… First, we introduce convolutional layers so that this approach … decoding algorithm is extended
as deep learning layers to … The input of the auto-decoder is the equalized signal y = y ˆh …

… In the first phase, an adaptive deep neural network (ADNN) … entry in simultaneous action,
but it requires hybrid decoding … related to the entire users and the BS is defined as in Eq. (2). …

… Then, we first apply it to a neural network-based belief … recent advances in deep learning
(DL), a neural network-based … a neural network for joint channel equalization and decoding, …

… and ultra-massive MIMO), deep learning (DL) is introduced to … The joint source-channel
decoder at the BS uses a decoding … Hd is first converted to the angular-delay domain F by Eq. (5) …

… , channel estimation, equalization and FEC decoding. Different … In the first part of the paper,
we design each module of our … channel estimation and channel equalization algorithms with …

… code (other than the one given in Eq. (1)) that would produce … Measurement decoding for
channels with multiple TX/RX … the left), we first do a column by column decoding where the j …

… of a channel equalizer to suppress the effects of wireless … This paper presents the first
attempt of applying DL in MC … Note that under the AWGN channel, we feed the decoder of our …

… operation (ie, channel estimation first and then signal … decoded as a whole (eg, 64 symbols
are detected jointly when the N c = 128 ). Since the performances of the machine learning …

… channel estimator algorithms such as turbo equalization, … length of 512 in the first layer
corresponding to an OFDM block … The decoder in LSTM considers the previous received symbol …

… with the use of machine learning techniques. Very promising … We propose a fully convolutional
encoder and decoder … softmax weights used in the soft assignment in Eq. (5). Since the …