Title: A resource allocation evolutionary algorithm for OFDM system
Authors: Qiang Wang; Hai-Lin Liu; Jiong-cheng Li; Yun Li
Addresses: Guangdong University of Technology, No. 161, Yinglong Road, Guangzhou, 510520, China ' Guangdong University of Technology, No. 161, Yinglong Road, Guangzhou, 510520, China ' The Key Wireless Network Optimization Center, Guangzhou Guangdong Planning and Designing Institute of Telecommunications Co., Ltd., No. 161, Yinglong Road, Guangzhou, 510630, China ' Guangdong University of Technology, No. 161, Yinglong Road, Guangzhou, 510520, China
Abstract: Resource allocation for orthogonal frequency division multiplexing (OFDM) system, as a core technology for the 4th generation mobile communication system, has shown significant importance in the improvement of system transmission rate. At present, the two-step algorithm is described as a main method to deal with resource allocation for OFDM system. As carrier allocation and power allocation are not independent of each other, the two-step algorithm may result in lower complexity but poor convergence. This paper proposes a mixed evolutionary algorithm to allocate sub-carrier and power at the same time. It combines the simulated annealing algorithm and evolutionary algorithm. This paper also improves the definition of fairness in OFDM system. It can achieves perfect fairness among users while maintaining the efficient capacity performance. Simulation results demonstrate that the proposed resource allocation algorithm can achieve perfect performance, and increase the convergence rate greatly meanwhile efficiently improving the system capacity.
Keywords: OFDM; orthogonal frequency division multiplexing; resource allocation; evolutionary algorithms; simulated annealing; 4th generation; mobile communications; carrier allocation; power allocation; fairness; simulation.
DOI: 10.1504/IJCSE.2017.081168
International Journal of Computational Science and Engineering, 2017 Vol.14 No.1, pp.55 - 63
Received: 26 Apr 2013
Accepted: 02 Oct 2013
Published online: 26 Dec 2016 *