Year 2020, Volume , Issue 19, Pages 466 - 474 2020-08-31

Bio-Inspired Pilot Design Approach based on Genetic Algorithm for OFDM-IDMA Scheme
OFDM-IDMA Sistemi İçin Genetik Algoritmaya Dayalı Biyo-İlhamlı Pilot Dizayn Yaklaşımı

Necmi TAŞPINAR [1] , Şakir ŞİMŞİR [2]


It is well known that the efficiency of a channel estimator employing the strategy of comb-type pilot placement can be controlled by adjusting the positions of pilot tones. In this paper, by considering this situation, in order to maximize the estimation precision of the least squares (LS) algorithm utilized as a channel estimator in orthogonal frequency division multiplexing – interleave division multiple access (OFDM-IDMA) scheme, the genetic algorithm (GA) possessing a wide range of uses due to its powerful problem solving capability was utilized in the optimization of pilot positions. Besides, the computational load of mean square error (MSE) which is used as the objective function of GA was avoided by employing its upper bound during the optimization process. The upper bound of MSE was achieved by utilizing the Gershgorin disc theorem. In the simulations, the suggested pilot arrangement strategy based on the GA was compared to the conventional techniques like equispaced and random pilot placements in point of two criteria known as bit error rate (BER) and MSE. Simulation results put forth that GA-based pilot design strategy establishes a very clear superiority over the other considered methods by providing significant MSE and BER performances.
Tarak-tipi pilot yerleştirme stratejisi kullanan bir kanal kestiricisinin veriminin, pilot tonların pozisyonlarının ayarlanarak kontrol edilebileceği iyi bilinmektedir. Bu makalede, bu durum dikkate alınarak, dikgen frekans bölmeli çoğullama-serpiştirme bölmeli çoklu erişim (OFDM-IDMA) sisteminde kanal kestiricisi olarak kullanılan en küçük kareler (LS) algoritmasının kestirim hassasiyetini maksimuma çıkarmak amacıyla, güçlü problem çözme yeteneğinden dolayı geniş bir kullanım yelpazesine sahip olan genetik algoritma (GA), pilot tonların optimizasyonunda kullanılmıştır. Bunun yanı sıra, GA’nın amaç fonksiyonu olarak kullanılan ortalama karesel hatanın (MSE) hesaplama yükünden, optimizasyon işlemi boyunca ilgili fonksiyonun üst sınırı kullanılarak kaçınılmıştır. MSE’nin üst sınırı, Gershgorin disk teoreminden faydalanılarak elde edilmiştir. Simülasyonlarda, önerilen GA’ya dayalı pilot yerleştirme stratejisi, eşit aralıklı ve rastgele pilot yerleştirme gibi geleneksel yöntemler ile, bit hata oranı (BER) ve MSE olarak bilinen iki adet kriter bakımından karşılaştırılmıştır. Simülasyon sonuçları, GA tabanlı pilot dizayn stratejisinin, kayda değer bir MSE ve BER performansı sağlayarak, dikkate alınan diğer yöntemler üzerinde çok açık bir üstünlük kurduğunu ortaya koymuştur.
  • Bhatia, T., Kansal, S., Goel, S., & Verma, A. K. (2016). A genetic algorithm based distance-aware routing protocol for wireless sensor networks. Computers and Electrical Engineering, 56(2016), 441–455.
  • Coleri, S., Ergen, M., Puri, A., & Bahai, A. (2002). Channel estimation techniques based on pilot arrangement in OFDM systems. IEEE Transactions on Broadcasting, 48(3), 223–229.
  • Dang, J., Zhang, W., Yang, L., & Zhang, Z. (2013). OFDM-IDMA with user grouping. IEEE Transactions on Communications, 61(5), 1947–1955.
  • D'orazio, L., Sacchi, C., & Doneli, M. (2010, September 13–14). Adaptive channel estimation for STBC-OFDM systems based on nature-inspired optimization strategies [Conference presentation]. International Workshop on Multiple Access Communications (MACOM2010), Barcelona, Spain.
  • Goldberg, D. E. (1989). Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley.
