Beamforming Design Research Articles

Joint Beamforming Design of Physical Layer Security Transmission for IRS Assisted V2V Communication

Joint Beamforming Design of Physical Layer Security Transmission for IRS Assisted V2V Communication

Joint Beamforming Design and User Clustering Algorithm in NOMA-Assisted ISAC Systems.

To enhance the performance of non-orthogonal multiple access (NOMA)-assisted integrated sensing and communication (ISAC) systems in multi-user distributed scenarios, an improved Gaussian Mixture Model (GMM)-based user clustering algorithm is proposed. This algorithm is tailored for ISAC systems, significantly improving bandwidth reuse gains and reducing serial interference. First, using the Sum of Squared Errors (SSE), the algorithm reduces sensitivity to the initial cluster center locations, improving clustering accuracy. Then, direction weight factors are introduced based on the base station position and a penalty function involving users' Euclidean distances and sensing power. Modifications to the EM algorithm in calculating posterior probabilities and updating the covariance matrix help align user clusters with the characteristics of NOMAISAC systems. This improves users' interference resistance, lowers decoding difficulty, and optimizes the system's sensing capabilities. Finally, a fractional programming (FP) approach addresses the non-convex joint beamforming design problem, enhancing power and channel gains and achieving co-optimizing sensing and communication signals. The simulation results show that, under the improved GMM user clustering algorithm and FP optimization, the NOMA-ISAC system improves user spectral efficiency by 4.3% and base station beam intensity by 5.4% compared to traditional ISAC systems.

UAV-mounted IRS assisted wireless powered mobile edge computing systems: Joint beamforming design, resource allocation and position optimization

Intelligent reflecting surface (IRS) and unmanned aerial vehicle (UAV) have been recently used in wireless-powered mobile edge computing (MEC) systems to enhance the computation bits and energy harvesting performance. However, in the conventional IRS- and UAV-aided MEC systems, the IRS is installed at fixed locations on a building, which restricts the computation performance. UAV-mounted IRS (UAV-IRS), as a promising technology, combines the advantages of UAV and IRS. Hence, in this work, we study a UAV-IRS wireless-powered MEC system, where multiple UAV-IRSs are considered between Internet of Things (IoT) devices and the base station to improve the computation bits and energy harvesting. The multi-antenna base station first charges the IoT devices via radio frequency signals, and then IoT devices offload their computation tasks to the base station via UAV-IRSs. We formulate a computation bits maximization problem for all IoT devices by jointly determining detection beamforming at IoT devices, active energy beamforming at the base station, power allocation, time slot assignment, CPU frequency, the phase shifts design in the wireless energy transfer (WET) and task offloading, and UAV-IRSs positions. A block coordinate descent (BCD) algorithm by decomposing the introduced problem into four blocks is proposed, while the detection beamforming, active energy beamforming, transmit power, time slot assignment, CPU frequency, and the phase shifts design in the task offloading are derived in closed-form results. Also, the successive convex approximation and semidefinite relaxation (SDR) are adopted to obtain the UAV-IRS positions and the phase shifts in the WET, respectively. The simulation results verify the effectiveness of the presented BCD method compared with the different benchmark schemes.

Joint LPI waveform and passive beamforming design for FDA-MIMO-DFRC systems

Dual-functional Radar-Communication (DFRC) systems have been recognized as one of the most promising technologies in the field of wireless communications. Nevertheless, the low probability of intercept (LPI) performance in the DFRC systems cannot be overlooked. Based on the frequency diverse array multiple-input–multiple output (FDA-MIMO) radar, a DFRC system is proposed to enhance target detection in clutter environment and achieve desirable LPI against an underlying hostile interceptor. The issue can be cast into an optimization problem that maximizes the radar signal-to-interference-plus-noise ratio (SINR) while satisfying the communication quality-of-service (QoS) requirement of each user under one of three metrics, the required LPI performance and the constant-modulus waveform constraint. To solve this challenging problem, we reformulate it into an equivalent but more tractable form by resorting to an auxiliary variable. Subsequently, we employ the alternative direction method of multipliers (ADMM) and majorization-minimization (MM) algorithms to solve the resultant problem. Simulation results validate that the proposed LPI FDA-MIMO-DFRC scheme exhibits superior sensing performance over the conventional scheme with MIMO.

