Optimized Hybrid Precoding for Energy and Spectrum Efficiency in mmWave Massive MIMO System

Abstract

This paper presents a novel hybrid connection structure-based precoding algorithm specifically designed for large-scale MIMO millimeter-wave (mmWave) systems. The pri- mary objective of this algorithm is to enhance both energy and spectrum efficiency while managing the inherent hardware complexity associated with such systems. By utilizing a con- stant modulus constraint, the algorithm addresses continuous interference and applies gradient descent along with alternating minimization techniques to develop an optimal hybrid precoding matrix.Simulation results demonstrate that the proposed algo- rithm achieves near-optimal spectrum efficiency, particularly in cases where the number of RF links exceeds the number of data streams. As the antenna count increases, the algorithm’s performance becomes even more pronounced when compared to existing techniques. Additionally, the hybrid connection archi- tecture outperforms both full and partial connection structures, offering significantly higher energy efficiency. While full con- nection structures exhibit marginally better spectrum efficiency, their practical applicability is hindered by increased hardware complexity and lower energy efficiency.Moreover, the proposed approach shows robustness against channel estimation errors, particularly in large antenna arrays, making it suitable for a wider range of deployment scenarios. The algorithm’s resilience in the face of imperfect channel state information (CSI) further broadens its potential for real-world applications. This makes the method a promising and efficient solution for future mmWave massive MIMO systems, especially as the industry moves to- wards 5G and beyond. The balance achieved between spectral efficiency, energy efficiency, and hardware complexity sets the proposed method apart, ensuring its relevance in modern wireless communication networks.