  • Goldberg, D. E., & Deb, K. (1991). A comparative analysis of selection schemes used in genetic algorithms. In G. J. E., Rawlins (Ed), Foundations of Genetic Algorithms (pp. 69–93). Morgan-Kaufman.
  • Horn, R. A., & Johnson, C. R. (1985). Matrix Analysis. Cambridge University Press.
  • Hsieh, M. H., & Wei, C. H. (1998). Channel estimation for OFDM systems based on comb-type pilot arrangement in frequency selective fading channels. IEEE Transactions on Consumer Electronics, 44(1), 217–225.
  • Ölgün, M., & Tilki, U. (2020). Neural network based sliding mode controller with genetic algorithm for two link robot manipulator. European Journal of Science and Technology, (Special Issue), 120–129.
  • Özoğlu, B., Çakmak, E., & Koç, T. (2019). Clarke & Wright's savings algorithm and genetic algorithms based hybrid approach for flying sidekick traveling salesman problem. European Journal of Science and Technology, (Special Issue), 185–192.
  • Ping, L., Guo, Q., & Tong, J. (2007). The OFDM-IDMA approach to wireless communication system. IEEE Wireless Communications, 14(3), 18–24.
  • Ping, L., Liu, L., Wu, K. Y., & Leung, W. K. (2006). Interleave-division multiple-access. IEEE Transactions on Wireless Communications, 5(4), 938–947.
  • Seyman, M. N., & Taşpınar, N. (2011). Particle swarm optimization for pilot tones design in MIMO-OFDM systems. EURASIP Journal on Advances in Signal Processing, 2011(10), 1–11.
  • Seyman, M. N., & Taşpınar, N. (2012). Optimization of pilot tones using differential evolution algorithm in MIMO-OFDM systems. Turkish Journal of Electrical Engineering and Computer Sciences, 20(1), 15–23.
  • Seyman, M. N., & Taşpınar, N. (2013). Pilot tones optimization using artificial bee colony algorithm for MIMO-OFDM systems. Wireless Personal Communications, 71(1), 151–163.
  • Şimşir, Ş., & Taşpınar, N. (2015). Channel estimation using radial basis function neural network in OFDM-IDMA system. Wireless Personal Communications, 85(4), 1883–1893.
  • Şimşir, Ş., & Taşpınar, N. (2017). Pilot tones design using Grey Wolf Optimizer for OFDM-IDMA system. Physical Communication, 25(1), 259–267.
  • Şimşir, Ş., & Taşpınar, N. (2018). Advanced pilot design procedure based on HS algorithm for OFDM-IDMA system. IET Communications, 12(10), 1155–1162.
  • Taşpınar, N., & Şimşir, Ş. (2017). Channel estimation using an adaptive neuro fuzzy inference system in the OFDM-IDMA system. Turkish Journal of Electrical Engineering and Computer Sciences, 25(1), 352–364.
  • Taşpınar, N., & Şimşir, Ş. (2019). Pilot tones design using particle swarm optimization for OFDM–IDMA system. Neural Computing and Applications, 31(9), 5299–5308.
  • Vidhya, K., & Shankarkumar, K. R. (2013). Channel estimation and optimization for pilot design in MIMO OFDM systems. International Journal of Emerging Technology and Advanced Engineering, 3(2), 175–180.
Primary Language en
Subjects Engineering
Journal Section Articles
Authors

Orcid: 0000-0003-4689-4487
Author: Necmi TAŞPINAR
Institution: ERCİYES ÜNİVERSİTESİ
Country: Turkey


Orcid: 0000-0002-1287-160X
Author: Şakir ŞİMŞİR (Primary Author)
Institution: NEVŞEHİR HACI BEKTAŞ VELİ ÜNİVERSİTESİ
Country: Turkey


Supporting Institution Scientific and Technological Research Council of Turkey (TUBITAK)
Project Number 115E653
Thanks Scientific and Technological Research Council of Turkey (TUBITAK) funded this work [Grant No: 115E653].
Dates

Publication Date : August 31, 2020

APA Taşpınar, N , Şi̇mşi̇r, Ş . (2020). Bio-Inspired Pilot Design Approach based on Genetic Algorithm for OFDM-IDMA Scheme . Avrupa Bilim ve Teknoloji Dergisi , (19) , 466-474 . DOI: 10.31590/ejosat.732528