Data-Driven Joint Estimation for Blind Signal Based on GA-PSO Algorithm

Data-Driven Joint Estimation for Blind Signal Based on GA-PSO Algorithm

LIU Shen1,2,3, QIN Yuannian1, LI Xiaofan2, ZHAO Yubin3, XU Chengzhong4

(1. Guilin University of Electronic Technology, Guilin, Guangxi 541004, China;
2. Shenzhen Institute of Radio Testing & Tech., Shenzhen, Guangdong 518000, China;
3. Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518000, China;
4. University of Macau, Macau SAR 999078, China)

Abstract：Without any prior information about related wireless transmitting nodes, joint estimation of the position and power of a blind signal combined with multiple co-frequency radio waves is a challenging task. Measuring the signal related data based on a group distributed sensor is an efficient way to infer the various characteristics of the signal sources. In this paper, we propose a particle swarm optimization to estimate multiple co-frequency “blind” source nodes, which is based on the received power data measured by the sensors. To distract the mix signals precisely, a genetic algorithm is applied, and it further improves the estimation performance of the system. The simulation results show the efficiency of the proposed algorithm.
Keywords:Particle Swarm Optimization (PSO);Genetic Algorithm (GA);spatially distributed sensor;blind signal detection