JOURNAL ARTICLE

Research on indoor wireless network coverage layout based on hybrid particle swarm optimization algorithm

Abstract

In this paper, the number and location of the deployment of indoor small base stations are used as optimization variables to ensure coverage and reduce the interference between base stations as conditions. Based on the corrected model, a differential evolution hybrid particle swarm optimization algorithm is used to solve the optimization objectives. In the process of each iteration, the solution solution given by the optimization algorithm is covered by the prediction model. The signal coverage degree in the target area is calculated and fed back to the particle swarm optimization algorithm as the historical experience data for learning, and the final planning scheme is output, which has certain engineering practice basis and guiding significance for operation and maintenance work.

Keywords:
Particle swarm optimization Computer science Multi-swarm optimization Mathematical optimization Base station Algorithm Differential evolution Meta-optimization Swarm behaviour Optimization problem Process (computing) Hybrid algorithm (constraint satisfaction) Software deployment Mathematics Artificial intelligence Telecommunications

Metrics

2
Cited By
0.33
FWCI (Field Weighted Citation Impact)
4
Refs
0.54
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced MIMO Systems Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Millimeter-Wave Propagation and Modeling
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Advanced Wireless Network Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
© 2026 ScienceGate Book Chapters — All rights reserved.