Transmission design for ISAC‐WPT backscatter RFID systems

AbstractIn this letter, a novel integrated sensing and communication (ISAC) scenario with wireless power transfer (ISAC‐WPT) is investigated. In this new setup, an access point simultaneously employs communication and sensing beams to serve a communication user, detect an RFID tag, and power an energy receiver. The objective is to design the sensing and communication beams to minimize the total transmit power while satisfying the requirements of tag detection, communication, and energy harvesting. To address the corresponding non‐convex problem, the constraints are reformulated into convex second‐order cone constraints, thereby obtaining the globally optimal solution. To further reduce computational complexity, zero‐forcing is employed to design the beamforming vectors, followed by solving a convex optimization problem to determine the optimal power allocation between sensing and communication beams. The simulation results demonstrate the effectiveness of the proposed beamforming designs, highlighting the potential of ISAC‐WPT Backscatter RFID systems.

Line-of-Sight MIMO Systems: DoF Analysis and Hybrid Beamforming Design

Line-of-Sight MIMO Systems: DoF Analysis and Hybrid Beamforming Design

Joint beamforming design for STAR-RIS-assisted integrated sensing, communication, and power transfer systems

In the sixth-generation network, many low-power devices are predicted to be integrated into tasks incorporating communication and sensing. The integrated sensing and communication (ISAC) technology reuses a wireless signal for data transfer and radar sensing. Furthermore, wireless signals have the capacity to transmit energy, allowing for the simultaneous wireless information and power transfer (SWIPT). To enhance spectrum utilization, the deeper integration of SWIPT and ISAC has opened up novel investigate directions for integrated sensing, communication, and power transfer (ISCPT). This paper investigates a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) supported ISCPT system that solves the problem of traditional RIS not achieving full space wireless signal coverage. In particular, since the serious path loss issue of sensing, we propose a novel architecture for installing dedicated sensors on STAR-RIS. Under this setting, we jointly optimized the passive beamforming at STAR-RIS and the active beamforming at base station to minimize the Cramér-Rao bound (CRB) used to estimate the sensing target's two-dimensional direction of arrivals, while being constrained by the lowest signal-to-interference-plus-noise-ratio (SINR) of communication users (CUs), the lowest energy harvesting (EH) of energy users (EUs), and the maximum transmission power at base station. For complex non-convex problems, a proposed two-layer cyclic algorithm utilizes penalty dual decomposition (PDD) and block coordinate descent (BCD). Finally, the numerical outcomes verify the efficacy of our suggested design, which reveals the performance trade-off between communication, power transmission and sensing. Furthermore, compared to traditional RIS, the estimated CRB of this design is lower.

Deep Learning-Based Joint Beamforming Design for Multi-Hop Reconfigurable Intelligent Surface (RIS)-Aided Communication Systems

Reconfigurable intelligent surface (RIS) is one of the promising technologies for sixth generation communications due to its advantages including energy saving, high spectral efficiency, etc. However, the non-convex joint beamforming design is a challenge, especially in the multi-hop RIS-assisted communication system. This paper proposes a deep learning-based joint beamforming (DLBF) design, aiming to maximize the system data rate for multi-hop RIS-aided communication systems. The proposed DLBF design consists of the reflection matrices design of all RISs and the transmit beamforming design at the base station, which has a reduced computational complexity. Numerical results show that the proposed DLBF can achieve 1.8 bit/s/Hz sum rate gain compared to the conventional beamforming method for the two-user scenario, which can be enhanced by large-scale users. The sum rate performance can be improved by increasing the number of RISs due to the reflection gain, and corresponding results provide a guidance of the multi-hop number selection for further investigation.

