Optimization of Transmit Beamforming based on Unsupervised Learning With Channel Covariances for MISO Downlink Assisted by Reconfigurable Intelligent Surfaces
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Updated
May 12, 2024 - Python
Optimization of Transmit Beamforming based on Unsupervised Learning With Channel Covariances for MISO Downlink Assisted by Reconfigurable Intelligent Surfaces
Affordable Digital HD Video Transmission made easy!
Simulation code for "Fast adaptive minorization-maximization procedure for beamforming design of downlink NOMA systems," IEEE Trans. Veh. Technol., vol. 69, no. 7, pp. 8023-8027, Jul. 2020 by O. Lyons, M. F. Hanif, M. Juntti, L.-N. Tran
Allows to reproduce the figures and the appendix of the paper "Correctly Modeling TX and RX Chain in (Distributed) Massive MIMO - New Fundamental Insights on Coherency"
Simulation code for "Fast Converging Algorithm for Weighted Sum Rate Maximization in Multicell MISO Downlink" by Le-Nam Tran, Muhammad Fainan Hanif, Antti Tolli, Markku Juntti, IEEE Signal Processing Letters 19.12 (2012): 872-875
Uplink frequency tracking QO-100
Basic examples to handle Sigfox downlink requests
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