An Overview of Signal Processing Techniques for Millimeter Wave MIMO Systems

TL;DR

This paper reviews the challenges and techniques in signal processing for millimeter wave MIMO systems, emphasizing the need for new algorithms due to large antenna arrays and wide bandwidths in next-generation wireless communication.

Contribution

It provides a comprehensive overview of signal processing challenges and potential solutions for mmWave MIMO systems, highlighting recent advances and future directions.

Findings

Identification of key signal processing challenges in mmWave MIMO

Discussion of compressed sensing for channel estimation and beamforming

Emphasis on low complexity transceiver algorithm development

Abstract

Communication at millimeter wave (mmWave) frequencies is defining a new era of wireless communication. The mmWave band offers higher bandwidth communication channels versus those presently used in commercial wireless systems. The applications of mmWave are immense: wireless local and personal area networks in the unlicensed band, 5G cellular systems, not to mention vehicular area networks, ad hoc networks, and wearables. Signal processing is critical for enabling the next generation of mmWave communication. Due to the use of large antenna arrays at the transmitter and receiver, combined with radio frequency and mixed signal power constraints, new multiple-input multiple-output (MIMO) communication signal processing techniques are needed. Because of the wide bandwidths, low complexity transceiver algorithms become important. There are opportunities to exploit techniques like compressed sensing for channel estimation and beamforming. This article provides an overview of signal processing challenges in mmWave wireless systems, with an emphasis on those faced by using MIMO communication at higher carrier frequencies.