Decentralized Joint Precoding With Pilot-Aided Beamformer Estimation - 2018 PROJECT TITLE :Decentralized Joint Precoding With Pilot-Aided Beamformer Estimation - 2018ABSTRACT:Downlink beamforming techniques with low beamformer coaching overhead are proposed for joint processing (JP) coordinated multipoint transmission (CoMP). The objective is to maximize the weighted add rate at intervals joint transmission clusters while not centralized beamformer processing, while accounting for uncertainty in the underlying channels. The proposed ways use time-division duplexing and pilot-based mostly coaching with, probably, nonorthogonal pilot sequences. The beamformer training is done while not the specific channel state info estimation, which greatly improves the robustness to pilot contamination. Best response and gradient-primarily based decentralized algorithms are proposed and offer a tradeoff between computational complexity and fast convergence rate. The impact of feedback/backhaul quantization is additionally considered. The results show that JP CoMP is possible with slow fading conditions and limited backhaul capacity by employing decentralized beamformer processing. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Decentralized DC Microgrid Monitoring and Optimization via Primary Control Perturbations - 2018 Decentralized RLS With Data-Adaptive Censoring for Regressions Over Large-Scale Networks - 2018