Distributed beamforming design for UAV‐based integrated communication and jamming systems

AbstractThe integrated communication and jamming system is proposed by exploiting the diversity gain and flexible deployment of unmanned aerial vehicle (UAV)‐based distributed multiple input multiple output technology, which is expected to gain higher spectral efficiency and system scalability. This paper designs transmit beamforming of multiple UAVs so that they can simultaneously impose jamming signal to jamming targets and communication signal to communication users at the same frequency. The aim is to maximize the total jamming effect of all jamming targets while achieving a certain communication rate of communication users by optimizing the transmit beamforming matrices. Two cases are considered in which the UAV swarm works in clock synchronization and clock asynchronization. Specifically, the problem is formulated into a non‐convex optimization in the synchronous case. A near optimal solution is derived by decoupling the beamforming matrix into multi‐user interference suppression matrix and single‐user beamforming matrix. In the asynchronous case, the transmitter–receiver matching relation needs to consider and multiple optimization variables are highly coupled, penalty factors and intermediate variables to convert the optimization problem to convex programming are introduced. The simulation results show that the proposed beamforming design algorithm coordinates the communication and jamming signal rationally and outperforms the conventional beamforming design algorithms.

Joint active and passive beamforming design in intelligent reflecting surface (IRS)-assisted covert communications: A multi-agent DRL approach

Joint active and passive beamforming design in intelligent reflecting surface (IRS)-assisted covert communications: A multi-agent DRL approach

Exploiting RIS in Secure Beamforming Design for NOMA-Assisted Integrated Sensing and Communication

Exploiting RIS in Secure Beamforming Design for NOMA-Assisted Integrated Sensing and Communication

Integrating Sensing, Communication, and Power Transfer: Multiuser Beamforming Design

Integrating Sensing, Communication, and Power Transfer: Multiuser Beamforming Design

Robust secure beamforming design in cognitive satellite communication for coexistence with terrestrial networks

This paper examines the scope of physical layer security (PLS) enabled in cognitive satellite communication for co-existence with terrestrial networks. The primary concern is to ensure secure information transmission from a Satellite Earth Station to a GEO Satellite while safeguarding against potential eavesdropping from a Spacecraft. To this end, an optimization problem is formulated, considering the inherent imperfections in the channel state information (CSI). The aim is to maximize the achievable secrecy rate while adhering to specific constraints on transmit power and interference at the nearby Fixed Service transmitter. This optimization task involves fine-tuning the beamforming vectors at the Satellite Earth Station transmitter. Due to the mathematical complexity of the formulated problem, the Semidefinite Relaxation (SDR) technique is employed. This conversion technique transforms the initial non-convex problem into a tractable one, allowing the derivation of beamforming weight vectors. Finally, simulation results are presented to confirm the effectiveness of the robust beamforming scheme. To the best of our knowledge, this study potentially marks the first attempt at developing a robust, secure beamforming strategy for uplink transmission in the forthcoming era of satellite communications. Its aim is to enable spectral coexistence with nearby terrestrial networks.

On Beamforming with the Single-Sideband Transform

In this paper, we examine the use of the Single-Sideband Transform (SSBT) for convolutive beamformers. We explore its unique properties and implications for beamformer design. Our study sheds light on the tradeoffs involved in using the SSBT in beamforming applications, offering insights into both its strengths and limitations. Despite the advantage of having real-valued coefficients, we show that the convolution handling of the transform presents challenges that impact fundamental beamforming principles. When compared to the Short-Time Fourier Transform (STFT), the SSBT displays lower robustness, especially in scenarios involving mismatch and modeling noise. Notably, we establish a direct equivalence between the SSBT and STFT when using identical transform parameters, enabling their seamless interchangeability and joint use in time–frequency signal enhancements. We validate our theoretical findings through realistic simulations using the Minimum-Power Distortionless Response beamformer. These simulations illustrate that although the STFT performs marginally better than the SSBT under optimal conditions, it outperforms significantly in non-ideal scenarios.

