Estimation of Gauss Mixing Models with Expectation Maximum in Cognitive Radios

Year 2020, Issue: 19, 588 - 595, 31.08.2020

Fatih Yavuz Ilgın

https://doi.org/10.31590/ejosat.726040

Abstract

Nowadays, it is known that there is a constantly increasing demand for the radio frequency spectrum. The biggest reason for this situation is the constantly increasing data sizes in wireless communication systems. Therefore, Cognitive Radio (BR) systems are potential technologies that can be a solution to future spectrum shortage problems. In the BR systems, the probability distribution function of the signal to be detected is utilized at the basis of spectrum detection. The probability distribution functions of the signals perceived by BR users according to their spatial location, which will perform spectrum detection in wireless communication systems, vary. The purpose of this study is to predict the common Gaussian mix model of signals perceived by different BR users using the expectation maximization algorithm. In the study, simulation results were performed according to different noise levels and different number of cognitive radio users in terms of spatial differences of different BR users. Thus, the estimated Gaussian mix models can be used to predict different spectrum sensing models.

Keywords

Cognitive Radio, Expectation Maximization, Spectrum Efficiency, Spectrum Sensing, Optimization

Bilişsel Radyolarda Beklenti Maksimizasyonu ile Gauss Karışım Modelleri Kestirimi

Abstract

Günümüzde radyo frekans spektrumuna sürekli artan bir talep olduğu bilinmektedir. Bu durumun en büyük sebebi kablosuz haberleşme sistemlerinde iletilen veri boyutlarının sürekli artmasıdır. Bu nedenle Bilişsel Radyo (BR) sistemleri gelecekte yaşanacak spektrum kıtlığı problemlerine çözüm olabilecek potansiyel teknolojilerdir. BR sistemlerinde spektrum algılamanın temelinde algılanacak işaretin olasılık dağılım fonksiyonundan faydalanılmaktadır. Kablosuz haberleşme sistemlerinde spektrum algılama işlemini gerçekleştirecek olan BR kullanıcılarının uzaysal konumuna göre algıladığı işaretlerin olasılık dağılım fonksiyonları değişiklik göstermektedir. Bu çalışmanın amacı beklenti maksimizasyonu algoritması kullanarak farklı BR kullanıcıları tarafından algılanan işaretlerin, ortak Gauss karışım modelinin tahmin edilmesidir. Yapılan çalışmada benzetim sonuçları farklı BR kullanıcılarının uzaysal farklılıklarını içermesi açısından farklı gürültü seviyeleri ve farklı sayıda Bilişsel Radyo kullanıcı sayısına göre gerçekleştirilmiştir. Böylece tahmin edilen Gauss karışım modelleri kestirimi farklı spektrum algılama modellerine temel oluşturmak için kullanılabilir.

Keywords

Bilişsel Radyo, Beklenti Maksimizasyonu, Spektrum Verimliliği, Spektrum Algılama, Optimizasyon

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