Capacity Achieving Design for Hybrid Beamforming in Millimeter Wave Massive MIMO Systems

2025-09-29

AI Summary

Existing mmWave massive MIMO hybrid beamforming designs rely solely on channel state information (CSI), neglecting the structural constraints of the transmit signal covariance matrix, thereby limiting downlink sum-rate performance. This paper proposes a novel joint optimization framework for transmit and receive beamforming matrices to maximize the downlink sum-rate in broadcast channels (BC). The key contribution lies in explicitly modeling and optimizing the structure of the transmit covariance matrix, leveraging the BC–MAC duality to transform the original non-convex problem into a tractable form, and designing an iterative algorithm tailored to hybrid digital/analog architectures. The method is generalizable to point-to-point MIMO, multi-user MISO, and MU-MIMO scenarios. Simulation results demonstrate significant sum-rate gains across diverse antenna configurations and SNR regimes, with strong robustness and consistent superiority over state-of-the-art baseline methods.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Constraint Satisfaction and Optimization: Mixed Discrete/Continuous Optimization
• Machine Learning: Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Novel mobile and WoT systems, and system-of-systems
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

Hybrid digital and analog beamforming is a highly effective technique for implementing beamforming methods in millimeter wave (mmWave) systems. It provides a viable solution to replace the complex fully digital beamforming techniques. However, the current design of precoding and combining matrices in hybrid beamforming solely relies on the channel information, neglecting the crucial consideration of the structure of covariance matrices of the transmit signals. In this paper, we present a novel approach for the joint design of hybrid beamforming matrices at the transmitter and receiver. This approach is centered around the optimization of the covariance matrix of the transmitted signals. Our goal is to maximize the downlink sum rate capacity of the system by achieving an optimal design of the transmit covariance matrix. We tackle the non-convex nature of this problem by leveraging the dual relationship between the broadcast channel (BC) and the multiple access channel (MAC). Through extensive simulations in various scenarios, including point-to-point multi-input multi-output (MIMO), multi-user (MU) multi-input single-output (MISO), and MU-MIMO, we demonstrate the superiority of our proposed method over traditional designs. These results highlight the effectiveness and versatility of our approach in optimizing beamforming for mmWave systems.

Problem

• Optimizing transmit covariance matrix for hybrid beamforming design
• Maximizing downlink sum rate capacity in mmWave MIMO systems
• Addressing non-convex problem via BC-MAC dual relationship

Innovation

• Optimizes transmit covariance matrix for beamforming design
• Leverages dual relationship between broadcast and multiple access channels
• Maximizes downlink sum rate capacity in mmWave systems