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Cunhua Pan

Publications and source records attributed to Cunhua Pan.

At least 145 records · Page 8Linked to original sources
arXiv2024

Robust Beamforming Design for Intelligent Reflecting Surface Aided Cognitive Radio Systems with Imperfect Cascaded CSI

In this paper, intelligent reflecting surface (IRS) is introduced to enhance the network performance of cognitive radio (CR) systems. Specifically, we investigate robust beamforming design based on both bounded channel state information (CSI) error model and statistical CSI error model for primary user (PU)-related channels in IRS-aided CR systems. We jointly optimize the transmit precoding (TPC) at the secondary user (SU) transmitter (ST) and phase shifts at the IRS to minimize the ST' s total transmit power subject to the quality of service of SUs, the limited interference imposed on the PU and unit-modulus of the reflective beamforming. The successive convex approximation (SCA) method, Schur's complement, General sign-definiteness principle, inverse Chi-square distribution and penalty convex-concave procedure are invoked for dealing with these intricate constraints. The non-convex optimization problems are transformed into several convex subproblems and efficient algorithms are proposed. Simulation results verify the efficiency of the proposed algorithms and reveal the impacts of CSI uncertainties on ST's minimum transmit power and feasibility rate of the optimization problems. Simulation results also show that the number of transmit antennas at the ST and the number of phase shifts at the IRS should be carefully chosen to balance the channel realization feasibility rate and the total transmit power.

eess.SP↗
arXiv2023

Large Language Model Enhanced Multi-Agent Systems for 6G Communications

The rapid development of the Large Language Model (LLM) presents huge opportunities for 6G communications, e.g., network optimization and management by allowing users to input task requirements to LLMs by nature language. However, directly applying native LLMs in 6G encounters various challenges, such as a lack of private communication data and knowledge, limited logical reasoning, evaluation, and refinement abilities. Integrating LLMs with the capabilities of retrieval, planning, memory, evaluation and reflection in agents can greatly enhance the potential of LLMs for 6G communications. To this end, we propose a multi-agent system with customized communication knowledge and tools for solving communication related tasks using natural language, comprising three components: (1) Multi-agent Data Retrieval (MDR), which employs the condensate and inference agents to refine and summarize communication knowledge from the knowledge base, expanding the knowledge boundaries of LLMs in 6G communications; (2) Multi-agent Collaborative Planning (MCP), which utilizes multiple planning agents to generate feasible solutions for the communication related task from different perspectives based on the retrieved knowledge; (3) Multi-agent Evaluation and Reflecxion (MER), which utilizes the evaluation agent to assess the solutions, and applies the reflexion agent and refinement agent to provide improvement suggestions for current solutions. Finally, we validate the effectiveness of the proposed multi-agent system by designing a semantic communication system, as a case study of 6G communications.

cs.AI↗
arXiv2023

Two Efficient Beamforming Methods for Hybrid IRS-aided AF Relay Wireless Networks

Due to the double fading effect caused by conventional passive intelligent reflecting surface (IRS), the signal via the reflection link is weak. To enhance the received signal, active elements with the ability to amplify the reflected signal are introduced to the passive IRS forming hybrid IRS. In this paper, we propose a hybrid IRS-aided amplify-and-forward (AF) relay wireless network, where an optimization problem is formulated, which is subject to the constraints of transmit power budgets at the source/AF relay/hybrid IRS and that of unit modulus for passive IRS elements. By alternately designing the beamforming matrix at AF relay and the reflecting coefficient matrices at IRS, signal-to-noise ratio can be maximized. To achieve high rate performance and extend the coverage range, a high-performance method based on semidefinite relaxation and fractional programming (HP-SDR-FP) algorithm is presented. Due to its extremely high complexity, a low-complexity method based on whitening filter, general power iterative and generalized Rayleigh-Ritz (WF-GPI-GRR) is proposed, which is different from HP-SDR-FP method. It is assumed that the amplifying coefficient of each active IRS element is equal, and the corresponding analytical solution of the amplifying coefficient can be obtained according to the transmit powers at AF relay and hybrid IRS. Simulation results show that the proposed two methods can greatly improve the rate performance compared to the existing networks, such as the passive IRS-aided AF relay and only AF relay network. In particular, a 50.0% rate gain over the existing networks is approximately achieved in the high power budget region of hybrid IRS. Moreover, it is verified that the proposed HP-SDR-FP method perform better than WF-GPI-GRR method in terms of rate performance.

