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Abstract
<p>This research puts forth an optimization- based analog beamforming scheme for millimeter-wave (mmWave) massive MIMO systems. Main aim is to optimize the combination of analog precoder / combiner matrices for the purpose of getting near-optimal performance. Codebook-based analog beamforming with transmit precoding and receive combining serves the purpose of compensating the severe attenuation of mmWave signals. The existing and traditional beamforming schemes involve a complex search for the best pair of analog precoder / combiner matrices from predefined codebooks. In this research, we have solved this problem by using Particle Swarm Optimization (PSO) to find the best combination of precoder / combiner matrices among all possible pairs with the objective of achieving near-optimal performance with regard to maximum achievable rate. Experiments prove the robustness of the proposed approach in comparison to the benchmarks considered. <strong></strong></p><p class="IndexTerms"> </p>
Highlights
The ever-increasing number of users and the demand for improved quality of service requires the development of new and better standards in wireless telecommunication
We propose the use of Particle Swarm Optimization to perform this search
Particle Swarm Optimization is assessed for the purpose of choosing such a pair of analog precoder and combiner that gives highest achievable rate in mm wave channel for massive MIMO
Summary
The ever-increasing number of users and the demand for improved quality of service requires the development of new and better standards in wireless telecommunication. As compared to 4G, the recent 5G networks claim to have the ability to increase capacity by 1000 times before 2020 [2, 3]. There are many methods that can increase capacity; for example, by increasing spectral efficiency using physical layer (massive multiple-input-multiple-output (MIMO) and advanced channel coding [4, 5]). Area spectral efficiency can be increased by deploying Network densification that includes:
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