An Optimization for Channel Estimation Based on Compressed Channel Sensing

摘要: The channel response of data communication over a multipath wireless is often required to be known at the receiver. An accurate estimation can greatly increase throughput whole systems. Training-based methods are commonly used learn response. But traditional doesn't take characteristics into account. On other hand, Compressive sensing has recently gained much attention in various areas. In communication, compressive also been estimate orthogonal frequency division multiplexing (OFDM) this paper, we consider selective channels which opposite time wireless. optimization for based on compressed proposed paper. considers character channel. We use delay optimize algorithm Orthogonal Matching Pursuit. present LS and CS estimators method modifications compromising performance. bit error number normalized mean square 16-QAM system presented by means simulation results. Our results demonstrate significant reduction performance bite error. So that, achieves same with pilots comparing estimation, then, modified spectral efficiency.