FLEXIBLE SPECTRUM ALLOCATION FOR NEXT GENERATION DISTRIBUTED WIRELESS NETWORKS
Author
Offidani, Serena
Term
10. term
Publication year
2008
Abstract
Nettjenester, teknologi og regulering er i hastig forandring, hvilket baner vejen for Next Generation (NextG) netværk. Ligesom tidligere systemer står NextG over for en stigende efterspørgsel efter radiospektrum—det begrænsede område af frekvenser, der bruges til trådløs kommunikation. Spektrum tildeles normalt i faste frekvensbånd til bestemte tjenestekategorier for at undgå interferens. For at udnytte spektret mere effektivt undersøges to delingsmodeller: underlay‑tilgangen (Ultra‑Wideband, UWB) og overlay‑tilgangen (Cognitive Radio, CR). Kognitive radioer kan registrere, hvilke frekvenser der er ledige, vælge passende transmissionsindstillinger og holde interferensen lav. Dette arbejde har til formål at fordele de tilgængelige radiospektrumressourcer retfærdigt mellem mange enheder, der opererer i samme område, selv når de kan forstyrre hinanden. Det ser på intelligente strategier for spektrumanvendelse, herunder en FSU‑algoritme baseret på SINR (et mål for signalets kvalitet i forhold til interferens og støj) og en interferenstærskel‑tilgang, samt Spectrum Load Balancing inspireret af water‑filling‑ideen om at udjævne ressourcer. Målet er at understøtte distribueret Quality of Service (QoS) og øge spektrets effektivitet.
Network services, technologies, and regulation are changing, ushering in Next Generation (NextG) networks. Like earlier systems, NextG faces growing demand for radio spectrum—the limited range of frequencies used for wireless communication. Spectrum is typically assigned in fixed frequency bands to specific service categories to prevent interference. To use spectrum more efficiently, two sharing models are considered: the underlay approach (Ultra-Wideband, UWB) and the overlay approach (Cognitive Radio, CR). Cognitive radios can sense which frequencies are free, choose suitable transmission settings, and keep interference low. This thesis aims to fairly distribute the available radio spectrum among many devices operating in the same area, even when they may interfere with one another. It examines intelligent spectrum-use strategies, including an FSU algorithm based on SINR (a measure of signal quality relative to interference and noise) and an interference threshold approach, as well as Spectrum Load Balancing inspired by the water-filling idea of leveling resources. The goal is to support distributed Quality of Service (QoS) and increase spectrum efficiency.
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