OFDM Sistemlerinde Verimli Kanal Tahmini için Kızıl Kuyruklu Şahin Algoritması

Öz

Bu çalışma, Kızıl Kuyruklu Şahin Optimizasyonu (RTHO) algoritmasını kullanan 5G kablosuz iletişim sistemleri için yenilikçi bir kanal tahmin metodolojisi sunmaktadır. Önerilen RTHO tabanlı Kanal Tahmini (RTHO-CE) yaklaşımı, Bit Hata Oranını (BER) ve Ortalama Kare Hatayı (MSE) en aza indirerek, önceden istatistiksel bilgi, eğitim veri setleri veya istikrarlı kanal istatistikleri gerektirmeden dinamik ortamlarda kablosuz kanalları doğru bir şekilde tahmin eder. Algoritma, pilot yoğunlukları (1/3, 1/6, 1/9, 1/12) ve modülasyon şemaları (16QAM, 64QAM, 256QAM, QPSK) arasında kapsamlı bir değerlendirme yaparak, BER ve MSE metriklerini En Küçük Kareler (LS) ve Minimum Ortalama Kareler Hatası (MMSE) metodolojileriyle karşılaştırır. 5G Yeni Radyo TDL-300 kanal modellerinde yapılan simülasyon sonuçları, RTHO-CE'nin MMSE optimalitesine göre %22,7'lik bir bozulma ile BER performansı elde ederken, QPSK modülasyonu ve 1/6 pilot yoğunluğu ile 20 dB SNR'de LS'ye göre %22,1'lik bir iyileşme sağladığını ortaya koymaktadır. Önerilen algoritma, farklı pilot yoğunluklarında güvenilir performansını sürdürür ve pilot oranı 1/3'ten 1/12'ye düştüğünde sadece %17'lik bir azalma gösterir. Zorlu yüksek hareketlilikli TDL-D300 senaryolarında, RTHO-CE daha güçlü bir uyarlanabilirlik gösterir, MMSE'yi %22,3 oranında geride bırakır ve LS'ye kıyasla %93,45'lik bir iyileşme sağlar. Bu sonuçlar, özellikle önceden kanal istatistiklerinin mevcut olmadığı durumlarda, 5G sistemleri için etkili bir kanal tahmin yöntemi olarak potansiyelini vurgulamaktadır.

Anahtar Kelimeler

• Kızıl Kuyruklu Şahin Algoritması
• Kanal Kestirimi
• 5G
• OFDM

Red-Tailed Hawk Algorithm for Efficient Channel Estimation in OFDM Systems

Öz

This study presents an innovative channel estimation methodology for 5G wireless communication systems utilizing the Red-Tailed Hawk Optimization (RTHO) algorithm. The proposed RTHO-based Channel Estimation (RTHO-CE) approach accurately estimates wireless channels in dynamic environments without requiring prior statistical knowledge, training datasets, or stable channel statistics by minimizing Bit Error Rate (BER) and Mean Square Error (MSE). The algorithm improves pilot-based Orthogonal Frequency Division Multiplexing (OFDM) systems performance under frequency-selective fading channels through comprehensive evaluation across pilot densities (1/3, 1/6, 1/9, 1/12) and modulation schemes (16QAM, 64QAM, 256QAM, QPSK), comparing BER and MSE metrics against Least Squares (LS) and Minimum Mean Square Error (MMSE) methodologies. Simulation results on 5G New Radio TDL-300 channel models reveal that RTHO-CE achieves BER performance with 22.7% degradation from MMSE optimality while providing 22.1% improvement over LS at 20 dB SNR with QPSK modulation and 1/6 pilot density. The proposed algorithm sustains reliable performance across different pilot densities, showing only a 17% reduction when the pilot ratio decreases from 1/3 to 1/12. Under challenging high-mobility TDL-D300 scenarios, RTHO-CE demonstrates stronger adaptability, surpassing MMSE by 22.3% and delivering a 93.45% improvement compared to LS. These results highlight its potential as an effective channel estimation method for 5G systems, especially in cases where prior channel statistics are not available.

Anahtar Kelimeler

• Red-Tailed Hawk Algorithm
• Channel Estimation
• 5G
• OFDM

Kaynakça

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