Cell Free

Cell-free massive MIMO networks aim to improve wireless communication performance by distributing access points across a wide area, eliminating cell boundaries and enhancing coverage uniformity. Current research focuses on optimizing resource allocation (e.g., power control, user association) through advanced algorithms like reinforcement learning (including variations such as twin delayed deep deterministic policy gradient) and Bayesian optimization, often incorporating hybrid MIMO processing and reconfigurable intelligent surfaces. These efforts seek to overcome challenges like limited backhaul capacity and computationally expensive optimization, ultimately leading to more efficient and robust wireless networks with improved spectral efficiency and reduced latency.