JOURNAL ARTICLE

Low complexity hybrid precoding for mmWave Massive MIMO systems

Abstract

Massive MIMO has the advantage of providing excellent multiplexing/diversity gain and data rate due to the large antenna array equipped at the BS or UEs. However, the high hardware cost and computational complexity limit the practical implementation of large antenna array. In this paper, we formulate a Minimum Mean Square Error (MMSE) based optimization model under the partially-connected structure to reduce the hardware cost, and propose a low complexity hybrid precoding algorithm based on the Particle Swarm Ant Colony Optimization (HP-PSACO). Simulation results show that the proposed algorithm with low computational complexity achieves higher energy efficiency than the fully digital baseband precoding.

Keywords:
Precoding Baseband Computer science Computational complexity theory MIMO Ant colony optimization algorithms Spatial multiplexing Particle swarm optimization Antenna (radio) Minimum mean square error Electronic engineering Zero-forcing precoding Antenna array Multiplexing Diversity gain Algorithm Telecommunications Mathematics Engineering Beamforming Bandwidth (computing)

Metrics

5
Cited By
0.40
FWCI (Field Weighted Citation Impact)
16
Refs
0.64
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Millimeter-Wave Propagation and Modeling
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Advanced MIMO Systems Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Antenna Design and Analysis
Physical Sciences →  Engineering →  Aerospace Engineering
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