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Title: | Contribution to the Development of Advanced Techniques for Massive MIMO Communication Systems |
Authors: | TABA, Somia |
Keywords: | 5G, OFDM, PAPR, PTS, PSO, WOA |
Issue Date: | 5-Oct-2023 |
Abstract: | The relentlessdemand for faster data rates, extremelylowlatency and significantimprovements in quality of service (QoS) has givenrise to the emergence of the fifthgeneration (5G) of wireless transmission technologies. This latestgeneration of cellular networks has broughtmanyadvances over previousgenerations. 5G uses a powerfulwaveformknown as orthogonal frequency division multiplexing (OFDM) due to itsinherentadvantagessuch as high capacity, immunity to multipath fading and the ease of implementation. However, the drawback of this technique isits high peak-to-average power ratio (PAPR), whichdegrades signal quality at the receiver and hampers the overallefficiency of the 5G system. Variousmethods have been proposed in the literature to mitigate PAPR in OFDM systems. In the second chapter of thisthesis, weprovided a comprehensiveoverview of the most effective PAPR reduction techniques and concludedthat the partial transmission sequence (PTS) technique was the mostpromisingamongthem. However, despiteitsefficiency and distortion-free nature, thisschemesuffersfrom an exponentiallyincreasingcomplexity. Therefore, the aim of thisthesisis to reduce PAPR levels in OFDM systems by introducing a new PTS technique thatcreates a good compromise between PAPR mitigation and complexity. To achievethis goal, two contributions have been presented, in which the PTS technique has been combinedwith efficient meta-heuristicalgorithms, resulting in new PTS alternatives thatoffer efficient PAPR reductionwhilemaintainingcompetitivecomplexity. The results are comparedwithother techniques described in the existingliterature, validating the effectiveness of the proposedapproaches |
URI: | http://dspace.univ-guelma.dz/jspui/handle/123456789/14620 |
Appears in Collections: | Thèses de Doctorat |
Files in This Item:
File | Description | Size | Format | |
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Thèse de doctorat TABA SOMIA.pdf | 10,45 MB | Adobe PDF | View/Open |
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