2016/05/19 by Zeineb Guizani, Guizani, Zeineb, Noureddine Hamdi +1
Computer Science · Engineering · Mathematics · #Advanced MIMO Systems Optimization #Advanced Wireless Communication Techniques #Algorithm #Cellular network #Cognitive radio #Computer network #Computer science #Constraint (computer-aided design) #Distributed computing #Engineering #FOS: Computer and information sciences #Heuristic #Integer (computer science) #Interference (communication) #Mathematical optimization #Mathematics #Millimeter-Wave Propagation and Modeling #Networking and Internet Architecture (cs.NI) #Optimization problem #Quality of service #Radio resource management #Resource allocation #Resource management (computing) #Scheme (mathematics) #Signal-to-noise ratio (imaging) #Spectral efficiency #Spectrum management #Telecommunications #Telecommunications and Broadcasting Technologies #Telecommunications link #Throughput #Underlay #Wireless #Wireless network #cs.NI
paper · pdf · doi:10.48550/arxiv.1605.06020
Accepted in IEEE Symposium on Computers and Communications June, 2016
arxiv created 2016/05/19 · openalex publication_date 2016/05/19 · arxiv updated 2016/05/20 · openalex created_date 2022/10/05 · openalex updated_date 2026/08/05
The work presented in this paper deals with the issue of massive demands for\nhigher capacity. For that matter, we investigate the spectrum resource\nmanagement in outdoor mmWave cell for the uplink of cellular and D2D\ncommunications. Indeed, we provide a first insight how to optimize the system\nperformance in terms of achievable throughput while realizing a compromise\nbetween the large number of admitted devices and the generated interference\nconstraint. We propose a mathematical formulation of the optimization objective\nwhich falls in the mixed integer-real optimization scheme. To overcome its\ncomplexity, we apply a heuristic algorithm and test its efficiency through\nsimulation results with a particular regard to the BER impact in the QoS.\n