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http://dx.doi.org/10.3837/tiis.2021.04.021

Improved AP Deployment Optimization Scheme Based on Multi-objective Particle Swarm Optimization Algorithm  

Kong, Zhengyu (School of Communication Engineering, Hangzhou Dianzi University)
Wu, Duanpo (School of Communication Engineering, Hangzhou Dianzi University)
Jin, Xinyu (Department of Information Science and Electronic Engineering, Zhejiang University)
Cen, Shuwei (China Mobile Communications Group Zhejiang Co., Ltd.)
Dong, Fang (College of Information and Electric Engineering, Zhejiang University City College)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.15, no.4, 2021 , pp. 1568-1589 More about this Journal
Abstract
Deployment of access point (AP) is a problem that must be considered in network planning. However, this problem is usually a NP-hard problem which is difficult to directly reach optimal solution. Thus, improved AP deployment optimization scheme based on swarm intelligence algorithm is proposed to research on this problem. First, the scheme estimates the number of APs. Second, the multi-objective particle swarm optimization (MOPSO) algorithm is used to optimize the location and transmit power of APs. Finally, the greedy algorithm is used to remove the redundant APs. Comparing with multi-objective whale swarm optimization algorithm (MOWOA), particle swarm optimization (PSO) and grey wolf optimization (GWO), the proposed deployment scheme can reduce AP's transmit power and improves energy efficiency under different numbers of users. From the experimental results, the proposed deployment scheme can reduce transmit power about 2%-7% and increase energy efficiency about 2%-25%, comparing with MOWOA. In addition, the proposed deployment scheme can reduce transmit power at most 50% and increase energy efficiency at most 200%, comparing with PSO and GWO.
Keywords
Deployment; Energy Efficiency; MOPSO; Redundancy Elimination;
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