Assistive Communication System Research Articles

GAO–FCNN–Enabled Beamforming of the RIS–Assisted Intelligent Communication System

The joint beamforming optimization from the perspective of the bit error rate (BER) in a reconfigurable intelligent surface (RIS)–assisted intelligent communication system is studied in this paper. A genetic algorithm (GA) is investigated to address the bottleneck of the system performance based on the dynamic adaptability theory. However, the bottleneck is caused by the interaction between the active and passive beamforming. To tackle the constraints of conventional optimization approaches, the hybrid scheme is proposed to combine the GA optimization (GAO) and fully connected neural network (FCNN) strategy. Specifically, the intelligent collaborative tuning of system parameters is achieved using this proposed technique. Simulation findings indicate that the hybrid scheme not only simplifies the calculation process to obtain the optimal network parameters, but also effectively optimizes the system structure by dynamically adjusting the RIS reflection configuration. Based on this, the signal transmission quality is improved, interference is reduced, and the stable and efficient operation of the RIS–assisted intelligent communication system is ensured in the complex wireless transmission scenario.

Resource optimization of multi-UAV assisted communication system based on user scheduling

In order to improve the transmission rate of the multi-user mobile communication downlink wireless transmission system, a resource optimization method for multi-unmanned aerial vehicle (UAV) assisted communication system based on user scheduling and trajectory optimization is proposed. The proposed method establishes an optimization problem with the maximization of the total multi-user throughput as the criterion under the constraints of user scheduling, total energy consumption of UAVs and user service quality requirements. In order to solve this non-convex problem, the original non-convex problem is decomposed into three easy-to-handle non-convex sub-problems by using the block coordinate descent method (BCD). The sub-problems are transformed and solved by introducing slack variables, first-order Taylor expressions, continuous convex approximation (SCA) and other methods, and then alternately iteratively optimized to obtain an approximate suboptimal solution to the original non-convex problem. Simulation results show that the proposed algorithm can effectively improve the total system throughput and has good convergence in both single and multi-UAV communication systems.

Deep Bidirectional Learning Based Enhanced Outage Probability for Aerial Reconfigurable Intelligent Surface Assisted Communication Systems

Deep Bidirectional Learning Based Enhanced Outage Probability for Aerial Reconfigurable Intelligent Surface Assisted Communication Systems

Energy Efficient Symbol Level Precoding Design in a RIS Assisted Communication System

Energy Efficient Symbol Level Precoding Design in a RIS Assisted Communication System

Optimization for UAV-assisted simultaneous transmission and reception communications in the existence of malicious jammers

In this paper, we study an unmanned aerial vehicle (UAV)-assisted communication system, where the UAV is dispatched to implement simultaneous transmission and reception (STR) in the existence of multiple malicious jammers. Two schemes are investigated, namely frequency band-division-duplex (FDD) and time-fraction (TF). Based on the FDD scheme, the UAV can transmit information by using the portion of the bandwidth and receive information within the remaining portion of the bandwidth simultaneously. To perform the STR within the whole bandwidth, the TF-based scheme is considered by using a fraction of a time slot for the downlink, while the remaining fraction of the time slot is allocated for the uplink. We aim to maximize the worst-case throughput by optimizing the UAV three-dimensional (3D) trajectory and resource allocation for each scheme. The optimization problem is non-convex and thus computationally intractable. To handle the nonlinear problem, we use the block coordinate decomposition method to disaggregate the optimization problem into four subproblems and adopt the successive convex approximation technique to tackle non-convex problems. The simulation results demonstrate the performance of the TF-based scheme over the benchmark schemes.

