Low-Cost mmWave MIMO Multi-Streaming via Bi-Clustering, Graph Coloring, and Hybrid Beamforming

• Published in: IEEE transactions on wireless communications Vol. 20; no. 7; pp. 4113 - 4127
• Main Authors: Ghasemi, Ahmad, Zekavat, Seyed A.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Antenna arrays; Antennas; Array signal processing; Beamforming; bi-clustering; Clustering; Complexity; Data transmission; Fading channels; Graph coloring; Graph theory; hybrid beamforming; IEEE Sections; Iterative algorithms; Iterative methods; machine learning; Mathematical analysis; Millimeter waves; mmWave; Optimization; Performance evaluation; Scattering; Singular value decomposition; Throughput
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2021.3056077

This paper proposes and analyses a set of novel and optimum multi-streaming techniques for mmWave multi-input multi-output systems. It formulates an optimization problem that enables exploiting available uncorrelated paths between the transmitter (Tx) and the receiver (Rx) to enhance the system throughput. In the proposed approach, antenna arrays at Tx/Rx are modeled as a Bipartite graph. Next, two bi-clustering algorithms are applied to the graph to simultaneously cluster antenna elements at Tx and Rx. In addition, the paper shows how the selection of subchannels and their corresponding subantenna arrays can be reduced to a variant of the graph coloring problem, based on which, two algorithms are proposed to find the optimum subchannels and subantenna arrays. Moreover, the paper defines two new beamforming methods and proves that those methods satisfy constant modulus and total power constraints. The first modified beamforming method uses singular vectors (SVs) of subchannels between Tx/Rx and incorporates the Power Iteration algorithm to decrease singular value decomposition complexity. The second newly proposed beamforming method finds precoders/combiners without using SVs which reduces the computational complexity. Performance evaluations in terms data streaming sum-rate demonstrate that the proposed technique increases the throughput using a low processing complexity.