MIMO-FBMC/OQAM sisteminde ayrık guguk kuşu arama algoritması kullanılarak sembol vektörlerinin algılanması

Öz

Çoklu-giriş çoklu-çıkış (MIMO) teknolojisinin filtre bankası çoklu taşıyıcı/ofset dördün genlik modülasyonuna (FBMC/OQAM) uygulanması sonucu elde edilen MIMO-FBMC/OQAM sistemi, kablosuz haberleşmede karşılaşılan birçok soruna çare olabilecek önemli özellikleri bünyesinde barındırmaktadır. Öte yandan, MIMO-FBMC/OQAM sisteminde sembol vektörlerini alıcıda en doğru şekilde algılayabilen etkili bir sembol dedektörüne ihtiyaç duyulmaktadır. Geleneksel maksimum olasılık (ML) dedektörü, kusursuz bir sembol algılama performansına sahiptir. Ancak alıcıya ulaşan sinyal üzerinden hangi sembol vektörünün iletilmiş olduğuna karar verirken, oluşabilecek bütün sembol kombinasyonlarını denemesi, ML dedektörünün karmaşıklığını oldukça yüksek seviyelere çıkarmaktadır. İdeal bir sembol dedektöründen, sembol vektörlerini minimum hata ile tespit etmesi ve bu işi sistem karmaşıklığını çok fazla artırmadan gerçekleştirmesi beklenir. Bu çalışmada, söz konusu beklentiye uygun bir sembol dedektörü geliştirmek için klasik ML dedektörü modifiye edilmiştir. Araştırma uzayında yer alan olası bütün sembol kombinasyonlarını tek tek deneyerek doğru sonuca ulaşmak yerine, sembol vektörleri optimize edilerek, optimum çözüme en kısa yoldan ulaşma yoluna gidilmiştir. Bu amaçla, birçok alanda yaygın olarak kullanılan guguk kuşu arama (CS) algoritmasının etkili bir ayrık versiyonu (DCS) kullanılmıştır. Söz konusu modifikasyon sonucu elde edilen DCS-ML stratejisi ile optimum çözüme oldukça yakın sonuçlar elde edilmekle kalmayıp, klasik ML dedektörünün karmaşıklığı büyük oranda düşürülmüştür.

Anahtar Kelimeler

• MIMO
• Sembol algılama
• FBMC/OQAM
• Maksimum olasılık
• Guguk kuşu arama algoritması

Detection of symbol vectors using discrete cuckoo search algorithm in MIMO-FBMC/OQAM system

Abstract

MIMO-FBMC/OQAM system, which is obtained by applying the multiple-input multiple output (MIMO) technology to the filter bank multicarrier/offset quadrate amplitude modulation (FBMC/OQAM) incorporates important features that can solve many problems encountered in wireless communication. On the other hand, an efficient symbol detector that can detect the symbol vectors at the receiver in the most accurate way is required in the MIMO-FBMC/OQAM system. The conventional maximum likelihood detector has a flawless symbol detection performance. However, when deciding which symbol vector has been transmitted based on the signal reaching the receiver, trying all of the possible symbol combinations enhances the complexity of ML to very high levels. It is expected from an ideal symbol detector to detect the symbol vectors with minimum error and do this task without increasing the system complexity too much. In this study, the classical ML detector was modified to develop a symbol detector compatible with the aforementioned expectation. Instead of reaching the correct result by trying all of the possible symbol combinations existing in the search space one by one, it was tried to reach the optimum solution in the shortest way by optimizing the symbol vectors. To this end, an efficient discrete version (DCS) of the cuckoo search (CS) algorithm, which is commonly used in many fields, was employed. With the DCS-ML strategy obtained as a result of the aforementioned modification, not only the results that are very close to the optimal solution were achieved, but also the complexity of the classical ML detector was substantially reduced.

Keywords

• MIMO
• Symbol detection
• FBMC/OQAM
• Maximum likelihood
• Cuckoo search algorithm

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