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arXiv2023

Resource Allocation for RIS-Empowered Wireless Communications: Low-Complexity and Robust Designs

This article delves into advancements in resource allocation techniques tailored for systems utilizing reconfigurable intelligent surfaces (RIS), with a primary focus on achieving low-complexity and resilient solutions. The investigation of low-complexity approaches for RIS holds significant relevance, primarily owing to the intricate characteristics inherent in RIS-based systems and the need of deploying large-scale RIS arrays. Concurrently, the exploration of robust solutions aims to address the issue of hardware impairments occurring at both the transceivers and RIS components in practical RIS-assisted systems. In the realm of both low-complexity and robust resource allocation, this article not only elucidates the fundamental techniques underpinning these methodologies but also offers comprehensive numerical results for illustrative purposes. The necessity of adopting resource allocation strategies that are both low in complexity and resilient is thoroughly established. Ultimately, this article provides prospective research avenues in the domain of low-complexity and robust resource allocation techniques tailored for RIS-assisted systems.

cs.IT↗
arXiv2023

FAS-assisted NOMA Short-Packet Communication Systems

In this paper, we investigate a fluid antenna system (FAS)-assisted downlink non-orthogonal multiple access (NOMA) for short-packet communications. The base station (BS) adopts a single fixed antenna, while both the central user (CU) and the cell-edge user (CEU) are equipped with a FAS. Each FAS comprises $N$ flexible positions (also known as ports), linked to $N$ arbitrarily correlated Rayleigh fading channels. We derive expressions for the average block error rate (BLER) of the FAS-assisted NOMA system and provide asymptotic BLER expressions. We determine that the diversity order for CU and CEU is $N$, indicating that the system performance can be considerably improved by increasing $N$. Simulation results validate the great performance of FAS.

cs.IT↗
arXiv2023

Performance Analysis and Low-Complexity Design for XL-MIMO with Near-Field Spatial Non-Stationarities

Extremely large-scale multiple-input multiple-output (XL-MIMO) is capable of supporting extremely high system capacities with large numbers of users. In this work, we build a framework for the analysis and low-complexity design of XL-MIMO in the near field with spatial non-stationarities. Specifically, we first analyze the theoretical performance of discrete-aperture XL-MIMO using an electromagnetic (EM) channel model based on the near-field spherical wavefront. We analytically reveal the impact of the discrete aperture and polarization mismatch on the received power. We also complement the classical Fraunhofer distance based on the considered EM channel model. Our analytical results indicate that a limited part of the XL-array receives the majority of the signal power in the near field, which leads to a notion of visibility region (VR) of a user. Thus, we propose a VR detection algorithm and leverage the acquired VR information to devise a low-complexity symbol detection scheme. Furthermore, we propose a graph theory-based user partition algorithm, relying on the VR overlap ratio between different users. Partial zero-forcing (PZF) is utilized to eliminate only the interference from users allocated to the same group, which further reduces computational complexity in matrix inversion. Numerical results confirm the correctness of the analytical results and the effectiveness of the proposed algorithms. It reveals that our algorithms approach the performance of conventional whole array (WA)-based designs but with much lower complexity.

eess.SP↗
arXiv2023

Proactive Monitoring via Jamming in Fluid Antenna Systems

This paper investigates the efficacy of utilizing fluid antenna system (FAS) at a legitimate monitor to oversee suspicious communication. The monitor switches the antenna position to minimize its outage probability for enhancing the monitoring performance. Our objective is to maximize the average monitoring rate, whose expression involves the integral of the first-order Marcum $Q$ function. The optimization problem, as initially posed, is non-convex owing to its objective function. Nevertheless, upon substituting with an upper bound, we provide a theoretical foundation confirming the existence of a unique optimal solution for the modified problem, achievable efficiently by the bisection search method. Furthermore, we also introduce a locally closed-form optimal resolution for maximizing the average monitoring rate. Empirical evaluations confirm that the proposed schemes outperform conventional benchmarks considerably.

eess.SP↗
arXiv2023

Outage Constrained Robust Transmission Design for IRS-aided Secure Communications with Direct Communication Links

