Semidynamic Cell-Clustering Algorithm Based on Reinforcement Learning in Cooperative Transmission System

In this paper, we propose a novel method of managing a semidynamic cluster through the use of a reinforcement learning. We derive some concepts from reinforcement learning that could be suitable for cooperative networks. We also verify the performance of proposed algorithm by means of a simulation,...

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Veröffentlicht in:IEEE systems journal 2018-12, Vol.12 (4), p.3853-3856
Hauptverfasser: Chung, Byung Chang, Cho, Dong-Ho
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description In this paper, we propose a novel method of managing a semidynamic cluster through the use of a reinforcement learning. We derive some concepts from reinforcement learning that could be suitable for cooperative networks. We also verify the performance of proposed algorithm by means of a simulation, in which we examined spectral efficiency and convergence properties. The proposed algorithm represents a considerable improvement for edge users in particular. In addition, we analyze the complexity of the clustering schemes. Our proposed algorithm is effective in the environment where there is a limited computational resource.
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subjects Algorithm design and analysis
Algorithms
Array signal processing
Cell clustering
Clustering
Clustering algorithms
Computer simulation
cooperative networks
Heuristic algorithms
Interference
Learning (artificial intelligence)
Machine learning
partial cooperative multipoint transmission (partial CoMP)
reinforcement learning
Signal to noise ratio
small cells (SC)
title Semidynamic Cell-Clustering Algorithm Based on Reinforcement Learning in Cooperative Transmission System
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