Clustering Based Hybrid Precoding Design for Multi-User Massive MIMO Systems
Ling Zhang, Lin Gui, Kai Ying, Qibo Qin

TL;DR
This paper introduces clustering-based hybrid precoding schemes for multi-user massive MIMO systems, improving spectrum and power efficiency while effectively managing inter-user interference.
Contribution
It proposes novel HAC-based and MKM-based clustering schemes for fully-connected and adaptively-connected hybrid precoding, respectively, addressing joint digital and analog precoding optimization challenges.
Findings
HAC-based FHP scheme achieves superior spectrum efficiency.
MKM-based AHP scheme demonstrates high power efficiency.
All schemes effectively handle inter-user interference and outperform existing methods.
Abstract
Hybrid precoding has been recognized as a promising technology to combat the path loss of millimeter wave signals in massive multiple-input multiple-output (MIMO) systems. However, due to the joint optimization of the digital and analog precoding matrices as well as extra constraints for the analog part, the hybrid precoding design is still a tough issue in current research. In this paper, we adopt the thought of clustering in unsupervised learning and provide design schemes for fully-connected hybrid precoding (FHP) and adaptively-connected hybrid precoding (AHP) in multi-user massive MIMO systems. For FHP, we propose the hierarchical-agglomerative-clustering-based (HAC-based) scheme to explore the relevance among RF chains in optimal hybrid procoding design. The similar RF chains are merged into an individual RF chain when insufficient RF chains are equipped at the base station (BS).…
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Taxonomy
TopicsMillimeter-Wave Propagation and Modeling · Microwave Engineering and Waveguides · Advanced MIMO Systems Optimization
