2021/02/02 by Zachary Grey, Susanna Mosleh, Grey, Zachary J. +9
Computer Science · Engineering · #90B18 (secondary) #94A05 (primary) #Advanced MIMO Systems Optimization #FOS: Computer and information sciences #FOS: Electrical engineering #Machine Learning (cs.LG) #Millimeter-Wave Propagation and Modeling #Signal Processing (eess.SP) #Wireless Networks and Protocols #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2102.09047
openalex publication_date 2021/02/02 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
To meet the ever-growing demands of data throughput for forthcoming and\ndeployed wireless networks, new wireless technologies like Long-Term Evolution\nLicense-Assisted Access (LTE-LAA) operate in shared and unlicensed bands.\nHowever, the LAA network must co-exist with incumbent IEEE 802.11 Wi-Fi\nsystems. We consider a coexistence scenario where multiple LAA and Wi-Fi links\nshare an unlicensed band. We aim to improve this coexistence by maximizing the\nkey performance indicators (KPIs) of these networks simultaneously via\ndimension reduction and multi-criteria optimization. These KPIs are network\nthroughputs as a function of medium access control protocols and physical layer\nparameters. We perform an exploratory analysis of coexistence behavior by\napproximating active subspaces to identify low-dimensional structure in the\noptimization criteria, i.e., few linear combinations of parameters for\nsimultaneously maximizing KPIs. We leverage an aggregate low-dimensional\nsubspace parametrized by approximated active subspaces of throughputs to\nfacilitate multi-criteria optimization. The low-dimensional subspace\napproximations inform visualizations revealing convex KPIs over mixed active\ncoordinates leading to an analytic Pareto trace of near-optimal solutions.\n