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Meta-Learning-Driven Adaptive Codebook Design for Near-Field Communications
Specifically, we first design a deep neural network (DNN) to learn the near-field codebook.
Design and Performance Analysis of Wireless Legitimate Surveillance Systems with Radar Function
We seek to jointly optimize the receive and transmit beamforming vectors to maximize the eavesdropping success probability which is transformed into the difference of signal-to-interference-plus-noise ratios (SINRs) subject to the performance requirements of radar and surveillance.
Multiband Delay Estimation for Localization Using a Two-Stage Global Estimation Scheme
In the coarse stage, we exploit the group sparsity structure of the multiband channel and propose a Turbo Bayesian inference (Turbo-BI) algorithm to achieve a good initial delay estimation based on a coarse signal model, which is transformed from the original multiband signal model by absorbing the carrier frequency terms.
