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

Yıl 2024, Cilt: 13 Sayı: 4, 1315 - 1326, 15.10.2024

Şakir Şimşir

https://doi.org/10.28948/ngumuh.1484055

Öz

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.

Anahtar Kelimeler

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

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

Kaynakça

• L. J. Cimini, Analysis and simulation of a digital mobile channel using orthogonal frequency division multiplexing. IEEE Transactions on Communications, 33 (7), 665-675, 1985. https://doi.org/10.1109/TCOM.1985.1096357.
• M. Yıldırım, Subcarrier-interactive dual-mode OFDM. IEEE Communications Letters, 27 (5), 1472-1476, 2023. https://doi.org/10.1109/lcomm.2023.3248523.
• Y. Kabalcı, 5g iletişim sistemleri için aday iletim tekniklerinin bit hata oranı başarımlarının araştırılması. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 9 (2), 821-831, 2020. https://doi.org/10.28948/ngumuh.654386.
• B. Farhang-Boroujeny, Filter bank multicarrier modulation: A waveform candidate for 5G and beyond. Advances in Electrical Engineering, 2014, 1-25, 2014. https://doi.org/10.1155/2014/482805.
• R. Nissel, S. Schwarz and M. Rupp, Filter bank multicarrier modulation schemes for future mobile communications. IEEE Journal on Selected Areas in Communications, 35 (8), 1768-1782, 2017. https://doi.org/10.1109/JSAC.2017.2710022.
• R. Zakaria and D. Le Ruyet, On maximum likelihood MIMO detection in QAM-FBMC systems. 21st Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, pp. 183-187, Istanbul, Turkey, 2010.
• R. Nissel, J. Blumenstein and M. Rupp, Block frequency spreading: A method for low-complexity MIMO in FBMC-OQAM. IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), pp. 1-5, Sapporo, Japan, 2017.
• Q. H. Spencer, A. L. Swindlehurst and M. Haardt, Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels. IEEE Transactions on Signal Processing, 52 (2), 461-471, 2004. https://doi.org/10.1109/TSP.2003.821107.
• X. Zhu and R. D. Murch, Performance analysis of maximum likelihood detection in a MIMO antenna system. IEEE Transactions on Communications, 50 (2), 187-191, 2002. https://doi.org/10.1109/26.983313.
• Ş. Şimşir and N. Taşpınar, A novel discrete cuckoo search algorithm-based selective mapping technique to minimize the peak-to-average power ratio of universal filtered multicarrier signal. International Journal of Communication Systems, 33 (18), 1-16, 2020. https://doi.org/10.1002/dac.4640.
• X. Kong, L. Gao, H. Ouyang and S. Li, A simplified binary harmony search algorithm for large scale 0–1 knapsack problems. Expert Systems with Applications, 42 (12), 5337-5355, 2015. https://doi.org/10.1016/j.eswa.2015.02.015.
• M. N. Seyman, Symbol detection based on back tracking search algorithm in MIMO-NOMA systems. Computer Systems Science & Engineering, 40 (2), 795-804, 2022. http://dx.doi.org/10.32604/CSSE.2022.019734.
• H. U. Rehman, S. I. Shah, I. Zaka and J. Ahmad, An MBER–BLAST algorithm for OFDM–SDMA communication using particle swarm optimization. International Journal of Communication Systems, 24 (2), 185-201, 2011. https://doi.org/10.1002/dac.1149.
• A. A. Khan, S. Bashir, M. Naeem, S. I. Shah and X. Li, Symbol detection in spatial multiplexing system using particle swarm optimization meta-heuristics. International Journal of Communication Systems, 21 (12), 1239-1257, 2008. https://doi.org/10.1002/dac.949
• M. Mandloi and V. Bhatia, A low-complexity hybrid algorithm based on particle swarm and ant colony optimization for large-MIMO detection. Expert Systems with Applications, 50, 66-74, 2016. https://doi.org/10.1016/j.eswa.2015.12.008.
• L. Li, W. Meng and S. Ju, A novel artificial bee colony detection algorithm for massive MIMO system. Wireless Communications and Mobile Computing, 16 (17), 3139-3152, 2016. https://doi.org/10.1002/wcm.2754.
• M. N. Seyman and N. Taşpınar, Symbol detection using the differential evolution algorithm in MIMO-OFDM systems. Turkish Journal of Electrical Engineering and Computer Sciences, 21 (2), 373-380, 2013. https://doi.org/10.3906/elk-1103-16.
• S. Chen and Y. Wu, Maximum likelihood joint channel and data estimation using genetic algorithms. IEEE Transactions on Signal Processing, 46 (5), 1469-1473, 1998. https://doi.org/10.1109/78.668813.
• C. Wang, E. K. S. Au, R. D. Murch, W. H. Mow, R. S. Cheng and V. Lau, On the performance of the MIMO zero-forcing receiver in the presence of channel estimation error. IEEE Transactions on Wireless Communications, 6 (3), 805-810, 2007. https://doi.org/10.1109/TWC.2007.05384.
• X. S. Yang and S. Deb, Cuckoo search via Lévy flights. 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), pp. 210-214, Coimbatore, India, 2009.
• T. T. Nguyen and L. Lampe, On partial transmit sequences for PAR reduction in OFDM systems. Transactions on Wireless Communications, 7 (2), 746-755, 2008. https://doi.org/10.1109/TWC.2008.060664.