… Since the first generation (1G) wireless communication network entered the market in the
1980s, the world has been dramatically changed by the development of mobile communication …

… wireless communications. To overcome this limit, we propose and demonstrate a recurrent
neural network (… -tolerant RC indoor optical wireless communication system. The experiments …

… in network management and security. For network traffic classification in wireless communications,
… dimensions of convolutional neural network (CNN) to network traffic classification by …

This chapter provides a comprehensive introduction to channel prediction methods with an
emphasis on neural network‐based prediction. It first briefly describes adaptive transmission …

… call a sliding bidirectional recurrent neural network (SBRNN) is … We evaluate this algorithm,
as well as other neural network (… She is an author of the book Wireless Communications and …

… -valued neural networks (CVNNs) to predict future channel states in fast-fading multipath
mobile communications. CVNN is suitable for dealing with a fading communication channel as …

… Some researchers trained binarized neural networks (BNNs) by directly binarizing [17], …
Inspired by their works, we study optimizing binarized neural networks (BNNs) for WII. BNN …

… a wireless powered communication network (WPCN). We provide a study and analysis of a
deep neural network … In this scheme, the deep neural network provides an optimized solution …

… and is a vital technique for intelligent wireless systems. Conventional DOA estimation
methods … to lift these limitations by combining artificial neural networks (ANNs) with space‐time‐…

… affect the performance of indoor optical wireless communication systems. The presence
of either … The discrete wavelet transform (DWT) and the artificial neural network (ANN)-based …