Orthogonal Frequency Division Multiplexing

Orthogonal Frequency Division Multiplexing (OFDM) is a digital modulation scheme that divides a wideband communication channel into many narrowband subcarriers, improving spectral efficiency and mitigating intersymbol interference. Current research heavily emphasizes improving OFDM's performance in challenging environments through techniques like deep learning-based channel estimation and signal detection, often employing neural network architectures such as transformers, convolutional neural networks, and recurrent neural networks. These advancements aim to enhance OFDM's robustness and efficiency in applications ranging from 5G and beyond ultra-reliable low-latency communications (URLLC) to multi-robot systems and Internet of Things (IoT) devices.