Fundamental Models and Signal Processing for Movable Antenna-Enhanced Wireless Communications and Sensing

TL;DR

This paper reviews the models, scenarios, and signal processing techniques for movable antenna technology in wireless communications and sensing, emphasizing its potential to enhance performance through spatial degrees of freedom.

Contribution

It provides a comprehensive overview of models, channel characterization, and signal processing methods for integrating movable antennas into next-generation wireless systems.

Findings

Channel models based on field response and spatial correlation are developed.

Efficient methods for flexible antenna movement are introduced.

Signal processing techniques for channel acquisition and antenna optimization are discussed.

Abstract

Movable antenna (MA) has been recognized as a promising technology for performance enhancement in wireless communication and sensing systems by exploiting the spatial degrees of freedom (DoFs) in flexible antenna movement. However, the integration of MAs into next-generation wireless networks still faces design challenges due to the paradigm shift from conventional fixed-position antennas (FPAs) to MAs, which motivates this paper to provide a comprehensive overview of the models, scenarios, and signal processing techniques for MA-enhanced wireless networks. First, we introduce several efficient methods to realize flexible antenna movement. Next, channel models based on field response and spatial correlation are presented to characterize the channel variations with respect to MA movement. Then, we discuss the advantages and challenges of applying MAs to typical application scenarios of wireless communications and sensing. Moreover, we show the signal processing techniques for MA-enhanced communication and sensing systems, including channel acquisition and antenna position optimization. Finally, we highlight promising research directions to inspire future investigations.