Abstract
In this paper, we assume that little is known about channel state information (CSI) at the receiver in order to recover the unknown transmitted signal. Therefore, channel estimation and data detection are the most useful techniques at the receiver in wireless communication networks for recovering the original transmitted signal. In our study, we propose an algorithm based on least mean square (LMS) algorithm and Bayesian linear model (BLM) detector for their robustness and low implementation complexity. Amplify and forward (AF) based cooperative relay networks is considered in this study for its capability to mitigate the effects caused by multipath fading and shadowing. Analytical and simulation results on receiver operating characteristics (ROC) and MSE learning curves are presented. The results show that the proposed algorithm is effective and can provide higher detection performance in the current and next generation wireless networks.
Sign-in/Register to access full text options 
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 callDisclaimer: 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.
