Beamforming Design Research Articles

Optimization-Driven DRL-Based Joint Beamformer Design for IRS-Aided ITSN Against Smart Jamming Attacks

This paper investigates an intelligent reflecting surfaces (IRS) aided anti-jamming communication strategy in the integrated terrestrial-satellite network (ITSN), where the IRS is exploited to mitigate jamming interference and enhance the integrated system communication performance. In such a network, the terrestrial network and satellite network are co-existing with a spectrum-sharing scheme in the presence of a multi-antenna jammer. We aim at maximizing the weighted sum rate (WSR) of all users by jointly optimizing the terrestrial beamformers and IRS phase shifts while considering the signal-to-interference-plus-noise ratio (SINR) requirements of legitimate users. Different from the non-convex optimization techniques utilized in the IRS-related problem, a novel optimization-driven deep reinforcement learning (DRL) algorithm is proposed, which leverages both the robustness of model-free learning approaches and the efficiency of model-based optimization methods. In the optimization module of the proposed algorithm, we analyze the smart jammer under the unknown jamming model and derive a lower bound of the anti-jamming uncertainty, such that the IRS-aided anti-jamming problem can be solved by alteration method with second-order cone programming (SOCP) algorithm and semidefinite relaxation (SDR) technique. Simulation results demonstrate that the IRS can enhance the anti-jamming performance efficiently, and the proposed optimization-driven DRL algorithm can improve both the learning rate and the system performance compared with existing solutions.

Robust Beamforming Design for Fairness-Aware Energy Efficiency Maximization in RIS-Assisted mmWave Communications

Robust Beamforming Design for Fairness-Aware Energy Efficiency Maximization in RIS-Assisted mmWave Communications

Joint Communications and Sensing Hybrid Beamforming Design via Deep Unfolding

Joint Communications and Sensing Hybrid Beamforming Design via Deep Unfolding

Robust beamforming design for co-existing radar and communication system with bounded error model

Robust beamforming design for co-existing radar and communication system with bounded error model

Joint channel training and passive beamforming design for intelligent reflecting surface-aided LoRa systems

<abstract><p>In order to examine the potential and synergetic aspects of intelligent reflecting surface (IRS) techniques for Internet-of-Things (IoT), we study an IRS-aided Long Range (LoRa) system in this paper. Specifically, to facilitate the acquisition of accurate channel state information (CSI) for effective reflection of LoRa signals, we first propose an optimal training design for the least squares channel estimation with LoRa modulation, and then, by utilizing the acquired CSI, we develop a high-performing passive beamforming scheme based on a signal-to-ratio (SNR) criterion. Numerical results show that the proposed training design considerably outperforms the baseline schemes, and the proposed passive beamforming design results in a significant improvement in performance over that of the conventional LoRa system, thereby demonstrating the feasibility of extending coverage areas of LoRa systems with the aid of IRS.</p></abstract>

Robust Beamforming Design for Integrated Sensing and Covert Communication Systems

Robust Beamforming Design for Integrated Sensing and Covert Communication Systems

Quality-Driven Beamforming Design for IRS-Aided Video Broadcasting

Quality-Driven Beamforming Design for IRS-Aided Video Broadcasting

Robust Beamforming Design for Covert Integrated Sensing and Communication in the Presence of Multiple Wardens

Robust Beamforming Design for Covert Integrated Sensing and Communication in the Presence of Multiple Wardens

URLLC-Aware Trajectory Plan and Beamforming Design for NOMA-Aided UAV Integrated Sensing, Communication, and Computation Networks

URLLC-Aware Trajectory Plan and Beamforming Design for NOMA-Aided UAV Integrated Sensing, Communication, and Computation Networks

Joint Beamforming Design for the STAR-RIS-Enabled ISAC Systems with Multiple Targets and Multiple Users

Joint Beamforming Design for the STAR-RIS-Enabled ISAC Systems with Multiple Targets and Multiple Users

RS-BNN: A Deep Learning Framework for the Optimal Beamforming Design of Rate-Splitting Multiple Access

RS-BNN: A Deep Learning Framework for the Optimal Beamforming Design of Rate-Splitting Multiple Access

Robust Beamforming Design for RIS-Assisted Cognitive Radio Systems with Hardware Impairments

Robust Beamforming Design for RIS-Assisted Cognitive Radio Systems with Hardware Impairments

A note on the design of frequency-invariant beamforming with uniform concentric circular microphone array

