Abstract
High data rates on the wireless channel can be achieved by combining orthogonal frequency division multiplexing (OFDM) with multiple input multiple output (MIMO) communication modulation scheme. MIMO-OFDM system impulse response of the channel is approximately sparse. Sparse channelestimation can be done using Compressive Sensing (CS) techniques. In this paper, a low complexity model based CoSaMp Compressive Sensing (CS) algorithm with conventional tools namely Least Square (LS) and Least Mean Square (LMS) are used for MIMO-OFDM channel estimation. Simulation results show amodel based CoSaMP for MIMO-OFDM channel estimation with LMS tool the Normalized Mean Square Error(NMSE)reduced by 34%with very reduced complexity.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Engineering & Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
