2020/02/13 by Hongyu Xiang, Mugen Peng, Xiang, Hongyu +5 · 1 citation
Computer Science · Engineering · #Advanced MIMO Systems Optimization #Artificial intelligence #Base station #Computer network #Computer science #Distributed computing #Energy Harvesting in Wireless Networks #FOS: Computer and information sciences #FOS: Electrical engineering #Key (lock) #Mathematical optimization #Mode (computer interface) #Networking and Internet Architecture (cs.NI) #Q-learning #Reinforcement learning #Resource allocation #Selection (genetic algorithm) #Signal Processing (eess.SP) #Software-Defined Networks and 5G #Telecommunications link #cs.NI #eess.SP #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2002.08419
published in arXiv (Cornell University) (Cornell University)
arxiv created 2020/02/13 · openalex publication_date 2020/02/13 · arxiv updated 2020/02/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
The mode selection and resource allocation in fog radio access networks (F-RANs) have been advocated as key techniques to improve spectral and energy efficiency. In this paper, we investigate the joint optimization of mode selection and resource allocation in uplink F-RANs, where both of the traditional user equipments (UEs) and fog UEs are served by constructed network slice instances. The concerned optimization is formulated as a mixed-integer programming problem, and both the orthogonal and multiplexed subchannel allocation strategies are proposed to guarantee the slice isolation. Motivated by the development of machine learning, two reinforcement learning based algorithms are developed to solve the original high complexity problem under traditional and fog UEs' specific performance requirements. The basic idea of the proposals is to generate a good mode selection policy according to the immediate reward fed back by an environment. Simulation results validate the benefits of our proposed algorithms and show that a tradeoff between system power consumption and queue delay can be achieved.