… the distributed machine learning (DML) technique to enable the reliable downlink channel
estimation. Specifically, we firstly build a downlink channel estimation neural network shared …

… the overhead due to pilot transmission for channel estimation can be prohibitive in … )-based
joint pilot design and downlink channel estimation scheme for frequency division duplex (FDD…

… Deep learning methods can be particularly useful to solve problems for which 1) we do not
… for downlink channel estimation which are blind (ie, does not require explicit downlink pilot …

… channel estimation schemes. To circumvent this fundamental constraint, we design a machine
learning (ML… the power allocation problem in the downlink of mMIMO networks. The use of …

… channel estimation (CE) schemes. To relax this stringent constraint, we design a machine
learning … “Impact of general channel aging conditions on the downlink performance of massive …

… phase for a wireless energy transfer system and demonstrated that downlink channel
estimation is necessary to harvest energy feedback information. In the considered system, a DNN …

… channel estimation scheme for the massive multiple-input multiple-output (MIMO) system.
Unlike existing studies, we develop the channel estimation … We consider the downlink of a …

… In the following, we present CNNs that estimate the channel estimation error covariance
matrices in the uplink and the estimation error variances in the downlink. 1) Uplink scenario: The …

… the downlink channel estimation … a channel estimation network based on deep learning,
called ChanEstNet. ChanEstNet uses the convolutional neural network (CNN) to extract channel …

… an uplink-aided downlink channel acquisition framework using deep learning to reduce such
… Toward this end, the pilot design and channel estimation modules in this work are jointly …