Computation-and-Communication Efficient Coordinated Multicast Beamforming in Massive MIMO Networks

Summary

This paper proposes a computation- and communication-efficient solution for coordinated multicast beamforming in massive MIMO networks. It derives the optimal beamforming structure and proposes a fast algorithm with semi-distributed computing.

Highlights

• The optimal coordinated multicast beamformer is a weighted MMSE beamformer with an inherent low-dimensional structure.
• The beamformer at each BS is naturally distributed and only depends on the local CSI.
• The algorithm uses the SCA method and ADMM construction to decompose the problem into small subproblems.
• The semi-distributed computing approach reduces the required fronthaul communication.
• The algorithm is scalable to the network size and has low computational complexity.
• The solution is extended to the imperfect CSI case and other coordination scenarios.
• Simulation results show that the proposed algorithm achieves near-optimal performance with significantly lower computational complexity and communication overhead.

Key Insights

• The optimal beamforming structure reveals that the beamformer at each BS is a function of the local CSI, making it naturally distributed and reducing the required fronthaul communication.
• The proposed algorithm uses the SCA method and ADMM construction to decompose the problem into small subproblems, making it scalable to the network size and reducing the computational complexity.
• The semi-distributed computing approach allows each BS to compute its beamformer based on the local CSI and limited essential information sharing, reducing the required fronthaul communication.
• The algorithm is extended to the imperfect CSI case, making it more practical for real-world scenarios where CSI is not always perfect.
• The solution is also extended to other coordination scenarios, such as BS clustering, making it more versatile and applicable to different network configurations.
• The simulation results demonstrate the effectiveness of the proposed algorithm in achieving near-optimal performance with significantly lower computational complexity and communication overhead.
• The proposed algorithm has the potential to enable more BSs to participate in coordination, further reducing interference and improving the overall system performance.

Mindmap

Citation

Yin, S., & Dong, M. (2024). Computation-and-Communication Efficient Coordinated Multicast Beamforming in Massive MIMO Networks (Version 1). arXiv. https://doi.org/10.48550/ARXIV.2412.18126