Sparse Channel Estimation for OFDM Systems Based on Sparse Reconstruction by Separable Approximation
- Resource Type
- Conference
- Authors
- Shi, Xiao-Lin; Yang, Yi-Xin
- Source
- 2016 International Conference on Information System and Artificial Intelligence (ISAI) ISAI Information System and Artificial Intelligence (ISAI), 2016 International Conference on. :467-471 Jun, 2016
- Subject
- Computing and Processing
Channel estimation
OFDM
Estimation
Discrete Fourier transforms
Communication systems
Mathematical model
Covariance matrices
Sparse channel estimation
SpaRSA
orthogonal frequency division multiplex
- Language
In high-rate data orthogonal frequency division multiplex (OFDM) communication systems, many encountered channels trend to have the structure of sparse multipath. The systems over multipath channels usually require that the channel response be known at the receiver and thus channel estimation is required. In this paper, a novel scheme based on the typical least square (LS) and sparse reconstruction by separable approximation (SpaRSA) for the sparse channel estimation is presented to improve the poor performance of the LS and ℓ2-norm channel estimations. This proposed scheme can reach the global optimal solution and leads to superior channel estimation performance by applying LS estimates and introducing the noise effect into the regularization parameter in the SpaRSA algorithm. And the simulation results show the validity of the proposed approach.