is introduced and used for maximize the downlink rate. Simulation results show that by deploying RIS in DFRC vehicular networks, the base station can detect the vehicle position in N-LoS scenario and provide it with reliable communication rates without channel estimation.

A method of time difference of arrival (TDOA) location for shortwave signal source by four receiving stations is introduced. The precision of time difference and the Geometric Dilution of Precision (GDOP) of TDOA location are analyzed and simulated. The results show that TDOA estimation performance is positively correlated with signal bandwidth, signal cumulative time and signal-to-noise ratio (SNR), while TDOA location precision is positively correlated with TDOA estimation precision and distance between the receiving stations. At the same time, the simulation analysis of station arrangement among multiple stations is carried out, and the results show that Y-shaped station mode gets the best location effect.

The wireless communication field is growing tremendously. To achieve the key requirements of future wireless networks, reconfigurable intelligent surface (RIS) assisted communication is a new research direction. RIS consists of more passive reflectors, and it can direct the signal towards the desired user by adjusting the phase shift of passive elements, hence signal-to-noise ratio (SNR) can be improved. The ideal RIS can compensate the channel effects completely. Practically, the compensation of each and every phase of RIS elements is very difficult. In this work, an algorithm for intelligent discrete phase shifter assisted RIS is developed. The proposed algorithm is tested with one-bit and two-bit discrete phase shifters. Discrete phase shifter maps the required phase of RIS elements to discrete phase levels and steers the beam. Through simulations, it is observed that the increase in discrete phase levels and RIS elements offers performance similar to ideal RIS assisted communication.

Reconfigurable intelligent surface (RIS) has recently emerged as a promising technology for wireless communications, which intelligently controls the phase shift of each unit cell to form desired beams. Most prior works on RIS focus on a single frequency band, and thus for time-division duplexing (TDD) systems, the same phase shifts can be applied to both uplink and downlink. However, for the frequency-division duplexing (FDD) mode, if the same phase shifts are applied in both uplink and downlink, the directions of the uplink RIS beams will not be aligned with those of the downlink, which will in turn cause performance degradation. To address this issue, in this paper, we investigate the practical RIS design and optimization for FDD systems. By representing the reflection coefficients of RIS with the equivalent circuit model which includes the resistor, inductor and tunable capacitor, we first provide the guidelines on the circuit design to realize 2&#x03C0; phase control over the two frequency bands of the FDD system. In addition, we propose a low-resolution RIS configuration scheme with two tunable modes corresponding to two capacitances, and we formulate a max-min signal-to-noise ratio (SNR) problem to maximize the minimum SNR of uplink and downlink. To solve the non-convex problem, we propose an alternating optimization algorithm to obtain a suboptimal solution. Simulation results show that our proposed RIS design outperforms those benchmarks which design the circuits by only optimizing uplink or downlink.

Backscatter communication (BC) has emerged as a pivotal wireless communication paradigm owing to its low-power and cost-effective characteristics. However, BC faces various challenges from its low signal detection rate to its security vulnerabilities. Recently, reconfigurable intelligent surfaces (RIS) have surfaced as a transformative technology addressing power and communication performance issues in BC. However, the potential of RIS in addressing the security challenges of BC remains uncharted. This paper investigates the secrecy performance of RIS-aided BC, where all channels are distributed according to the Fisher-Snedecor <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {F}$</tex-math></inline-formula> distribution. Specifically, we consider a RIS with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$N$</tex-math></inline-formula> reflecting elements to help a backscatter device (BD) establish a smart environment and enhance the secrecy performance in BC. Due to the nature of BC systems, our analysis considers two possible scenarios (i) in the absence of direct links and (ii) in the presence of direct links. In both cases, we first derive compact analytical expressions of the probability density function (PDF) and cumulative distribution function (CDF) for the received signal-to-noise ratio (SNR) at both a legitimate receiver and an eavesdropper. Then, to analyze the secrecy performance, we further derive analytical expressions of the average secrecy capacity (ASC) and secrecy outage probability (SOP) for both mentioned scenarios. In addition, regarding the importance of system behavior in a high SNR regime, we provide an asymptotic analysis of the SOP and ASC. Eventually, the Monte-Carlo simulation is used to validate the analytical results, revealing that utilizing RIS can greatly improve the secrecy performance of the BC system relative to traditional BC setups that do not incorporate RIS.

This paper investigates a reconfigurable intelligent surface (RIS) aided communication scenario in which the RIS and the transmitter jointly send information to the receiver. While most studies of the RIS focus on its ability to beamform and boost the received signal-to-noise ratio (SNR), it is known that if the information data stream is also available at the RIS and can be modulated through the adjustable phases at the RIS, significant improvement in the multiplexing gain of the overall channel is possible. To achieve the theoretic multiplexing gain, this paper provides a symbol level precoding (SLP) approach for modulating data through the phases of the RIS. The SLP strategy is to set the received signal to be as close to the desired points in a constellation as possible. The idea is to directly make the received signal to be the symbols corresponding to the information to be transmitted and to design the transmitter and the reflective coefficients of the RIS so that the desired symbols are synthesized at the receiver. This strategy is formulated as an optimization problem and an augmented Lagrangian approach with the Riemannian conjugate gradient descent method is proposed to solve the optimization problem efficiently. Numerical simulation results show that the proposed method can achieve the theoretical multiplexing gain.