Spatially Sparse Precoding in Millimeter Wave MIMO Systems

TL;DR

This paper develops sparse reconstruction algorithms for mmWave MIMO precoding and combining, enabling hardware-efficient beamforming that approaches optimal performance despite RF hardware constraints.

Contribution

It formulates the precoding and combining problem as a sparse reconstruction task and proposes basis pursuit algorithms for practical low-cost RF implementation.

Findings

Algorithms accurately approximate optimal precoders and combiners.

Proposed methods enable mmWave systems to approach unconstrained performance limits.

Numerical results validate the effectiveness of the algorithms.

Abstract

Millimeter wave (mmWave) signals experience orders-of-magnitude more pathloss than the microwave signals currently used in most wireless applications. MmWave systems must therefore leverage large antenna arrays, made possible by the decrease in wavelength, to combat pathloss with beamforming gain. Beamforming with multiple data streams, known as precoding, can be used to further improve mmWave spectral efficiency. Both beamforming and precoding are done digitally at baseband in traditional multi-antenna systems. The high cost and power consumption of mixed-signal devices in mmWave systems, however, make analog processing in the RF domain more attractive. This hardware limitation restricts the feasible set of precoders and combiners that can be applied by practical mmWave transceivers. In this paper, we consider transmit precoding and receiver combining in mmWave systems with large antenna arrays. We exploit the spatial structure of mmWave channels to formulate the precoding/combining problem as a sparse reconstruction problem. Using the principle of basis pursuit, we develop algorithms that accurately approximate optimal unconstrained precoders and combiners such that they can be implemented in low-cost RF hardware. We present numerical results on the performance of the proposed algorithms and show that they allow mmWave systems to approach their unconstrained performance limits, even when transceiver hardware constraints are considered.