An Advanced Symbol Detection Method Based on Discrete Crow Search Algorithm for MIMO-FBMC/OQAM Transmission Technology

Year 2024, Volume: 40 Issue: 2, 393 - 407, 31.08.2024

Şakir Şimşir

Abstract

Although multiple-input multiple-output – filter bank multicarrier/offset quadrature amplitude modulation (MIMO-FBMC/OQAM), which is among the prominent transmission technologies developed in recent years, has the capability of solving various problems peculiar to wireless communication, it requires an efficient symbol detector at its receiver. In this study, a new symbol detector with both low complexity and high symbol detection performance has been developed for MIMO-FBMC/OQAM system. For this, the classical maximum likelihood (ML) detector, which can detect the symbol vectors perfectly but performs this process by using an exhaustive search procedure that causes a quite high searching cost, was modified. In this modification, the high-cost exhaustive search procedure was disabled and instead, discrete crow search algorithm (DCSA) was integrated to carry out the optimization process of the symbol vectors. Thus, not only the pretty high search cost of the traditional ML method was reduced, but also a near-optimum symbol detection performance was achieved.

Keywords

Crow Search Algorithm, FBMC/OQAM, Symbol Detection, MIMO, Maximum Likelihood

MIMO-FBMC/OQAM İletim Teknolojisi İçin Ayrık Karga Arama Algoritması Tabanlı Gelişmiş Bir Sembol Algılama Yöntemi

Abstract

Son yıllarda geliştirilmiş önde gelen iletim teknolojileri arasında yer alan çoklu-giriş çoklu-çıkış - filtre bankası çoklu taşıyıcı/ofset dördün genlik modülasyonu (MIMO-FBMC/OQAM), kablosuz iletişime has birçok problemi çözme yetisine sahip olmakla birlikte, alıcısında etkili bir sembol dedektörüne gereksinim duymaktadır. Bu çalışmada, MIMO-FBMC/OQAM sistemi için hem düşük karmaşıklı hem de yüksek sembol algılama performansına sahip yeni bir sembol dedektörü geliştirilmiştir. Bunun için, sembol vektörlerini kusursuz bir şekilde algılayabilen ancak bu işlemi oldukça yüksek bir araştırma maliyetine sebep olan kapsamlı arama prosedürü kullanarak gerçekleştiren klasik maksimum olasılık (ML) dedektörü modifiye edilmiştir. Söz konusu modifikasyonda, yüksek maliyetli kapsamlı arama prosedürü devre dışı bırakılarak, yerine sembol vektörlerinin optimizasyon işlemini gerçekleştirmek üzere ayrık karga arama algoritması (DCSA) entegre edilmiştir. Böylelikle, geleneksel ML yönteminin oldukça yüksek olan araştırma maliyeti düşürülmekle kalmayıp, optimuma yakın bir sembol algılama performansı elde edilmiştir.

Keywords

Karga Arama Algoritması, FBMC/OQAM, Sembol Algılama, MIMO, Maksimum Olasılık

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