Research Article
Using Joint Particle Swarm Optimization and Genetic Algorithm for Resource Allocation in TD-LTE Systems
@INPROCEEDINGS{10.4108/eai.19-8-2015.2260168, author={Jianbo Du and Liqiang Zhao and Jie Xin and Jen-Ming Wu and Jie Zeng}, title={Using Joint Particle Swarm Optimization and Genetic Algorithm for Resource Allocation in TD-LTE Systems}, proceedings={11th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness}, publisher={EAI}, proceedings_a={QSHINE}, year={2015}, month={9}, keywords={lte radio resource management (rrm) particle swarm optimization (pso) genetic algorithm (ga)}, doi={10.4108/eai.19-8-2015.2260168} }- Jianbo Du
Liqiang Zhao
Jie Xin
Jen-Ming Wu
Jie Zeng
Year: 2015
Using Joint Particle Swarm Optimization and Genetic Algorithm for Resource Allocation in TD-LTE Systems
QSHINE
IEEE
DOI: 10.4108/eai.19-8-2015.2260168
Abstract
This paper presents a joint radio resource allocation scheme in LTE/LTE-A systems. In order to maximize system throughput while satisfying the minimum user rate requirement, the resource allocation is modeled as a convex optimization with constraints in this paper, which is proved to be NP-hard. Hence, a heuristic approach based on joint Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) is proposed. The proposed method exploits the benefits of GA and PSO so that it could avoid the low speed problem of genetic algorithm and the local optimum trap concern in particle swarm optimization algorithm. Simulation results show that the proposed algorithm can overcome the disadvantages of genetic algorithm and particle swarm optimization algorithm, and achieve better performance, e.g., a faster convergence and global optimum.