Compared to the frequency-invariant beamformer (FIB) with uniform circular microphone arrays, the FIB with uniform concentric circular microphone arrays (UCCAs) can mitigate the deep nulls problem in the white noise gain (WNG) and the directivity factor (DF). The WNG of the FIB-UCCAs can be improved by increasing the number of microphones. However, certain Jacobi-Anger expansion based methods for FIB-UCCAs utilize a linearly transformed version of the beamformer coefficients to optimize the WNG, which may result in severe beampattern distortion at high frequencies. In this paper, we present a beamformer design method that is based on the Jacobi-Anger expansion but optimizes the WNG directly. We analyze the effect of the truncation error of Jacobi-Anger expansion and demonstrate that the proposed method can effectively reduce the beampattern distortion. Computer simulations illustrate the performance advantages of the developed method in terms of the DF and WNG.

Design and Implementation of Analog-Digital Hybrid Beamformers for Low-Complexity Ultrasound Systems: A Feasibility Study.

Low-complexity ultrasound systems are increasingly desired for both wearable, point-of-care ultrasound and high-end massive-channel ultrasound for 3-D matrix imaging. However, the imaging capabilities, including spatial resolution and contrast, could suffer as low complexity systems are pursued, which remains as an unresolved tradeoff. To mitigate this limitation, this study revisits the general structures of analog and digital beamformers and introduces a hybrid approach, referred to as analog-digital hybrid beamforming, to implement efficient ultrasound systems. The suggested hybrid beamforming takes two stages sequentially, where the first analog stage partially beamforms M-channel RF signals to N sum-out data (i.e., M-to-N beamforming), and the second digital stage beamforms N partial sums to single final beamformed data (i.e., N-to-1 beamforming). Our approach was systematically designed and implemented with only four major integrated circuits, which was capable of driving full 64-channel transmission and reception. The developed system was demonstrated with a customized 64-channel 1-D phased array using a commercial tissue mimicking phantom. From the phantom imaging results, signal-to-noise ratio, contrast-to-noise ratio, and full beam width at half maximum values were quantitatively evaluated. The demonstrated results indicate that the analog-digital hybrid beamforming can be applied to any type of array for sophisticated 3-D imaging and tiny wearable ultrasound applications.

Multi-user communications for line-of-sight large intelligent surface systems

In this paper, we propose a new interference-suppression beamformer design and a Direction-of-Arrival (DoA) estimation method for Line-of-Sight (LoS) multi-user communication systems with circular Large Intelligent Surfaces (LISs). This symmetrical circular-shaped LIS allows signals defined on it to be formed by combining Fourier and Bessel series. The Fourier harmonics are orthogonal along the rotational direction and the Bessel functions constituting the Bessel series are orthogonal along the radial direction. Synthesizing basis functions from these two series results in the proposed interference-suppression beamformer, with their coefficients designed to cancel inter-user interference. Also by exploiting signal structure of a circular LIS communicating with Mobile Stations (MSs), we devise a DoA estimation method to obtain directional information of incoming signals. Under LoS channel, the DoA corresponds to elevation and Azimuth angles of MSs relative to the LIS. This method is numerically demonstrated to have promising performance with high-frequency carriers.

QoS-Guaranteed Hybrid Beamforming Design for Multi-User Systems With Finite-Resolution Phase Shifters

Massive multiple input multiple output (MIMO) technology is a key enabler of the next generation wireless communications. The partially-connected hybrid beamforming architecture is attractive in massive MIMO systems for its reduced cost, power consumption, and hardware complexity. On the other hand, the specific analog beamforming structure and finite-resolution in phase shifters complicate the beamforming design. In this paper, we study the hybrid beamforming design for the partially-connected architecture, where users can have multiple antennas and different requirements on quality of service (QoS). A transmit power minimization problem is formulated. The beamforming design needs to be aligned to discrete phase values due to the practical limitations. Such problem is non-convex and is hard to solve. We propose an effective algorithm for this problem. In particular, the penalty-based method is used to decouple the variables. The original problem is decomposed into several sub-problems. The block prox-linear method is applied to solve the sub-problems alternatively with convergence guarantee. We show the effectiveness and robustness of our proposed algorithm via simulations. Our proposed algorithm with low resolution phase shifters achieves better performance with lower transmit power than existing methods.

