Power Line Channel Extraction And Reconstruction Based On Compressed Sensing

With the development of communication bandwidth is higher and higher, in order to make better use of the spectrum resources, it is very important to study the communication channel. Domestic and foreign scholars have done much through field measurement and laboratory analysis respectively from the noise, channel transmission, impedance and other aspects to measure communication environment. A method of channel characteristics acquisition can extract the noise and channel transmission characteristics for various communication scenarios, in order to quantize and simulate the communication environment that observed on field. This paper discuss the method of channel acquisition under power line communication scenario, in order to implement the extraction and compression process which achieve the noise and channel transmission characteristics.As we known, traditional ADC acquiring channel characteristics will face the problem of processing large data volume. In view of the problem, this paper put forward a kind of acquisition and analysis method of power line noise and channel transmission characteristics based on compressed sensing. Through the analysis of power line noise and channel transmission characteristics, we can using its sparse property to collect, extract and storage only little amount of effective parameters. It is very useful to reduce the amount of processing data in digital signal processing module, the memory hardware requirements and the cost of hardware. Compressed sensing include three phase: signal sparse representation, signal measurements and signal restoration to process and analyze the characteristics of power line noise and channel transmission. In order to make full use of signal-self sparse property and reduce the requirements of acquisition equipment in front end, we focus on the back end to design the CS reconstruction algorithms. Being one class of the algorithms used most widely in CS signal reconstruction, this paper study the performance on power line channel reconstruction with typical greedy algorithms based on compressed sensing, including OMP-Orthogonal Matching Pursuit, St OMP-Stagewise Orthogonal Matching Pursuit, ROMP-Regularized Orthogonal Matching Pursuit, SP-Subspace Pursuit. Firstly, the four algorithms are analyzed theoretically, the relations among them compared and the corresponding implementation processes given respectively, and then the performance of four algorithms are analyzed through the simulation of Matlab from two aspects: the algorithm reconstruction error and running time. Considering the compressed dimension, signal to noise ratio and other factors, we make some simulation using four reconstruction algorithms to reconstruct the compressed measurement of power line channel characteristics. By the theoretical analysis and simulation results, the relevant conclusions are drawn in this paper. We can select the most suitable algorithm to reconstruct the compressed power line channel characteristics, and simulate power line communication environment to make communication performance test of PLC equipment from all manufacturers.