Abstract

High data rates can be achieved with large-scale MIMO systems by using hybrid beamforming (HBF), which also simplifies and lowers MIMO systems' costs, but designing hybrid precoders is an extremely challenging task that requires handling CSI feedback and solving demanding optimization problems. With the RSSI-based unsupervised deep learning approach introduced in this paper, hybrid beamforming is designed for large-scale MIMO systems. In addition, there are two approaches provided: one for designing the codebook for the simulated pre-encoder, and another for designing the synchronization signal (SS) for the initial access (IA), and different scenarios and realistic channel models are used to evaluate the system performance.

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 call

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.