Robust Beamforming Optimization Design for RIS-Aided MIMO Systems With Practical Phase Shift Model and Imperfect CSI

The ideal phase shift model and the acquisition of channel state information (CSI) are practically difficult to realize in reconfigurable intelligent surface (RIS) assisted communication systems. Therefore, these have greatly troubled the beamforming design of multiple-input multiple-output (MIMO) systems via RIS. This paper presents a robust beamforming design framework in the RIS-enhanced MIMO communication networks in the presence of considering practical phase shifts for the RIS and imperfect CSI of the cascade channels. More specifically, we propose an alternative optimization framework and adopt the distributed alternating direction method of multipliers (ADMM) method to solve the sum-rate maximization problem by combining the true environment model (TEM) and the mismatch environment model (MEM) with beamforming. In particular, the proposed scheme is also used for the MEM scenario. It shows that the sum rate of the ADMM scheme with MEM under low SNR is about 3 bps/Hz more than the BFP method, approximately 6 bps/Hz more than the APG method. Next, when the SNR is 5dB, the above three schemes are greater than SDR method. But, the above methods are smaller than SDR method in MEM. Then, the sum rate of the SDR method with the TEM is approximately 1.6 times of the MEM, while the CPU time of both is consistent with the computational complexity. Therefore, the differences between the two models affect the performance achieved by different methods. The proposed approach sheds a light to engineers working in wireless communication on enhancing the transmission robustness of existing wireless networks.

ASER analysis of DF relay assisted communication systems with diversity receiver at destination subject to Nakagami-m fading channels

ASER analysis of DF relay assisted communication systems with diversity receiver at destination subject to Nakagami-m fading channels

A Novel 6G ISAC Channel Model Combining Forward and Backward Scattering

The integrated sensing and communication (ISAC) refers to the integration of radio sensing and wireless communications to realize the multiplexing of space, time, and frequency resources. In the sixth generation (6G) wireless networks, ISAC is considered as one of the most promising technologies. In this paper, a novel ISAC channel model combining forward and backward scattering is proposed. In addition to the non-stationarity caused by motions, the correlations between sensing and communication channels are investigated. The channel characteristics of sensing such as forward scattering and backward scattering are introduced into the communication channel model. Utilizing the correlations between sensing and communication channels, the communication channel model is divided into line-of-sight (LOS), forward scattering, and backward scattering components. These three components are summed according to probability weighting to obtain a more accurate channel model for sensing assisted communication systems. Moreover, important statistical properties of the proposed ISAC channel model are derived and simulated. The analytical and simulation results match well, demonstrating the correctness of derivations and simulations. Some derived/simulated statistical properties are verified by corresponding measurement data, which indicates the utility of the proposed ISAC channel model.

Sensing Assisted Communication System Design Based on OTFS Waveforms

Sensing Assisted Communication System Design Based on OTFS Waveforms

Joint IRS Location and Size Optimization in Multi-IRS Aided Two-Way Full-Duplex Communication Systems

Intelligent reflecting surfaces (IRSs) have emerged as a promising wireless technology for the dynamic configuration and control of electromagnetic waves, thus creating a smart (programmable) radio environment. In this context, we study a multi-IRS assisted two-way communication system consisting of two users that employ full-duplex (FD) technology. More specifically, we deal with the joint IRS location and size (i.e., the number of reflecting elements) optimization in order to minimize an upper bound of system outage probability under various constraints: minimum and maximum number of reflecting elements per IRS, maximum number of installed IRSs, maximum total number of reflecting elements (implicit bound on the signaling overhead) as well as maximum total IRS installation cost. First, the problem is formulated as a discrete optimization problem and, then, a theoretical proof of its NP-hardness is given. Moreover, we provide a lower bound on the optimum value by solving a linear-programming relaxation (LPR) problem. Subsequently, we design two polynomial-time algorithms, a deterministic greedy algorithm and a randomized approximation algorithm, based on the LPR solution. The former is a heuristic method that always computes a feasible solution for which (a posteriori) performance guarantee can be provided. The latter achieves an approximate solution, using randomized rounding, with provable (a priori) probabilistic guarantees on the performance. Furthermore, extensive numerical simulations demonstrate the superiority of the proposed algorithms compared to the baseline schemes. Finally, useful conclusions regarding the comparison between FD and conventional half-duplex (HD) systems are also drawn.

Robust Beamforming for Sensing Assisted Integrated Communication and Jamming Systems

This paper investigates the robust beamforming design problem in a sensing assisted integrated communication and jamming (ICAJ) system, which aims to minimize the transmission energy consumption in a time duration while ensuring the communication requirements for multiple legitimate users and jamming demands for the suspicious network with multiple communication groups. To achieve these goals, we first design a sensing-communication and jamming (SCJ) protocol. Then, a robust beamforming design problem with both communication and jamming channel state information (CSI) estimation error is formulated as a non-convex optimization. To solve it, a joint optimization (JO) algorithm is developed to jointly optimize the beamforming matrices of communication and jamming, by leveraging the General S-procedure, Schur' complement and General Sign-definiteness techniques. Simulation results show that the proposed SCJ protocol with JO algorithm has superior performance, as compared to benchmark methods.

