Search arXivSearch

arXiv · 2410.19763

Movable Antenna Enabled Integrated Sensing and Communication

Abstract

In this paper, we investigate a novel integrated sensing and communication (ISAC) system aided by movable antennas (MAs). A bistatic radar system, in which the base station (BS) is configured with MAs, is integrated into a multi-user multiple-input-single-output (MU-MISO) system. Flexible beamforming is studied by jointly optimizing the antenna coefficients and the antenna positions. Compared to conventional fixed-position antennas (FPAs), MAs provide a new degree of freedom (DoF) in beamforming to reconfigure the field response, and further improve the received signal quality for both wireless communication and sensing. We propose a communication rate and sensing mutual information (MI) maximization problem by flexible beamforming optimization. The complex fractional objective function with logarithms are first transformed with the fractional programming (FP) framework. Then, we propose an efficient algorithm to address the non-convex problem with coupled variables by alternatively solving four sub-problems. We derive the closed-form expression to update the antenna coefficients by Karush-Kuhn-Tucker (KKT) conditions. To improve the direct gradient ascent (DGA) scheme in updating the positions of the antennas, a 3-stage search-based projected GA (SPGA) method is proposed. Simulation results show that MAs significantly enhance the overall performance of the ISAC system, achieving 59.8\% performance gain compared to conventional ISAC system enabled by FPAs. Meanwhile, the proposed SPGA-based method has remarkable performance improvement compared the DGA method in antenna position optimization.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Wanting Lyu, Songjie Yang, Yue Xiu, Zhongpei Zhang, Chadi Assi, Chau Yuen. 2024-12-30. Movable Antenna Enabled Integrated Sensing and Communication. https://arxiv.org/abs/2410.19763

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Multi-Carrier Rydberg Atomic Quantum Receivers with Enhanced Bandwidth Feature for Communication and Sensing

Rydberg atomic quantum receivers (RAQRs) have attracted significant attention in recent years due to their ultra-high sensitivity. Although capable of precisely detecting the amplitude and phase of weak signals, conventional RAQRs face inherent limitations in accurately receiving wideband RF signals, due to the discrete nature of atomic energy levels and their intrinsic instantaneous bandwidth constraints. These limitations hinder their direct application to multi-carrier communication and sensing. To address this issue, this paper proposes a multi-carrier Rydberg atomic quantum receiver (MC-RAQR) structure with five energy levels. We derive the amplitude and phase of the MC-RAQR and extract the baseband electrical signal for signal processing. In terms of multi-carrier communication and sensing, we analyze the channel capacity and accuracy of angle of arrival (AoA) and distance parameters, respectively. Numerical results validate our proposed model, showing that the MC-RAQR can achieve up to a bandwidth of 11.7 MHz, which is 17-fold larger than the conventional RAQRs. As a result, the channel capacity and the resolution for multi-target sensing are improved significantly. Specifically, the channel capacity of MC-RAQR is 110-fold and 2.8-fold larger than the classical RF receivers and RAQRs, respectively. For sensing performance, the RMSE of AoA estimation for MC-RAQR exhibits 7.6-fold reduction, compared with the conventional RAQRs. Furthermore, the RMSE of distance estimation is $634$-fold smaller than that of the root-CRB of classical RF receivers, showing the superior performance of the MC-RAQR. This demonstrates its compatibility with waveforms such as orthogonal frequency-division multiplexing (OFDM) and its significant advantages for multi-carrier signal reception.

eess.SP

Channel Estimation in MIMO Systems Aided by Microwave Linear Analog Computers (MiLACs)

Microwave linear analog computers (MiLACs) have recently emerged as a promising solution for future gigantic multiple-input multiple-output (MIMO) systems, enabling beamforming with greatly reduced hardware and computational cost. However, channel estimation for MiLAC-aided systems remains an open problem. Conventional least squares (LS) and minimum mean square error (MMSE) estimation rely on intensive digital computation, which undermines the computational advantage offered by MiLACs. In this letter, we propose efficient LS and MMSE channel estimation schemes for MiLAC-aided MIMO systems. By designing the training precoder and combiner implemented by lossless and reciprocal MiLACs, the proposed schemes perform LS and MMSE estimation in the analog domain, leaving only simple digital scaling. They achieve identical estimation performance to their digital counterparts while significantly reducing computational complexity. Numerical results verify the effectiveness of the proposed schemes.

eess.SP

Joint Subcarrier Phase Recovery for Nonlinearity Mitigation

We propose a low-complexity phase recovery scheme that simultaneously mitigates laser phase noise and fiber nonlinearity across several subcarriers. In a long single-span link with Raman amplification, the scheme achieves 0.9 dB gain with 99 real multiplications per complex symbol.

eess.SP