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

Şakir Şimşir

Makale detayları

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

Yazarlar:

Şakir Şimşir

Yayıncı:

Erciyes University

Ana Başlıklar:

Elektrik Mühendisliği (Diğer)

Dergi:

Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi Vol.40 Issue 2, pp.393-407

Belge Tipi:

Makale

Yayın Tarihi:

8/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001326273

pISSN:

1012-2354

Anahtar kelimeler:

Özet:

 Although multiple-input multiple-output  filter bank multicarrieroffset quadrature amplitude modulation MIMO-FBMCOQAM, 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-FBMCOQAM 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.

 Although multiple-input multiple-output  filter bank multicarrieroffset quadrature amplitude modulation MIMO-FBMCOQAM, 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-FBMCOQAM 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.

 Although multiple-input multiple-output  filter bank multicarrieroffset quadrature amplitude modulation MIMO-FBMCOQAM, 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-FBMCOQAM 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.

 Son yıllarda geliştirilmiş önde gelen iletim teknolojileri arasında yer alan çoklu-giriş çoklu-çıkış - filtre bankası çoklu taşıyıcıofset dördün genlik modülasyonu MIMO-FBMCOQAM, kablosuz iletişime has birçok problemi çözme yetisine sahip olmakla birlikte, alıcısında etkili bir sembol dedektörüne gereksinim duymaktadır. Bu çalışmada, MIMO-FBMCOQAM 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.

Makale detayları

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

Yazarlar:

Şakir Şimşir

Yayıncı:

Erciyes University

Ana Başlıklar:

Elektrik Mühendisliği (Diğer)

Dergi:

Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi Vol.40 Issue 2, pp.393-407

Belge Tipi:

Makale

Yayın Tarihi:

8/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001326273

pISSN:

1012-2354

Crow Search Algorithm

FBMC/OQAM

Symbol Detection

MIMO

Maximum LikelihoodKarga Arama Algoritması

FBMC/OQAM

Sembol Algılama

MIMO

Maksimum Olasılık

Sayı

Makale detayları

Yazarlar: Şakir Şimşir

Yayıncı: Erciyes University

Ana Başlıklar: Elektrik Mühendisliği (Diğer)

Dergi: Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi Vol.40 Issue 2, pp.393-407

Belge Tipi: Makale

Yayın Tarihi: 8/2024

Belge Dili: Türkçe

Document ID (Org No.): 2001326273

pISSN: 1012-2354

Sayı

Yazarlar:

Şakir Şimşir

Yayıncı:

Erciyes University

Ana Başlıklar:

Elektrik Mühendisliği (Diğer)

Dergi:

Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi Vol.40 Issue 2, pp.393-407

Belge Tipi:

Makale

Yayın Tarihi:

8/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001326273

pISSN:

1012-2354