Xuming Fang

TL;DR: This survey conducts a comprehensive review on the medium access control layer (MAC) related issues for the IEEE 802.11ay, including spatial sharing and interference mitigation technologies, and presents an in-depth survey on beamforming training, beam tracking, single- user multiple-input-multiple-output beamforming, and multi-user multiple- input- multiple- Output beamforming.

TL;DR: Deep learning could be a powerful tool to mitigate the complexity of RRM problems in dense mmWave networks through a deep learning-based beam management and interference coordination method, through which the conventional complex BM-IC algorithm is transformed into a deep neural network (DNN)-based approximation.

TL;DR: A handover trigger decision scheme based on GM(1, n) model of the grey system theory is proposed that is capable of triggering handover in advance effectively and of enhancing handover success probability remarkably.

TL;DR: An optimized handover scheme is proposed, in which the coordinated multiple point transmission technology and dual vehicle station coordination mechanism are applied to improve the traditional hard handover performance of LTE.

TL;DR: A decentralized algorithm based on HMBCRANs architecture and binary log-linear learning is proposed to obtain the optimal pure strategy Nash equilibrium of the proposed game, in which a concurrent multi-player selection scheme and an information exchanging protocol among players are developed to reduce the complexity and signal overheads.