Abstract

The Partial Transmit Sequence which reduces the PAPR (Peak-to-Average Power Ratio) in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system using a novel optimization algorithm is proposed in this study. This novel optimization algorithm is based on a hybrid of Bacterial Foraging Optimization (BFO) and Modified Cuckoo Search algorithm (MCS) and is thus called HBFOMCS. In HBFOMCS, reproduction of individuals in a new generation is created, not only by swim and tumble operation as in BFO, but also by MCS. The natural reproduction step of BFO is swapped by the concept of searching best solutions as in MCS which then increases the possibility of generating the elite individuals for next generation. These enhanced reproduction step constitute the ready-to-perform population for the new generation once the initial population is performed by swim and tumble operation. Afterwards, discover probability is applied to abandon the worst solution due to the nature of MCS. HBFOMCS is applied to optimize the best combination from a set of allowed phase factors in Partial Transmit Sequence (PTS) technique. The performance of HBFOMCS is compared with BFO, Cuckoo Search (CS) and Modified cuckoo search MCS in the PAPR reduction in MIMO-OFDM system, accordingly proving its proficiency.

Keywords:

Bacterial foraging algorithm, hybrid algorithm, MIMO-OFDM, modified cuckoo search algorithm, PAPR reduction, partial transmit sequence,

References

1. Bäck, T. and H.P. Schwefel, 1993. An overview of evolutionary algorithms for parameter optimization. Evolut. Comput., 1(1): 1-23.
   CrossRef    
2. Cimini, L.J. and N.R. Sollenberger, 2000. Peak-to-average power ratio reduction of an OFDM signal using partial transmit sequences. IEEE Commun. Lett., 4(3): 86-88.
   CrossRef    
3. Fogel, D.B., 1995. Evolutionary Computation: Toward a New Philosophy of Machine Intelligence. IEEE Press, Piscataway, NJ, pp: 1-272.
   PMid:7711479    
4. Han, S.H. and J.H. Lee, 2004. PAPR reduction of OFDM signals using a reduced complexity PTS technique. IEEE Signal Proc. Let., 11(11): 887-890.
   CrossRef    
5. Ishibuchi, H., T. Yoshida and T. Murata, 2003. Balance between genetic algorithm and local search in memetic algorithms for multi objective epermutation flow shop scheduling. IEEE T. Evol. Comput., 7: 204-223.
   CrossRef    
6. Jaszkiewicz, A., 2001. Comparison of local search-based metaheuristics on the multiple objective knapsack problem. Found. Comput. Decis. Sci., 26: 99-120.
   
7. Jiang, T., W. Xiang, P.C. Richardson, J. Guo and G. Zhu, 2007. PAPR reduction of OFDM signals using partial transmit sequences with low computational complexity. IEEE T. Broadcast., 53(3): 719-724.
   CrossRef    
8. Jing, G., J. Wang and Z. Xie, 2009. Peak to average power ratio reduction for MIMO-OFDM systems with decomposed selected mapping. Int. J. Inform. Syst. Sci., 3(3-4): 572-580.
   
9. Jing, D., A. Brabazon, M. O'Neill and D. Edelman, 2008. Option Model Calibration Using a Bacterial Foraging Optimization Algorithm. In: Giacobini, M. et al. (Ed.), Evoworkshops. LNCS 4974, Springer-Verlag, Berlin, Heidelberg.
   
10. Jones, E., T.A. Wilkinson and S.K. Barton, 1994. Block coding scheme for reduction of peak to mean envelope power ratio of multicarrier transmission scheme. Electron. Lett., 30(25): 2098-2099.
    CrossRef    
11. Khan, Y.A., M.A. Matin and S.I. Ferdous, 2010. PAPR reduction in MIMO-OFDM systems using modified PTS and SLM without side information. Int. J. Commun. Networks Inform. Secur., 2(3).
    
12. Knowles, J.D. and D.W. Corne, 2000. M-PAES: A memetic algorithm for multiobjective optimization. Proceedings of Congress on Evolutionary Computation, pp: 325-332.
    CrossRef    
13. Krasnogor, N. and J. Smith, 2000. A memetic algorithm with self adaptive local search: TSP as a case study. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2000). Morgan Kaufmann, San Francisco, USA, pp: 987-994.
    
14. Lain, J.K., S.Y. Wu and P.H. Yang, 2011. PAPR reduction of OFDM signals using PTS: A real-valued genetic approach. EURASIP J. Wirel. Comm., 126, DOI: 10.1186/1687-1499-2011-126.
    CrossRef    
15. Merz, P. and B. Freisleben, 1997. Genetic local search for the TSP: New results. Proceeding of IEEE International Conference Evolutionary Computation. Indianapolis, pp: 159-164.
    CrossRef    
16. Mouhib, K.E., A. Oquour, Y. Jabrane, B.A.E. Said and A.A. Ouahman, 2011. PAPR reduction using BPSO/PTS and STBC in MIMO OFDM system. J. Comput. Sci., 7(4): 454-458.
    CrossRef    
17. Müller, S.H. and J.B. Huber, 1997a. OFDM with reduce peak-to-average power ratio by optimum combination of partial transmit sequences. Electron. Lett., 33(5): 368-369.
    CrossRef    
18. Müller, S.H. and J.B. Huber, 1997b. A novel peak power reduction scheme for OFDM. Proceeding of the 8th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC '97). Helsinki, pp: 1090-1094.
    CrossRef    
19. Sharma, P.K., C. Sharma, S.K. Tomar and A.K. Gupta, 2011. PAPR reduction in MIMO-OFDM system using new PTS. MIT Int. J. ECE, 1(2): 83-87.
    
20. Wen, J.H., S.H. Lee, Y.F. Hung and H.L. Hung, 2008. A suboptimal PTS algorithm based on particle swarm optimization technique for PAPR reduction in OFDM systems. EURASIP J. Wirel. Comm., 601346, DOI: 10.1155/ 2008/601346.
    
21. Whitley, D., V.S. Gordon and K. Mathias, 1994. Lamarckian evolution, the Baldwin effect and function optimization. Proceeding of International Conference Parallel Problem Solving from Nature, 866: 6-15.
    CrossRef    
22. Yajun, W., W. Chen and C. Tellambura, 2010. A PAPR reduction method based on artificial bee colony algorithm for OFDM signals. IEEE T. Wirel. Commun., 9(10): 2994-2999.
    CrossRef    
23. Yang, X.S. and S. Deb, 2009. Cuckoo search via Lévy flights. Proceedings of World Congress on Nature and Biologically Inspired Computing (NaBIC 2009). Coimbatore, pp: 210-214.
    CrossRef    
24. Yang, X.S. and S. Deb, 2010. Engineering optimisation by cuckoo search. Int. J. Math. Modell. Numer. Optimiz., 1: 330-343.
    CrossRef    
25. Yao, X., 1999. Evolutionary Computation: Theory and Applications. World Scientific, Singapore.
    CrossRef    
26. Zhang, Y., Q. Ni and H.H. Chen, 2009. A new partial transmit sequence scheme using genetic algorithm for peak-to-average power ratio reduction in a multi-carrier code division multiple access wireless system. Int. J. Auton. Adap. Commun. Syst., 2(1): 40-57.
    CrossRef    
27. Zhou, G.T. and L. Peng, 2005. Optimality condition for selected mapping in OFDM. IEEE T. Signal Proces., 54(8): 3159-3165.
    

Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.