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

Şakir Şimşir

Makale detayları

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

Yazarlar:

Şakir Şimşir

Yayıncı:

Nigde Omer Halisdemir University

Ana Başlıklar:

Memnuniyet ve Optimizasyon | Radyo Frekansı Mühendisliği

Dergi:

Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi Vol.13 Issue 4, pp.1315-1326

Belge Tipi:

Makale

Yayın Tarihi:

10/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001329707

pISSN:

2564-6605

Anahtar kelimeler:

Özet:

 MIMO-FBMCOQAM system, which is obtained by applying the multiple-input multiple output MIMO technology to the filter bank multicarrieroffset quadrate amplitude modulation FBMCOQAM 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-FBMCOQAM 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.

 MIMO-FBMCOQAM system, which is obtained by applying the multiple-input multiple output MIMO technology to the filter bank multicarrieroffset quadrate amplitude modulation FBMCOQAM 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-FBMCOQAM 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.

 MIMO-FBMCOQAM system, which is obtained by applying the multiple-input multiple output MIMO technology to the filter bank multicarrieroffset quadrate amplitude modulation FBMCOQAM 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-FBMCOQAM 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.

 Çoklu-giriş çoklu-çıkış MIMO teknolojisinin filtre bankası çoklu taşıyıcıofset dördün genlik modülasyonuna FBMCOQAM uygulanması sonucu elde edilen MIMO-FBMCOQAM sistemi, kablosuz haberleşmede karşılaşılan birçok soruna çare olabilecek önemli özellikleri bünyesinde barındırmaktadır. Öte yandan, MIMO-FBMCOQAM 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.

Makale detayları

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

Yazarlar:

Şakir Şimşir

Yayıncı:

Nigde Omer Halisdemir University

Ana Başlıklar:

Memnuniyet ve Optimizasyon | Radyo Frekansı Mühendisliği

Dergi:

Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi Vol.13 Issue 4, pp.1315-1326

Belge Tipi:

Makale

Yayın Tarihi:

10/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001329707

pISSN:

2564-6605

MIMO

Symbol detection

FBMC/OQAM

Maximum likelihood

Cuckoo search algorithmMIMO

Sembol algılama

FBMC/OQAM

Maksimum olasılık

Guguk kuşu arama algoritması

Sayı

Makale detayları

Yazarlar: Şakir Şimşir

Yayıncı: Nigde Omer Halisdemir University

Ana Başlıklar: Memnuniyet ve Optimizasyon | Radyo Frekansı Mühendisliği

Dergi: Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi Vol.13 Issue 4, pp.1315-1326

Belge Tipi: Makale

Yayın Tarihi: 10/2024

Belge Dili: Türkçe

Document ID (Org No.): 2001329707

pISSN: 2564-6605

Sayı

Yazarlar:

Şakir Şimşir

Yayıncı:

Nigde Omer Halisdemir University

Ana Başlıklar:

Memnuniyet ve Optimizasyon | Radyo Frekansı Mühendisliği

Dergi:

Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi Vol.13 Issue 4, pp.1315-1326

Belge Tipi:

Makale

Yayın Tarihi:

10/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001329707

pISSN:

2564-6605