Reduced-Feedback Hybrid Precoding for Wideband mmWave MIMO-OFDM Systems
This work addresses the high feedback overhead problem in wideband mmWave MIMO-OFDM systems, offering a practical solution for reducing CSI feedback cost.
The paper proposes a feedback-efficient hybrid precoding framework for wideband mmWave MIMO-OFDM systems that reduces feedback overhead from O(K) to O(K/M + log M) while achieving comparable or superior spectral efficiency and BER performance to existing schemes.
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.