Doppler Shift and Channel Estimation for Intelligent Transparent Surface Assisted Communication Systems on High-Speed Railways

The critical distinction between the emerging intelligent transparent surface (ITS) and intelligent reflection surface (IRS) is that the incident signals can penetrate the ITS instead of being reflected, which enables the ITS to combat the severe signal penetration loss for high-speed railway (HSR) wireless communications. This paper thus investigates the channel estimation problem for an ITS-assisted HSR network where the ITS is embedded into the carriage window. We first formulate the channels as functions of physical parameters, and thus transform the channel estimation into a parameter recovery problem. Next, we design the first two pilot blocks within each frame and develop a serial low-complexity channel estimation algorithm. Specifically, the channel estimates are initially obtained, and each estimate is further expressed as the sum of its perfectly known value and the estimation error. By leveraging the relationship between channels for the two pilot blocks, we recover the Doppler shifts from the channel estimates, based on which we can further acquire other channel parameters. Moreover, the Cramer-Rao lower bound (CRLB) for each parameter is derived as a performance benchmark. Finally, we provide numerical results to establish the effectiveness of our proposed estimators.

Downlink channel estimation of intelligent reflective surface aided MU-MIMO system

Obtaining channel status information (CSI) is one of the main problems of the intelligent reflective surface (IRS) assisted communication system. This is because IRS has only a large number of passive reflective components and cannot process signals. In this paper, we aim to estimate downlink channel of IRS assisted multi-user multiple-input multiple-output (MU-MIMO) communication system. In time division duplex (TDD) mode, the downlink channel is estimated according to the uplink pilot by using channel reciprocity. We propose a parallel factor analysis based on projection subspace (PSS-PARAFAC) channel estimation scheme. In the first step, the common sparsity among multiple users is used for signal subspace projection to reduce noise energy and complexity. The second step is to convert each user signal received of base station (BS) into the PARAFAC problem. The iterative method of alternating least squares (ALS) is used to solve this problem. From the analysis of simulation results, the channel estimation performance of the proposed algorithm is better.

Achievable rate as affected by active elements distribution in reconfigurable intelligent surfaces for wireless communication.

To increase constantly the achievable rate of reconfigurable intelligent surfaces (RISs)-assisted communication systems, the traditional approaches are to deploy a few active elements randomly on the passive RISs. However, the effect of the geometry distribution of the deployment of the active elements is ignored in performance analysis. In this article, three types of geometry distribution with active elements on RISs, denoted as random distribution, uniform distribution, and eight-queens distribution, are discussed to analyze the affect on achievable rate in RISs-assisted wireless communications. Specifically, the optimal achievable rate is obtained according to the predefined codebook, and the codebook is determined by the reflection beamforming codeword related to the active elements geometry distribution in RISs. Simulation results show that different geometry distribution of active elements in RISs causes different influences to achievable rates. The eight-queens distribution proposed in this article for active elements in RISs brings the highest achievable rate compared with random distribution and uniform distribution. In the passive RISs surface, the distribution of a few active elements is limited by the eight-queens, further enhancing the achievable rate of the wireless communication system. This method has a 7% improvement over the conventional method.

Distributed Beam Tracking for Vehicular Communications via UAV-Assisted Cellular Network

In this paper, we propose a distributed beam tracking scheme for millimeter-wave unmanned aerial vehicle (UAV)-assisted communication systems. In the considered systems, aerial node base (aNB) connects the ground vehicles (GV) through directive beams to mitigate the path loss. However, line-of-sight (LoS) blockage may result in the link disconnection, which leads to the corruption of observations. To solve this issue, we extend the one-to-one beam tracking into the multi-node cooperative beam tracking scheme. For the multi-node cooperative problem, we develop the distributed extended Kalman filter (EKF)-based beam tracking to overcome the high nonlinearity and field-of-view (FoV) limitation of the observation model. While the multi-node cooperation scheme alleviates the corruptions of the observations, it may cause the error propagation between neighbor nodes. Thus, we incorporate the resilient network control into the proposed scheme. Consequently, a distributed EKF-based multi-node cooperative beam tracking protocol is proposed for the correction of corrupted observations and link stability. From our comprehensive simulation, the result of the proposed scheme shows 87.07% error reduction compared to the single node method. This improvement is comparable to the result of the centralized method (91.28% error reduction), and the proposed scheme also has the advantage of scalability.