A low-complexity ADMM-based secure beamforming for IRS-assisted uplink cognitive radio networks with NOMA

Intelligent reflecting surface (IRS) and non-orthogonal multiple access (NOMA) are both powerful means to improve the spectrum efficiency and can assist the cognitive radio network (CRN) in achieving more effective spectrum allocation. However, spectrum sharing in CRNs and the utilization of the scarce bandwidth in NOMA make it vulnerable to security threats. The secure beamforming design in IRS-assisted CRNs with NOMA is complicated and non-convex. Traditional semidefinite relaxation along with Gaussian randomization (SDR-GR) algorithm can solve the non-convex problem, however a high computational complexity. This paper proposes an alternating direction method of multipliers (ADMM)-based sum secrecy rate maximization (A-SSRM) scheme to achieve secure transmission with low computation complexity in IRS-assisted uplink CRNs with NOMA. Specifically, we derive an appropriate transformation of the original problem based on the ADMM framework and decompose it into multiple sub-problems, which are carefully designed to have closed-form solutions. Furthermore, an eavesdropper zero forcing (EZF)-based sub-optimal scheme is presented. Simulation results reveal that our proposed A-SSRM scheme outperforms other benchmarks in terms of sum secrecy rate and reduces the average running time by 6 times compared with the traditional SDR-GR algorithm. This is attributed to our effective decoupling and decomposing of the original problem, which enables each sub-problem to obtain a simple closed-form solution through derivation.

Sparse Design of Polynomial Beamformers by Jointly Sparsifying Sensor Locations and Farrow Structures

Sparse Design of Polynomial Beamformers by Jointly Sparsifying Sensor Locations and Farrow Structures

Anti-Jamming Hybrid Beamforming Design for Millimeter-Wave Massive MIMO Systems

Anti-Jamming Hybrid Beamforming Design for Millimeter-Wave Massive MIMO Systems

Secure RIS-Assisted Hybrid Beamforming Design With Low-Resolution Phase Shifters

Secure RIS-Assisted Hybrid Beamforming Design With Low-Resolution Phase Shifters

Beamforming design for Star-RIS assisted secure wireless communication system under hardware impairments

Simultaneous transmission and reflection reconfigurable intelligent surface (Star-RIS) has been recently introduced as one of the hopeful technologies in future communications. In this work, we investigate a beamforming design for Star-RIS-assisted secure wireless communications with two practical protocols, namely energy splitting (ES) and mode switching (MS). We assume that our transceivers are not ideal and have residual hardware impairments that lead to distortion noise. We aim to maximize the total secrecy rate by optimizing the beamforming in BS and Star-RIS under the limitation of transmission power consumption. The proposed non-convex optimization problem is solved via successive convex approximation and alternating optimization.

Secure beamforming design for MISO URLLC networks in IoT applications

This paper investigates joint beamforming and artificial noise (AN) design for secure multiple-input single-output (MISO) ultra-reliable and low latency communication (URLLC) networks in Internet of Things (IoT) applications. In considered system, a base station (BS) transmits confidential information for individual IoT users using the short-packet communication technique under the wiretap of eavesdroppers. To enhance physical layer security, the BS injects additional dedicated AN symbols to degrade the information retrieval ability at eavesdroppers. In this paper, we aim to joint design the transmit beamforming and AN symbol to maximize the minimum URLLC secrecy rate of IoT user subject to the power budget of the BS. The optimization design problem is highly nonconvex due to coupled variables in the URLLC secrecy rate and channel dispersion expressions, and thus it is mathematically challenging to solve this problem directly. To overcome this issue, we first introduce various convex inner approximations to convexify the nonconvex terms, and then we develop an efficient iterative algorithm based on the sequential convex programming approach. Extensive numerical simulation results are conducted to investigate the URLLC secrecy rate region. In conclusion, the two new URLLC parameters, i.e., the transmit packet blocklength and block error probability, will cause the considerable degradation on the URLLC secrecy rate region when comparing to that of the traditional beamforming design based on the Shannon capacity.