Tunable SRS-Aware Robust Coordinated Beamforming Design With Channel Aging

Coordinated beamforming holds tremendous potential to maximize network capacity, whose effect largely depends on the period sounding reference signal (SRS)-based channel sounding. However, the huge discrepancy between the sounding channel and the real-time channel is inevitable and nonnegligible with channel aging, which results in severe degradation of coordinated beamforming gain. In this paper, the discrepancy is modeled as a random error term with the effect of channel aging included, and a robust coordinated beamforming design with channel aging is further proposed, exploiting the potential capacity gain through the channel statistical information, which provides the potential for tuning the SRS period. Specifically, the joint correlation properties of channels are modeled in the random error matrix with the static statistical information collected from practical channel samples. To cope with multiple random terms, the deterministic equivalent method is adopted to obtain the approximate closed-form expression of the ergodic capacity, aiming at deriving a robust beamformer that can achieve a stationary point of the expected weighted sum-rate maximization problem. In addition, by adopting the proposed beamforming design, the tuning guidance for the SRS period is provided for practical networks satisfying different capacity requirements and mobile scenarios. Simulation results show that the proposed design can extend the SRS period more than 1× at 10% capacity loss when user speed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$v=30\rm {km/h}$</tex-math></inline-formula> , compared with the traditional beamforming design.

ARIS-Empowered Wireless Communications: Joint Beamforming Design and Deployment Optimization

ARIS-Empowered Wireless Communications: Joint Beamforming Design and Deployment Optimization

Integrated Sensing and Communication With Delay Alignment Modulation: Performance Analysis and Beamforming Optimization

Delay alignment modulation (DAM) has been recently proposed to enable manipulable channel delay spread for efficient single- or multi-carrier communications. In particular, with perfect delay alignment, inter-symbol interference (ISI) can be eliminated even with single-carrier (SC) transmission, without relying on sophisticated channel equalization. The key ideas of DAM are <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">delay pre-compensation</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">path-based beamforming</i> , so that all multi-path signal components may arrive at the receiver simultaneously and be superimposed constructively, rather than causing the detrimental ISI. Compared to the classic orthogonal frequency division multiplexing (OFDM) transmission, DAM-enabled SC communication has several appealing advantages, including low peak-to-average-power ratio (PAPR) and high tolerance for Doppler frequency shift, which renders DAM also appealing for radar sensing. Therefore, in this paper, DAM is investigated for integrated sensing and communication (ISAC) systems. We first study the output signal-to-noise ratios (SNRs) for ISI-free SC communication and radar sensing, respectively, and then derive the closed-form expressions for DAM-based sensing in terms of the ambiguity function (AF) and integrated sidelobe ratio (ISR). Furthermore, we study the beamforming design problem for DAM-based ISAC to maximize the communication SNR while guaranteeing the sensing performance in terms of the sensing SNR and ISR. Finally, we provide performance comparison between DAM and OFDM for ISAC, and it is revealed that DAM signal may achieve better communication and sensing performance, thanks to its low PAPR, reduced guard interval overhead, as well as higher tolerance for Doppler frequency shift. Simulation results are provided to show the great potential of DAM for ISAC.

Robust Integrated Data and Energy Transfer Aided by Intelligent Reflecting Surfaces: Successive Target Migration Optimization Toward Energy Sustainability

Intelligent reflecting surfaces (IRSs) can actively adjust the wireless environment. However, accurate channel estimation on IRS-aided communication systems is difficult to obtain. Therefore, we study a robust beamforming design for an IRS-aided integrated data and energy transfer (IDET) with imperfect channel state information (CSI). Against the uncertain channel estimation error, we robustly design the transmit beamformers of the transmitter and the passive reflecting beamformer of the IRS to minimize the transmit power by satisfying both the wireless data transfer (WDT) and wireless energy transfer (WET) requirements for realising energy-sustainability in 6G. A successive target migration optimization (STMO) algorithm is proposed to obtain a robust design. The transmit covariance matrices are optimized by relaxing rank-one constraints, when a passive reflecting beamformer is given. Then, the target to minimize the transmit power is migrated to maximize the QoS requirements of energy users due to the fixed transmit power. A local optimal reflecting beamformer is obtained for improving the attainable WET performance, when the transmit covariance matrices are given. Finally, we prove that the rank-one transmit beamformers can always be found, which have the same WET and WDT performance as the transmit covariance matrices. The numerical results demonstrate the advantage of our design.