In this paper, we investigate the robust outage constrained transmission design for an intelligent reflecting surface (IRS) aided secure communication system. We assume that a single-antenna legitimate receiver (Bob) served by a multi-antenna base station (BS) is overheard by multiple single-antenna eavesdroppers (Eves), and the artificial noise (AN) is incorporated to confuse the Eves. In particular, we aim to jointly optimize the transmit beamforming, the AN spatial distribution at the BS, and the passive beamforming at the IRS, where the Eve-related channels are assumed to be imperfect due to the channel estimation errors and their concealment. Two scenarios with partial channel state information (CSI) error of only cascaded BS-IRS-Eve channel and full CSI errors of both cascaded BS-IRS-Eve channel and direct BS-Eve channel are investigated under the statistical CSI error model. An outage-constrained power minimization problem is formulated by limiting the maximum allowable data rate of Eves and ensuring the minimum data rate requirement of Bob. To solve it, the Bernstein-type inequality and alternating optimization strategy are exploited, and artful mathematical manipulations are performed to facilitate the optimization on the phase shifts of the IRS. Simulation results confirm the performance advantages of the proposed algorithm.

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arXiv2023

On Performance of Fluid Antenna System using Maximum Ratio Combining

This letter investigates a fluid antenna system (FAS) where multiple ports can be activated for signal combining for enhanced receiver performance. Given $M$ ports at the FAS, the best $K$ ports out of the $M$ available ports are selected before maximum ratio combining (MRC) is used to combine the received signals from the selected ports. The aim of this letter is to study the achievable performance of FAS when more than one ports can be activated. We do so by analyzing the outage probability of this setup in Rayleigh fading channels through the utilization of Gauss-Chebyshev integration, lower bound estimation, and high signal-to-noise ratio (SNR) asymptotic approximations. Our analytical results demonstrate that FAS can harness rich spatial diversity, which is confirmed by computer simulations.

eess.SP↗
arXiv2023

Energy Minimization for Active RIS-Aided UAV-Enabled SWIPT Systems

In this paper, we consider an active reconfigurable intelligent surface (RIS)-aided unmanned aerial vehicle(UAV)-enabled simultaneous wireless information and power transfer(SWIPT) system with multiple ground users. Compared with the conventional passive RIS, the active RIS deploying the internally integrated amplifiers can offset part of the multiplicative fading. In this system, we deal with an optimization problem of minimizing the total energy cost of the UAV. Specifically, we alternately optimize the trajectories, the hovering time, and the reflection vectors at the active RIS by using the successive convex approximation (SCA) method. Simulation results show that the active RIS performs better in energy saving than the conventional passive RIS.

eess.SP↗
arXiv2023

Two-Timescale Transmission Design for RIS-Aided Cell-Free Massive MIMO Systems

This paper investigates the performance of a two-timescale transmission design for uplink reconfigurable intelligent surface (RIS)-aided cell-free massive multiple-input multiple-output (CF-mMIMO) systems. We consider the Rician channel model and design the passive beamforming of RISs based on the long-time statistical channel state information (CSI), while the central processing unit (CPU) utilizes the maximum ratio combining (MRC) technology to perform fully centralized processing based on the instantaneous overall channel, which are the superposition of the direct and RIS-reflected channels. Firstly, we derive the closed-form approximate expression of the uplink achievable rate for arbitrary numbers of access point (AP) antennas and RIS reflecting elements. Relying on the derived expressions, we theoretically analyze the benefits of deploying RIS into cell-free mMIMO systems and draw explicit insights. Then, based on the closed-form approximate rate expression under statistical CSI, we optimize the phase shifts of RISs based on the genetic algorithm (GA) to maximize the sum rate and minimum rate of users, respectively. Finally, the numerical results demonstrate the correctness of our derived expressions and the benefits of deploying large-size RISs into cell-free mMIMO systems. Also, we investigate the optimality and convergence behaviors of the GA to verify its effectiveness. To give more beneficial analysis, we give the closed-form expression of the energy efficiency and present numerical results to show the high energy efficiency of the system with the help of RISs. Besides, our results have revealed the benefits of distributed deployment of APs and RISs in the RIS-aided mMIMO system with cell-free networks.

