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

• Zhengyu Kong,
• Duanpo Wu,
• Xinyu Jin,
• Shuwei Cen,
• Fang Dong,

Vol. 15, No. 4, April 30, 2021
10.3837/tiis.2021.04.021, Download Paper (Free):

• deployment
• Energy Efficiency
• MOPSO
• Redundancy Elimination

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.

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