Abstract
The significant forecasted increase in the number of devices and mobile data requirements has posed stringent requirements for future wireless communication networks. Massive MIMO is one of the chief candidates for future 5G wireless communication systems, but to fully reap the true benefits many research problems still need to be solved or require further analysis. Among many, the problem of estimating channel between the user terminals and each BS antenna holds a significant place. In this paper, we deal with the accurate and timely acquisition of massive Channel State Information as an optimization problem that is solved using heuristic optimization techniques i.e. Genetic Algorithm, Particle Swarm Optimization and Differential Evolution. Results have been obtained by exploiting the parallel processing property bestowed when using match filtering and beamforming for precoding and decoding respectively. Monte Carlos simulation have been presented for the purpose of performance comparison among aforementioned optimization techniques based on Mean Squared Error criterion.
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.