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arXiv2023

Over-the-Air Federated Averaging with Limited Power and Privacy Budgets

To jointly overcome the communication bottleneck and privacy leakage of wireless federated learning (FL), this paper studies a differentially private over-the-air federated averaging (DP-OTA-FedAvg) system with a limited sum power budget. With DP-OTA-FedAvg, the gradients are aligned by an alignment coefficient and aggregated over the air, and channel noise is employed to protect privacy. We aim to improve the learning performance by jointly designing the device scheduling, alignment coefficient, and the number of aggregation rounds of federated averaging (FedAvg) subject to sum power and privacy constraints. We first present the privacy analysis based on differential privacy (DP) to quantify the impact of the alignment coefficient on privacy preservation in each communication round. Furthermore, to study how the device scheduling, alignment coefficient, and the number of the global aggregation affect the learning process, we conduct the convergence analysis of DP-OTA-FedAvg in the cases of convex and non-convex loss functions. Based on these analytical results, we formulate an optimization problem to minimize the optimality gap of the DP-OTA-FedAvg subject to limited sum power and privacy budgets. The problem is solved by decoupling it into two sub-problems. Given the number of communication rounds, we conclude the relationship between the number of scheduled devices and the alignment coefficient, which offers a set of potential optimal solution pairs of device scheduling and the alignment coefficient. Thanks to the reduced search space, the optimal solution can be efficiently obtained. The effectiveness of the proposed policy is validated through simulations.

cs.LG↗
arXiv2023

Channel Estimation for RIS-Aided Multi-User mmWave Systems with Uniform Planar Arrays

In this paper, we adopt a three-stage based uplink channel estimation protocol with reduced pilot overhead for an reconfigurable intelligent surface (RIS)-aided multi-user (MU) millimeter wave (mmWave) communication system, in which both the base station (BS) and the RIS are equipped with a uniform planar array (UPA). Specifically, in Stage I, the channel state information (CSI) of a typical user is estimated. To address the power leakage issue for the common angles-of-arrival (AoAs) estimation in this stage, we develop a low-complexity one-dimensional search method. In Stage II, a re-parameterized common BS-RIS channel is constructed with the estimated information from Stage I to estimate other users' CSI. In Stage III, only the rapidly varying channel gains need to re-estimated. Furthermore, the proposed method can be extended to multi-antenna UPA-type users, by decomposing the estimation of a multi-antenna channel with $J$ scatterers into estimating $J$ single-scatterer channels for a virtual single-antenna user. An orthogonal matching pursuit (OMP)-based method is proposed to estimate the angles-of-departure (AoDs) at the users. Simulation results demonstrate that the proposed algorithm significantly achieves high channel estimation accuracy, which approaches the genie-aided upper bound in the high SNR regime.

eess.SP↗
arXiv2023

Two-Timescale Design for RIS-aided Cell-free Massive MIMO Systems with Imperfect CSI

The objective of this paper is to evaluate the effectiveness of a two-timescale transmission design in cell-free massive multi-input multiple-output (MIMO) systems incorporating reconfigurable intelligent surfaces (RISs) under the assumption of imperfect channel state information (CSI). We examine the Rician channel model and formulate the passive beamforming for the RISs based on statistical channel state information (S-CSI). To that end, we put forth a linear minimum mean square error (LMMSE) estimator with the aim of estimating the aggregation of channels from the users to the APs within each channel coherence interval. Meanwhile, the active beamforming for the radio units (APs) is executed using the maximum ratio combining (MRC) approach, which utilizes the instantaneous aggregated channels, that result from the combination of the direct and reflected channels from the RISs. Subsequently, we derive the closed-form expressions of the achievable uplink spectral efficiency (SE), which is a function of S-CSI elements such as distance-dependent path loss, Rician factors as well as the number of RIS elements and AP antennas. We then optimize the phase shifts of the RISs to maximize the sum SE of the users, utilizing the soft actor-critic (SAC) which is a deep reinforcement learning (RL) method, and relying on the derived closed-form expressions. Numerical evaluations affirm that, despite the presence of imperfect CSI, the deployment of RIS in cell-free systems can lead to significant performance improvement.

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arXiv2023

Resource Allocation for Cell-free Massive MIMO-enabled URLLC Downlink Systems

Ultra-reliable and low-latency communication (URLLC) is a pivotal technique for enabling the wireless control over industrial Internet-of-Things (IIoT) devices. By deploying distributed access points (APs), cell-free massive multiple-input and multiple-output (CF mMIMO) has great potential to provide URLLC services for IIoT devices. In this paper, we investigate CF mMIMO-enabled URLLC in a smart factory. Lower bounds (LBs) of downlink ergodic data rate under finite channel blocklength (FCBL) with imperfect channel state information (CSI) are derived for maximum-ratio transmission (MRT), full-pilot zero-forcing (FZF), and local zero-forcing (LZF) precoding schemes. Meanwhile, the weighted sum rate is maximized by jointly optimizing the pilot power and transmission power based on the derived LBs. Specifically, we first provide the globally optimal solution of the pilot power, and then introduce some approximations to transform the original problems into a series of subproblems, which can be expressed in a geometric programming (GP) form that can be readily solved. Finally, an iterative algorithm is proposed to optimize the power allocation based on various precoding schemes. Simulation results demonstrate that the proposed algorithm is superior to the existing algorithms, and that the quality of URLLC services will benefit by deploying more APs, except for the FZF precoding scheme.

