… deep reinforcement learning technique into the UAV navigation through the massive MIMO.
… 1) First, we employ the deep reinforcement learning technique to achieve UAV navigation …

… We consider a CF massive MIMO network with M single-antenna APs and K single-antenna
UEs, where the APs are connected to a central processing unit (CPU) via the perfect …

… Second option, called reinforcement learning assumes that target dataset is not known, but
… approach for beamforming namely deep adversarial reinforcement learning. The main idea is …

… None of the above works considered CF massive MIMO. In [11], a deep CNN (DCNN) was
… algorithm for power allocation in CF massive MIMO. In reinforcement learning, the idea is to …

… We propose a reinforcement learning (RL) based algorithm for cognitive multitarget
detection in the presence of unknown disturbance statistics. The radar acts as an agent that …

Reinforcement learning (RL) based approaches in massive multiple input multiple output (mMIMO)
arrays allow target detection in unknown environments. However, there are two main …

… tion in a cell-free massive multiple-input multiple-output (MIMO) system is investigated. …
We propose to solve this challenging problem by model-free deep reinforcement learning (…

… scheme for multi-cell M-MIMO system using deep reinforcement learning (DRL). At first, a …
the uplink transmission of a multicell M-MIMO system, which consists of L cells each contain…

… with massive-MIMO base stations, two function approximation based reinforcement learning
… We first derive the ASP for multi-user massive MIMO systems and conclude that for inter…

… networks are expected to utilize the Massive Multiple-Input Multiple-Output technology (…
a sub-class of Machine Learning techniques named Reinforcement Learning (RL). Because …