Massive MIMO Based on Compressed Sensing Adaptive Clustering Algorithm

Joint Spatial Division and Multiplexing (JSDM) is a recently proposed scheme to realize massive MIMO for FDD systems. This scheme is carried out using two steps: partitioning MS into groups in terms of covariances of each group; harnessing a two-stage beamforming: a precoder to mitigate inter-group...

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Bibliographic Details
Published in:2018 10th International Conference on Advanced Infocomm Technology (ICAIT) pp. 152 - 155
Main Authors: Jin, Zhou, Hua, Shijian
Format: Conference Proceeding
Language:English
Published: IEEE 01.08.2018
Subjects:
adaptive clustering algorithm
Array signal processing
Clustering algorithms
Compressed sensing
Correlation
genetic algorithm
Genetic algorithms
Interference
JSDM
Massive MIMO
Multiplexing
Simulation
System performance
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Summary:Joint Spatial Division and Multiplexing (JSDM) is a recently proposed scheme to realize massive MIMO for FDD systems. This scheme is carried out using two steps: partitioning MS into groups in terms of covariances of each group; harnessing a two-stage beamforming: a precoder to mitigate inter-group interference by spatial correlation and a mutli-user precoder to counterbalance intra-group interference. Dual polarized massive MIMO aims to stave off the spatial constraint of 5G massive mimo. Diverging from pervious contributions which equally distribute MS into groups, this paper focuses mainly on an adaptive MS clustering algorithm for massive mimo JSDM scheme to optimize system performance. Simulation results show that the system outdoes the former JSDM FDD system.
DOI:10.1109/ICAIT.2018.8686641