Performance Evaluation of SSK Modulation Over Shadowed-Rician Land Mobile Satellite Links

We investigate the performance of satellite communication systems acquiring the space shift keying (SSK) modulation technique over shadowed-rician (SR) land mobile satellite (LMS) link. Specifically, we discuss the analytical performance of the considered system over independent and identically distributed SR fading channels in terms of symbol error rate (SER), diversity order, and average capacity. The SER of the considered set-up is derived by utilizing moment generating function (MGF) expression over the SR fading LMS communication links. The analytical diversity order of the scheme is derived by using SER expression. We consider the effect of elevation angles on the SER performance, diversity order, and channel capacity of the considered SSK-assisted satellite communication system. As observed from simulation and analytical results, the performance of the considered set-up can be raised by improving elevation angles. Further, a closed-form expression of the average capacity of the SSK assisted satellite communication system is also derived. It is shown through simulation and analysis that the fading conditions and elevation angle does not affect the diversity order of the system, but it adversely acts on the SER performance and average capacity of the system.

Max-Min Energy-Efficiency Fair Optimization in STAR-RIS Assisted Communication System

Max-Min Energy-Efficiency Fair Optimization in STAR-RIS Assisted Communication System

Optimal Element Allocation for RIS-Aided Physical Layer Security

In this paper, we investigate an innovative physical layer security (PLS) scheme for an uncertain reconfigurable intelligent surface- (RIS-) assisted communication system under eavesdropping attack. Specifically, in our proposed system, we consider that the uncertain RIS is known to the legitimate user while not to the eavesdropper (Eve). In this manner, the reflective elements of the uncertain RIS are adjusted to strengthen the keen signals for the legitimate user while suppressing the signals for Eve via jamming. We analyze the system by assuming legitimate and wiretap channels, respectively, where the secrecy capacity maximization problem is formulated and its exact closed-form expression is derived. Simulation results verifying the accuracy of our analysis demonstrate the validity and superiority of the uncertain RIS-assisted communication system against its counterparts.

Secrecy Rate Analysis of Randomized Radiation for Intelligent Reflecting Surface-Aided Communication Systems

We consider an intelligent reflecting surface (IRS)-assisted communication system as a cost-effective technique to enhance secrecy rate performance in physical-layer security (PLS) systems. In this letter, the randomized radiation (RR)-based PLS algorithm, which uses active antenna arrays to randomize the radiation pattern, is adopted in IRS through passive beamforming. We show that RR cannot be simply applied to IRS because the secrecy rate is subject to the phase-dependent amplitude variations in IRS. Therefore, we provide an exact and closed-form expression for the secrecy rate of RR using IRS. Based on the analysis, we introduce a constant phase shift into the IRS elements and identify it as a key parameter to optimize the secrecy performance through a genetic algorithm.

Passive Beamforming for 3-D Coverage in IRS-Assisted Communications

In this letter, we study the passive beamforming design for optimizing the three-dimensional (3-D) coverage performance in an intelligent reflecting surface (IRS)-assisted communication system. In particular, we maximize the minimum (i.e., max-min) beamforming gain over all locations in the target area by jointly optimizing the passive reflection of all IRS elements. The resulting problem has a non-convex and semi-infinite beamforming gain constraint and a non-convex constant-modulus constraint. Both of them are reformulated to be finite and convex in the lifted matrix space with an additional rank-one constraint, and a difference-of-convex technique is developed to solve the reformulated problem efficiently. Finally, we demonstrate that the proposed passive beamforming solution outperforms the existing methods and can approach the upper bound on the max-min beamforming gain.