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Qingqing Wu

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Joint Beamforming and Power Allocation for RIS Aided Full-Duplex Integrated Sensing and Uplink Communication System

Sep 07, 2023
Yuan Guo, Yang Liu, Qingqing Wu, Xiaoyang Li, Qingjiang Shi

Integrated sensing and communication (ISAC) capability is envisioned as one key feature for future cellular networks. Classical half-duplex (HD) radar sensing is conducted in a "first-emit-then-listen" manner. One challenge to realize HD ISAC lies in the discrepancy of the two systems' time scheduling for transmitting and receiving. This difficulty can be overcome by full-duplex (FD) transceivers. Besides, ISAC generally has to comprise its communication rate due to realizing sensing functionality. This loss can be compensated by the emerging reconfigurable intelligent surface (RIS) technology. This paper considers the joint design of beamforming, power allocation and signal processing in a FD uplink communication system aided by RIS, which is a highly nonconvex problem. To resolve this challenge, via leveraging the cutting-the-edge majorization-minimization (MM) and penalty-dual-decomposition (PDD) methods, we develop an iterative solution that optimizes all variables via using convex optimization techniques. Besides, by wisely exploiting alternative direction method of multipliers (ADMM) and optimality analysis, we further develop a low complexity solution that updates all variables analytically and runs highly efficiently. Numerical results are provided to verify the effectiveness and efficiency of our proposed algorithms and demonstrate the significant performance boosting by employing RIS in the FD ISAC system.

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Reconfigurable Intelligent Surface Aided Space Shift Keying With Imperfect CSI

Sep 06, 2023
Xusheng Zhu, Wen Chen, Qingqing Wu, Zhendong Li, Jun Li, Shunqing Zhang, Ming Ding

In this paper, we investigate the performance of reconfigurable intelligent surface (RIS)-aided spatial shift keying (SSK) wireless communication systems in the presence of imperfect channel state information (CSI). Specifically, we analyze the average bit error probability (ABEP) of two RIS-SSK systems respectively based on intelligent reflection and blind reflection of RIS. For the intelligent RIS-SSK scheme, we first derive the conditional pairwise error probability of the composite channel through maximum likelihood (ML) detection. Subsequently, we derive the probability density function of the combined channel. Due to the intricacies of the composite channel formulation, an exact closed-form ABEP expression is unattainable through direct derivation. To this end, we resort to employing the Gaussian-Chebyshev quadrature method to estimate the results. In addition, we employ the Q-function approximation to derive the non-exact closed-form expression when CSI imperfections are present. For the blind RIS-SSK scheme, we derive both closed-form ABEP expression and asymptotic ABEP expression with imperfect CSI by adopting the ML detector. To offer deeper insights, we explore the impact of discrete reflection phase shifts on the performance of the RIS-SSK system. Lastly, we extensively validate all the analytical derivations using Monte Carlo simulations.

* arXiv admin note: text overlap with arXiv:2307.01994 
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On the Performance of RIS-Aided Spatial Scattering Modulation for mmWave Transmission

Aug 31, 2023
Xusheng Zhu, Wen Chen, Zhendong Li, Qingqing Wu, Ziheng Zhang, Kunlun Wang, Jun Li

In this paper, we investigate a state-of-the-art reconfigurable intelligent surface (RIS)-assisted spatial scattering modulation (SSM) scheme for millimeter-wave (mmWave) systems, where a more practical scenario that the RIS is near the transmitter while the receiver is far from RIS is considered. To this end, the line-of-sight (LoS) and non-LoS links are utilized in the transmitter-RIS and RIS-receiver channels, respectively. By employing the maximum likelihood detector at the receiver, the conditional pairwise error probability (CPEP) expression for the RIS-SSM scheme is derived under the two scenarios that the received beam demodulation is correct or not. Furthermore, the union upper bound of average bit error probability (ABEP) is obtained based on the CPEP expression. Finally, the derivation results are exhaustively validated by the Monte Carlo simulations.

