Ateş böceği algoritması kullanarak MC-CDMA sistemlerinde çevrimsel ön takı uzunluğunun belirlenmesi

Öz

Çok taşıyıcılı kod bölmeli çoklu erişim gibi yüksek hızlarda veri iletimini sağlayan çok taşıyıcılı haberleşme sistemlerinde semboller arası girişim ve kanallar arası girişimi önlemek için çevrimsel ön takıdan faydalanılır. Bu yüzden çevrimsel ön takı uzunluğunun uygun bir şekilde belirlenmesi, sadece hata performansını artırmayacak aynı zamanda da sembol enerjisindeki azaltmaları da engelleyecektir. Bu çalışmada çevrimsel ön takı uzunluklarının belirlenmesi için yeni bir meta-sezgisel algoritma olan ateş böceği algoritması önerilmiştir. Önerilen bu algoritmayı kullanarak, Genetik Algoritmalar ve 1/8 oranlı çevrimsel ön takı kod uzunluklu sistemlere göre daha iyi bit hata oranları elde edilmiştir. Parametre sayısının az ve performansının Genetik Algoritmalara göre yüksek olması nedeniyle bu algoritma çok taşıyıcılı kod bölmeli çoklu erişim sistemlerinde çevrimsel ön takı boyutlarının adaptif olarak belirlenmesinde kullanılabilir.

Anahtar Kelimeler

• MC-CDMA,Çevrimsel ön takı,Ateş böceği algoritması,Genetik algoritmalar

Determination of the cyclic prefix length in MC-CDMA using firefly algorithm

Öz

Cyclic prefix is utilized to prevent inter symbol interference and inter carrier interference in multi carrier communication systems such as multi-carrier code division multiple access that provides high speed data transmission. Therefore determination of the cyclic prefix length properly, not only increases the error performance but also prevents the reduction in symbol energy. In this work, the fire fly algorithm which is a new meta-heuristic algorithm, is proposed to determine the CP length. By using the proposed algorithm, the better bit error rate in comparison with Genetic Algorithms and 1/8 rate cyclic prefix systems was obtained. Due to the less parameters and high performance of this algorithm over Genetic Algorithms, it can be used in multi carrier code division multiplexing systems to determine the cyclic prefix length adaptively.

Anahtar Kelimeler

• MC-CDMA,Cyclic prefix,Fire fly algorithm,Genetic algorithms

Kaynakça

1. Fazel K, Kaiser S. Multi-Carrier and Spread Spectrum Systems: From OFDM and MC-CDMA to LTE and WiMAX 2nd ed. New York, USA, Wiley, 2008.
2. Li B, Zheng W, Ren S, Wu J. “Optimal selection of cyclic-prefix and subcarrier for OFDM signal in mobile satellite communications channel”. 2nd International Conference on Computer and Information Application (ICCCIA 2012), Taiyun, China, 8-9 December 2012.
3. Tonello AM, D'Alessandro S, Lampe L. “Cyclic prefix design and allocation in bit-loaded OFDM over power line communication channels”. IEEE Transactions on Communications, 58(11), 3265-3276, 2010.
4. Wolkerstorfer M, Tsiafkis P, Moonen M, Statovci D. “Joint power-loading and cyclic prefix length optimization for OFDM-Based power line communication”. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Vancouver, Canada, 26-31 May 2013.
5. Bhattacharyya1 B, Misra IS, Sanya SK. “Novel cyclic prefix selection to ımprove spectral efficiency and signal strength in OFDM systems”. International Journal on Recent Trends in Engineering and Technology, 8(2), 20-25, 2013.
6. Ghosh S, Misra IS, Sanyal SK. “Article: Study of the effect of cyclic prefix on different QoS parameters in wimax network”. International Conference on Communication, Circuits and Systems Bhubanswar, India, 1-3 June 2013.
7. Osman WE, Rahman TA. “Optimization of guard time length for mobile WiMAX system over multipath channel”. International Multi Conference of Engineers and Computer Scientists 2008, Hong Kong, 19-21 March 2008.
8. Chang YP, Lemmens P, Tu PM, Huang CC, Chen PY. “Cyclic prefix optimization for OFDM transmission over fading propagation with bit-rate and BER constraints”. 2nd International Conference on Innovations in Bio-inspired Computing and Applications, Shenzhan, China, 16-18 December 2011.

9. Bakir M, Belhachat M, Liu JG, Zhu SZ. “Optimization of guard interval for OFDM performance over fading and AWGN channels using genetic algorithm”. 6th CAS Symposium on Emerging Technologies: Mobile and Wireless Communication, Shanghai, China, 31 May-02 June, 2004.
10. Yang XS. “Firefly Algorithms For Multimodal Optimization”. Stochastic Algorithms: Foundations And Applications”. SAGA, Lecture Notes in Computer Sciences 5792, Berlin, Heidelberg, Germany, 2009.
11. Fister I, Fister I.Jr, Yang XS, Brest J. “A comprehensive review of firefly algorithms”. Swarm and Evolutionary Computation, 13, 34-46, 2013.
12. Apostolopoulos T, Vlachos A. “Application of the firefly algorithm for solving the economic emissions load dispatch problem”. International Journal of Combinatorics, 2011, 1-23, 2011.
13. Horng M. and Jiang T. “Multilevel ımage thresholding selection based on the firefly algorithm”. 7th International Conference on Autonomic & Trusted Computing on Ubiquitous Intelligence and Computing (UIC/ATC), Xi’an, China, 26-29 October 2010.
14. Sahoo A., Chandra S. “L'evy-Flight firefly algorithm based active contour model for medical ımage segmentation”. 6th International Conference on Contemporary Computing, Noida, India, 8-9 August 2013.
15. Basu B, MahantiGK. “Firefly and Artificial Bees Colony Algorithm for Synthesis of Scanned and Broadside Linear Array Antenna”. Progress in Electromagnetic Research B, 32,169-190, 2011.
16. Chatterjee A, Mahanti GK, Chatterjee A. “Design of a fully digital controlled reconfigurable switched beam conconcentric ring array antenna using firefly and particle swarm optimisation algorithm”. Progress in Elelectromagnetic Research B, 36, 113-131, 2012.
17. Horng MH. “Vector quantization using the firefly algorithm for ımage compression”. Expert Systems with Applications, 39, 1078-1091, 2012.
18. Failli M., "Digital Land Mobile Radio Communications COST 207, Final Report, Rome, Italy, 1988.
19. Beasley D, Bull DR, Martin RR. “An overview of genetic algorithms”. Part 1, Fundamentals. University Computing, 15(2), 58-69, 1993.