RAMP and An Improved Algorithm For Sparse Channel Estimation in MIMO-OFDM System

Fei Gao, Li Dan Mei, Hong Yun Pan, Yan Ming Xue

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

The sparse channel estimation in multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems was examined. Regularized adaptive matching pursuit (RAMP) was applied to the channel estimation, and the algorithm's iteration termination condition was improved by taking the difference between the residual energy less than the set threshold to terminate the iterative process, ultimately obtain a more accurate estimation of the channel sparsity and improve the estimation accuracy of sparse channel. Simulation results demonstrate that compared to the sparsity adaptive matching pursuit (SAMP) and RAMP, the improved algorithm can obtain better MSE performance. Under the premise of unknown sparsity, the improved algorithm can reach the same MSE performance with orthogonal matching pursuit (OMP).

Original languageEnglish
Pages (from-to)297-303
Number of pages7
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume37
Issue number3
DOIs
Publication statusPublished - 1 Mar 2017

Keywords

  • Compressed sensing
  • MIMO-OFDM
  • RAMP algorithm
  • Sparse channel estimation

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