Interference Channel

Interference channels model communication scenarios where multiple transmitters simultaneously send signals to multiple receivers, leading to signal interference. Current research focuses on developing advanced detection and mitigation techniques, employing machine learning models like neural networks, belief propagation, and deep reinforcement learning to optimize symbol detection, precoding, and power allocation. These efforts aim to improve data transmission efficiency and robustness in various communication systems, particularly in scenarios with imperfect channel knowledge or bursty noise, impacting the design of next-generation wireless networks. The ultimate goal is to achieve near-optimal performance while maintaining low computational complexity.