Network Topology Reconfiguration for FSO-Based Fronthaul/Backhaul in 5G+ Wireless Networks

• Published in: IEEE access Vol. 6; pp. 69426 - 69437
• Main Authors: Gu, Zhiqun, Zhang, Jiawei, Ji, Yuefeng, Bai, Lin, Sun, Xiang
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Free space optics; Free space optics (FSO); FSO-based fronthaul/backhaul; Greedy algorithms; Heuristic algorithms; Laser beams; Mixed integer; multi-criteria optimization; Network topologies; Network topology; Nonlinear programming; Optical communication; Optical transmitters; Power consumption; Reconfiguration; Reliability; Topology; Topology optimization; topology reconfiguration; Weather; Wireless networks
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2018.2880880

Using free-space optics (FSO) in the mobile fronthaul/backhaul networks is a promising solution that can potentially enhance the capacity of mobile networks. The main challenge of establishing FSO-based fronthaul/backhaul networks is the dynamic feature of the networks, i.e., the fragile links under adverse weather conditions and the dynamic traffic demands among small cells. Topology reconfiguration is proposed to dynamically rearrange the FSO links. In this paper, two types of network reconfigurations are investigated, in which the proactive network reconfiguration is to proactively optimize the topology of the FSO-based fronthaul/backhaul networks for each specific time period based on the statistics of the network, and the reactive reconfiguration is to actively adjust the topology when traffic demands and link states are changed. The proactive network reconfiguration is formulated as a mixed integer nonlinear programming (MINLP) problem, which jointly optimizes the network throughput and power consumption of the FSO-based fronthaul/backhaul networks. A greedy algorithm is proposed to derive the solution of the proposed problem. After the network topology having been reconfigured by solving the MINLP problem, two reactive reconfiguration algorithms are designed to optimally adjust the network topology once a link failure and demand explosion occur, respectively, to further enhance the network throughput and reduce the power consumption. The performance of the algorithms is demonstrated via extensive simulations.