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Songling Zhang

Publications and source records attributed to Songling Zhang.

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On Performance of Fluid Antenna Relay (FAR)-Assisted AAV-NOMA Wireless Network

In this paper, we investigate the performance of a fluid antenna relay (FAR)-assisted downlink communication system utilizing non-orthogonal multiple access (NOMA). The FAR, which integrates a fluid antenna system (FAS), is equipped on an autonomous aerial vehicle (AAV), and introduces extra degrees of freedom to improve the performance of the system. The transmission is divided into a first phase from the base station (BS) to the users and the FAR, and a second phase where the FAR forwards the signal using amplify-and-forward (AF) or decode-and-forward (DF) relaying to reduce the outage probability (OP) for the user maintaining weaker channel conditions. To analyze the OP performance of the weak user, Copula theory and the Gaussian copula function are employed to model the statistical distribution of the FAS channels. Analytical expressions for weak user's OP are derived for both the AF and the DF schemes. Simulation results validate the effectiveness of the proposed scheme, showing that it consistently outperforms benchmark schemes without the FAR. In addition, numerical simulations also demonstrate the values of the relaying scheme selection parameter under different FAR positions and communication outage thresholds.

eess.SP

Fluid Antenna Relay (FAR)-assisted Communication with Hybrid Relaying Scheme Selection

In this paper, we investigate a fluid antenna relay (FAR)-assisted communication system with hybrid relaying scheme selection. By leveraging statistical channel state information (CSI) and distribution characteristics of fluid antenna system (FAS), we approximate the outage probability (OP) with different relaying schemes utilizing a Gaussian copula-based method. Each relay node follows the OP-minimized principle to choose the forwarding schemes. To reduce self-interference and avoid multi-user interference, half-duplex relays and frequency division multiple access schemes are considered, respectively. On this basis, we formulate a sum-rate maximization problem to mitigate the rate loss introduced by the half-duplex mode. To solve this problem, we first transform the original nonconvex problem into a power control optimization problem by obtaining the closed form of bandwidth allocation and substituting it into the original problem. Then, we solve the power control optimization problem with a low complexity method. Simulation results verify the effectiveness of our proposed algorithm to improve the sum rate of the system.

eess.SP

A generalized Nystrom method with column sketching for low-rank approximation of nonsymmetric matrices

This paper is concerned with the low-rank approximation for large-scale nonsymmetric matrices. Inspired by the classical Nystrom method, which is a popular method to find the low-rank approximation for symmetric positive semidefinite matrices, we explore an extension of the Nystrom method to approximate nonsymmetric matrices. The proposed method is a generalized Nystrom method with column sketching and shows its advantages in accuracy and speed without sacri cing stability. And the numerical experiments will illustrate the robustness of our new methods in finding a desired low-rank approximation of nonsymmetric matrix.

math.NA

Beamforming Design for the Performance Optimization of Intelligent Reflecting Surface Assisted Multicast MIMO Networks

In this paper, the problem of maximizing the sum of data rates of all users in an intelligent reflecting surface (IRS)-assisted millimeter wave multicast multiple-input multiple-output communication system is studied. In the considered model, one IRS is deployed to assist the communication from a multiantenna base station (BS) to the multi-antenna users that are clustered into several groups. Our goal is to maximize the sum rate of all users by jointly optimizing the transmit beamforming matrices of the BS, the receive beamforming matrices of the users, and the phase shifts of the IRS. To solve this non-convex problem, we first use a block diagonalization method to represent the beamforming matrices of the BS and the users by the phase shifts of the IRS. Then, substituting the expressions of the beamforming matrices of the BS and the users, the original sum-rate maximization problem can be transformed into a problem that only needs to optimize the phase shifts of the IRS. To solve the transformed problem, a manifold method is used. Simulation results show that the proposed scheme can achieve up to 28.6% gain in terms of the sum rate of all users compared to the algorithm that optimizes the hybrid beamforming matrices of the BS and the users using our proposed scheme and randomly determines the phase shifts of the IRS.

eess.SP

Quantum Algorithm for Matrix Logarithm by Integral Formula

The matrix logarithm is one of the important matrix functions. Recently, a quantum algorithm that computes the state $|f\rangle$ corresponding to matrix-vector product $f(A)b$ is proposed in [Takahira, et al. Quantum algorithm for matrix functions by Cauchy's integral formula, QIC, Vol.20, No.1\&2, pp.14-36, 2020]. However, it can not be applied to matrix logarithm. In this paper, we propose a quantum algorithm, which uses LCU method and block-encoding technique as subroutines, to compute the state $|f\rangle = \log(A)|b\rangle / \|\log(A)|b\rangle\|$ corresponding to $\log(A)b$ via the integral representation of $\log(A)$ and the Gauss-Legendre quadrature rule.

math.NA