* arXiv admin note: substantial text overlap with arXiv:2307.14662 
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Intelligent Reflecting Surface Aided Multi-Tier Hybrid Computing

Aug 18, 2023
Yapeng Zhao, Qingqing Wu, Guangji Chen, Wen Chen, Ruiqi Liu, Ming-Min Zhao, Shaodan Ma, Yuan Wu

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The Digital twin edge network (DITEN) aims to integrate mobile edge computing (MEC) and digital twin (DT) to provide real-time system configuration and flexible resource allocation for the sixth-generation network. This paper investigates an intelligent reflecting surface (IRS)-aided multi-tier hybrid computing system that can achieve mutual benefits for DT and MEC in the DITEN. For the first time, this paper presents the opportunity to realize the network-wide convergence of DT and MEC. In the considered system, specifically, over-the-air computation (AirComp) is employed to monitor the status of the DT system, while MEC is performed with the assistance of DT to provide low-latency computing services. Besides, the IRS is utilized to enhance signal transmission and mitigate interference among heterogeneous nodes. We propose a framework for designing the hybrid computing system, aiming to maximize the sum computation rate under communication and computation resources constraints. To tackle the non-convex optimization problem, alternative optimization and successive convex approximation techniques are leveraged to decouple variables and then transform the problem into a more tractable form. Simulation results verify the effectiveness of the proposed algorithm and demonstrate the IRS can significantly improve the system performance with appropriate phase shift configurations. Moreover, the results indicate that the DT assisted MEC system can precisely achieve the balance between local computing and task offloading since real-time system status can be obtained with the help of DT. This paper proposes the network-wide integration of DT and MEC, then demonstrates the necessity of DT for achieving an optimal performance in DITEN systems through analysis and numerical results.

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Hierarchical Codebook Design and Analytical Beamforming Solution for IRS Assisted Communication

Aug 03, 2023
Xiyuan Liu, Qingqing Wu, Die Hu, Rui Wang, Jun Wu

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In intelligent reflecting surface (IRS) assisted communication, beam search is usually time-consuming as the multiple-input multiple-output (MIMO) of IRS is usually very large. Hierarchical codebooks is a widely accepted method for reducing the complexity of searching time. The performance of this method strongly depends on the design scheme of beamforming of different beamwidths. In this paper, a non-constant phase difference (NCPD) beamforming algorithm is proposed. To implement the NCPD algorithm, we first model the phase shift of IRS as a continuous function, and then determine the parameters of the continuous function through the analysis of its array factor. Then, we propose a hierarchical codebook and two beam training schemes, namely the joint searching (JS) scheme and direction-wise searching (DWS) scheme by using the NCPD algorithm which can flexibly change the width, direction and shape of the beam formed by the IRS array. Simulation results show that the NCPD algorithm is more accurate with smaller side lobes, and also more stable on IRS of different sizes compared to other wide beam algorithms. The misalignment rate of the beam formed by the NCPD method is significantly reduced. The time complexity of the NCPD algorithm is constant, thus making it more suitable for solving the beamforming design problem with practically large IRS.

* 33 pages, 11 figures 
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Multi-Objective Optimization for UAV Swarm-Assisted IoT with Virtual Antenna Arrays

Aug 03, 2023
Jiahui Li, Geng Sun, Lingjie Duan, Qingqing Wu

Unmanned aerial vehicle (UAV) network is a promising technology for assisting Internet-of-Things (IoT), where a UAV can use its limited service coverage to harvest and disseminate data from IoT devices with low transmission abilities. The existing UAV-assisted data harvesting and dissemination schemes largely require UAVs to frequently fly between the IoTs and access points, resulting in extra energy and time costs. To reduce both energy and time costs, a key way is to enhance the transmission performance of IoT and UAVs. In this work, we introduce collaborative beamforming into IoTs and UAVs simultaneously to achieve energy and time-efficient data harvesting and dissemination from multiple IoT clusters to remote base stations (BSs). Except for reducing these costs, another non-ignorable threat lies in the existence of the potential eavesdroppers, whereas the handling of eavesdroppers often increases the energy and time costs, resulting in a conflict with the minimization of the costs. Moreover, the importance of these goals may vary relatively in different applications. Thus, we formulate a multi-objective optimization problem (MOP) to simultaneously minimize the mission completion time, signal strength towards the eavesdropper, and total energy cost of the UAVs. We prove that the formulated MOP is an NP-hard, mixed-variable optimization, and large-scale optimization problem. Thus, we propose a swarm intelligence-based algorithm to find a set of candidate solutions with different trade-offs which can meet various requirements in a low computational complexity. We also show that swarm intelligence methods need to enhance solution initialization, solution update, and algorithm parameter update phases when dealing with mixed-variable optimization and large-scale problems. Simulation results demonstrate the proposed algorithm outperforms state-of-the-art swarm intelligence algorithms.

