Title :
A compressed sensing sparse channel estimation method for TDCS based on cyclic prefix
Author :
Su Yuze;Ren Qinghua;Meng Qingwei
Author_Institution :
Information and Navigation College, Air Force Engineering University, Xi´an, China
Abstract :
Channel of transform domain communication system is always assumed to multipath intensive channel or the channel state is already known, while when transform domain communication system is in high-speed wireless transmission status, the channel shows sparse multipath transmission characteristics. To make full use of this characteristics, a compressed sensing sparse channel estimation method for TDCS based on cyclic prefix is proposed. Firstly, a measurement matrix with weak coherence is designed based on the transform domain communication system basis function which has perfect autocorrelation characteristics, then an improved orthogonal matching pursuit algorithm is proposed which can achieve accurate sparse channel estimation value in condition of the prior information is unknown. Both theory analysis and simulation results show that the new method can improve the accuracy of sparse channel estimation of TDCS in COST207 rural area channel model and get 3dB performance gain compared with the traditional least square channel estimation method when the bit error rate is 0.002.
Keywords :
"Channel estimation","Coherence","Matching pursuit algorithms","Sparse matrices","Compressed sensing","Signal to noise ratio","Mathematical model"
Conference_Titel :
Signal Processing, Communications and Computing (ICSPCC), 2015 IEEE International Conference on
Print_ISBN :
978-1-4799-8918-8
DOI :
10.1109/ICSPCC.2015.7338903