Reduced-Feedback Hybrid Precoding for Wideband mmWave MIMO-OFDM Systems

TL;DR

This paper introduces a feedback-efficient hybrid precoding framework for wideband mmWave MIMO-OFDM systems that reduces feedback overhead and maintains high spectral efficiency.

Contribution

It proposes a novel analog precoding design based on dominant AoA/AoD directions and a hierarchical digital precoding algorithm with adaptive codeword assignment.

Findings

Reduces feedback from O(K) to O(K/M + log M) scaling.

Achieves comparable or better spectral efficiency and BER performance.

Significantly lowers computational complexity and improves robustness.

Abstract

In this paper, we propose a feedback-efficient hybrid precoding framework for wideband millimeter-wave (mmWave) multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems. To mitigate the high cost of radio frequency (RF) chains and channel state information (CSI) feedback in large-scale antenna arrays, we first construct frequency-flat analog precoders by extracting dominant angle-of-arrival (AoA) and angle-of-departure (AoD) directions from sparse frequency-domain channels. For digital precoding, we design a quantized codebook using the Lloyd algorithm and develop a binary-search-based hierarchical interpolation algorithm that adaptively assigns codewords according to subcarrier correlation. The proposed method achieves sub-linear feedback scaling by reducing the feedback overhead from O(K) to O(K/M + log M), where K is the number of subcarriers and M is the pilot spacing. Simulation results demonstrate that the proposed method achieves comparable or superior spectral efficiency and bit error rate (BER) performance to existing clustering and interpolation schemes, while significantly reducing computational complexity and exhibiting robustness under imperfect CSI.