* This paper has been accepted by IEEE Transactions on Mobile Computing 
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Cooperative Cellular Localization with Intelligent Reflecting Surface: Design, Analysis and Optimization

Jul 28, 2023
Kaitao Meng, Qingqing Wu, Wen Chen, Deshi Li

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Autonomous driving and intelligent transportation applications have dramatically increased the demand for high-accuracy and low-latency localization services. While cellular networks are potentially capable of target detection and localization, achieving accurate and reliable positioning faces critical challenges. Particularly, the relatively small radar cross sections (RCS) of moving targets and the high complexity for measurement association give rise to weak echo signals and discrepancies in the measurements. To tackle this issue, we propose a novel approach for multi-target localization by leveraging the controllable signal reflection capabilities of intelligent reflecting surfaces (IRSs). Specifically, IRSs are strategically mounted on the targets (e.g., vehicles and robots), enabling effective association of multiple measurements and facilitating the localization process. We aim to minimize the maximum Cram\'er-Rao lower bound (CRLB) of targets by jointly optimizing the target association, the IRS phase shifts, and the dwell time. However, solving this CRLB optimization problem is non-trivial due to the non-convex objective function and closely coupled variables. For single-target localization, a simplified closed-form expression is presented for the case where base stations (BSs) can be deployed flexibly, and the optimal BS location is derived to provide a lower performance bound of the original problem ...

* 14 pages, This work has been submitted to IEEE for possible publication 
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Deep Reinforcement Learning Based Intelligent Reflecting Surface Optimization for TDD MultiUser MIMO Systems

Jul 28, 2023
Fengyu Zhao, Wen Chen, Ziwei Liu, Jun Li, Qingqing Wu

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In this letter, we investigate the discrete phase shift design of the intelligent reflecting surface (IRS) in a time division duplexing (TDD) multi-user multiple input multiple output (MIMO) system.We modify the design of deep reinforcement learning (DRL) scheme so that we can maximizing the average downlink data transmission rate free from the sub-channel channel state information (CSI). Based on the characteristics of the model, we modify the proximal policy optimization (PPO) algorithm and integrate gated recurrent unit (GRU) to tackle the non-convex optimization problem. Simulation results show that the performance of the proposed PPO-GRU surpasses the benchmarks in terms of performance, convergence speed, and training stability.

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Performance of RIS-Assisted Full-Duplex Space Shift Keying With Imperfect Self-Interference Cancellation

Jul 27, 2023
Xusheng Zhu, Wen Chen, Qingqing Wu, Ziwei Liu, Jun Li

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In this paper, we consider a full-duplex (FD) space shift keying (SSK) communication system, where information exchange between two users is assisted only by a reconfigurable intelligent surface (RIS). In particular, the impact of loop interference (LI) between the transmit and receive antennas as well as residual self-interference (SI) from the RIS is considered. Based on the maximum likelihood detector, we derive the conditional pairwise error probability and the numerical integration expression for the unconditional pairwise error probability (UPEP). Since it is difficult to find a closed-form solution, we perform accurate estimation by the Gauss-Chebyshev quadrature (GCQ) method. To gain more useful insights, we derive an expression for UPEP in the high signal-to-noise ratio region and further give the average bit error probability (ABEP) expression. Monte Carlo simulations were performed to validate the derived results. It is found that SI and LI have severe impacts on system performance. Fortunately, these two disturbances can be well counteracted by increasing the number of RIS units.

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RIS-Aided Spatial Scattering Modulation for mmWave MIMO Transmissions

Jul 27, 2023
Xusheng Zhu, Wen Chen, Zhendong Li, Qingqing Wu, Ziheng Zhang, Kunlun Wang, Jun Li

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This paper investigates the reconfigurable intelligent surface (RIS) assisted spatial scattering modulation (SSM) scheme for millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems, in which line-of-sight (LoS) and non-line-of-sight (NLoS) paths are respectively considered in the transmitter-RIS and RIS-receiver channels. Based on the maximum likelihood detector, the conditional pairwise error probability (CPEP) expression for the RIS-SSM scheme is derived under the two cases of received beam correct and demodulation error. Furthermore, we derive the closed-form expressions of the unconditional pairwise error probability (UPEP) by employing two different methods: the probability density function and the moment-generating function expressions with a descending order of scatterer gains. To provide more useful insights, we derive the asymptotic UPEP and the diversity gain of the RIS-SSM scheme in the high SNR region. Depending on UPEP and the corresponding Euclidean distance, we get the union upper bound of the average bit error probability (ABEP). A new framework for ergodic capacity analysis is also provided to acquire the proposed system's effective capacity. Finally, all derivation results are validated via extensive Monte Carlo simulations, revealing that the proposed RIS-SSM scheme outperforms the benchmarks in terms of reliability.

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