cs.IT↗
arXiv2023

A Framework for Transmission Design for Active RIS-Aided Communication with Partial CSI

Active reconfigurable intelligent surfaces (RISs) have recently been proposed to compensate for the severe multiplicative fading effect of conventional passive RIS-aided systems. Each reflecting element of active RISs is assisted by an amplifier such that the incident signal can be reflected and amplified instead of only being reflected as in passive RIS-aided systems. This work addresses the practical challenge that, on the one hand, in active RIS-aided systems the perfect individual CSI of the RIS-aided channels cannot be acquired due to the lack of signal processing power at the active RISs, but, on the other hand, this CSI is required to calculate the expected system data rate and RIS transmit power needed for transceiver design. To address this issue, we first derive closed-form expressions for the average achievable rate and the average RIS transmit power based on partial CSI of the RIS-aided channels. Then, we formulate an average achievable rate maximization problem for jointly optimizing the active beamforming at both the base station (BS) and the RIS. This problem is then tackled using the majorization--minimization (MM) algorithm framework, and, for each iteration, semi-closed-form solutions for the BS and RIS beamforming are derived based on the Karush-Kuhn-Tucker (KKT) conditions. To ensure the quality of service (QoS) of each user, we further formulate a rate outage constrained beamforming problem, which is solved using the Bernstein-Type inequality (BTI) and semidefinite relaxation (SDR) techniques. Numerical results show that the proposed algorithms can efficiently overcome the challenges imposed by imperfect CSI in active RIS-aided wireless systems.

cs.IT↗
arXiv2023

Channel Tracking for RIS-aided mmWave Communications Under High Mobility Scenarios

The emerging reconfigurable intelligent surface (RIS) technology is promising for applications in the millimeter wave (mmWave) communication systems to effectively compensate for propagation loss or tackle the blockage issue. Considering the high mobility of users in realistic scenarios, it is essential to adjust the phase shifts in real time to align the beam towards the mobile users, which requires to frequently estimate the channel state information. Hence, it is imperative to design efficient channel tracking schemes to avoid the complex channel estimation procedure. In this paper, we develop a novel channel tracking scheme with two advantages over conventional schemes. First, our tracking scheme is based on the cascaded angles at the RIS instead of the accurate angle values, which is more practical. Second, it can be employed under a more general setting where the noise can be non-Gaussian. Simulation results show the high tracking accuracy of our proposed scheme, and validate the superiority to the existing EKF-based tracking scheme.

eess.SP↗
arXiv2023

Channel Estimation for RIS-aided mmWave Massive MIMO System Using Few-bit ADCs

Millimeter wave (mmWave) massive multiple-input multiple-output (massive MIMO) is one of the most promising technologies for the fifth generation and beyond wireless communication system. However, a large number of antennas incur high power consumption and hardware costs, and high-frequency communications place a heavy burden on the analog-to-digital converters (ADCs) at the base station (BS). Furthermore, it is too costly to equipping each antenna with a high-precision ADC in a large antenna array system. It is promising to adopt low-resolution ADCs to address this problem. In this paper, we investigate the cascaded channel estimation for a mmWave massive MIMO system aided by a reconfigurable intelligent surface (RIS) with the BS equipped with few-bit ADCs. Due to the low-rank property of the cascaded channel, the estimation of the cascaded channel can be formulated as a low-rank matrix completion problem. We introduce a Bayesian optimal estimation framework for estimating the user-RIS-BS cascaded channel to tackle with the information loss caused by quantization. To implement the estimator and achieve the matrix completion, we use efficient bilinear generalized approximate message passing (BiG-AMP) algorithm. Extensive simulation results verify that our proposed method can accurately estimate the cascaded channel for the RIS-aided mmWave massive MIMO system with low-resolution ADCs.

cs.IT↗