Massive MIMO systems for 5G and beyond networks—overview, recent trends, challenges, and future research direction
The global bandwidth shortage in the wireless communication sector has motivated the
study and exploration of wireless access technology known as massive Multiple-Input …
study and exploration of wireless access technology known as massive Multiple-Input …
Deep learning-aided 6G wireless networks: A comprehensive survey of revolutionary PHY architectures
Deep learning (DL) has proven its unprecedented success in diverse fields such as
computer vision, natural language processing, and speech recognition by its strong …
computer vision, natural language processing, and speech recognition by its strong …
Deep learning for mmWave beam and blockage prediction using sub-6 GHz channels
Predicting the millimeter wave (mmWave) beams and blockages using sub-6 GHz channels
has the potential of enabling mobility and reliability in scalable mmWave systems. Prior work …
has the potential of enabling mobility and reliability in scalable mmWave systems. Prior work …
Deep reinforcement learning for intelligent reflecting surfaces: Towards standalone operation
The promising coverage and spectral efficiency gains of intelligent reflecting surfaces (IRSs)
are attracting increasing interest. To adopt these surfaces in practice, however, several …
are attracting increasing interest. To adopt these surfaces in practice, however, several …
Pruning the pilots: Deep learning-based pilot design and channel estimation for MIMO-OFDM systems
With the large number of antennas and subcarriers the overhead due to pilot transmission
for channel estimation can be prohibitive in wideband massive multiple-input multiple-output …
for channel estimation can be prohibitive in wideband massive multiple-input multiple-output …
Reinforcement learning of beam codebooks in millimeter wave and terahertz MIMO systems
Millimeter wave (mmWave) and terahertz MIMO systems rely on pre-defined beamforming
codebooks for both initial access and data transmission. These pre-defined codebooks …
codebooks for both initial access and data transmission. These pre-defined codebooks …
Dual CNN-based channel estimation for MIMO-OFDM systems
Recently, convolutional neural network (CNN)-based channel estimation (CE) for massive
multiple-input multiple-output communication systems has achieved remarkable success …
multiple-input multiple-output communication systems has achieved remarkable success …
Integration of hybrid networks, AI, ultra massive-MIMO, THz frequency, and FBMC modulation toward 6G requirements: A review
The fifth-generation (5G) wireless communications have been deployed in many countries
with the following features: wireless networks at 20 Gbps as peak data rate, a latency of 1 …
with the following features: wireless networks at 20 Gbps as peak data rate, a latency of 1 …
Application of reinforcement learning and deep learning in multiple-input and multiple-output (MIMO) systems
The current wireless communication infrastructure has to face exponential development in
mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems …
mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems …
Channel estimation for one-bit multiuser massive MIMO using conditional GAN
Channel estimation is a challenging task, especially in a massive multiple-input multiple-
output (MIMO) system with one-bit analog-to-digital converters (ADC). Traditional deep …
output (MIMO) system with one-bit analog-to-digital converters (ADC). Traditional deep …