Design of Space-Time Coded Multi-Carrier CDMA System based on Metaheuristic Optimization Algorithms

Design of Space-Time Coded Multi-Carrier CDMA System based on Metaheuristic Optimization Algorithms

  IJETT-book-cover           
  
© 2022 by IJETT Journal
Volume-70 Issue-10
Year of Publication : 2022
Authors : P. Sreesudha, B. L. Malleswari
DOI : 10.14445/22315381/IJETT-V70I10P208

How to Cite?

P. Sreesudha, B. L. Malleswari, "Design of Space-Time Coded Multi-Carrier CDMA System based on Metaheuristic Optimization Algorithms ," International Journal of Engineering Trends and Technology, vol. 70, no. 10, pp. 61-66, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I10P208

Abstract
Multiple Carrier Code Division Multiple Access (MC-CDMA) system performances are evaluated with the MMSE (Minimum Mean Square Error) equalization algorithm in this framework. The system's performance is augmented with the assistance of meta-heuristic optimization algorithms. Nature-inspired Krill Herd algorithm with an oppositional-based learning method (OKH) is used to improve performance. And the system was also implemented using Kinetic Gas Molecule Optimization (KGMO) algorithm. KGMO is also a metaheuristic-based process that operates with the concept of thermodynamics. Procuring wireless channel details is a difficult task in mobile wireless systems. Both algorithms help in obtaining channel information. Multiple inputs and multiple outputs (MIMO) are primary in existing and ensuing wireless communications. Space-time coding (STC) is integral to multi-antenna operations, mainly concerned with integrity. The proposed optimisation algorithms based on the multi-carrier CDMA system using space-time coding are implemented, and the BER parameter is evaluated. 2 transmitting and 1 receiving antennae are considered in the proposed system. Simulations are done in Rayleigh fading channel.

Keywords
CDMA, MC-CDMA, MIMO, OFDM, Optimization Algorithm.

Reference
[1] Nagaradjane, Prabagarane & Muthu, Tamilarasi, “Performance of Relay-Aided Multi-Carrier-CDMA using Preprocessing based on Quantized Feedback,” Computers & Electrical Engineering, vol. 48, pp.187-202, 2015.
[2] Hara S, Mouri M, Okada M, et al., “Transmission Performance Analysis of Multi-Carrier Modulation in Frequency Selective Fast Rayleigh Fading Channel,” Wireless Personal Communications, vol. 2, pp. 335–356, 1995.
[3] S. D. Blostein and H. Leib, “Multiple Antenna Systems: Their Role and Impact in Future Wireless Access,” in IEEE Communications Magazine, vol. 41, no. 7, pp. 94-101, 2003.
[4] S. M. Alamouti, “A Simple Transmit Diversity Technique for Wireless Communications,” in IEEE Journal on Selected Areas in Communications, vol. 16, no. 8, pp. 1451-1458, 1998.
[5] Yu, Jung-Lang & Lee, Ming-Feng & Lin, Chih-Chan, “Multi-User Receivers for MC-CDMA MIMO Systems with Space-Time Block Codes,” Signal Processing, vol. 89, no. 1, pp. 99-110, 2009.
[6] Nahar, Ali & Ghazali, Kamarul. “Local Search Particle Swarm Optimization Algorithm Channel Estimation Based on MC-CDMA System,” ARPN Journal of Engineering and Applied Sciences, vol. 10, no. 20, pp. 9659-9667, 2015.
[7] Md. Sofiqul Islam, Md. Firoz Ahmed, A. Z. M. Touhidul Islam, "Performance Analysis of V-Blast Encoded MIMO MC-CDMA Wireless Communication System in Encrypted Color Image Transmission," International Journal of Recent Engineering Science, vol. 7, no. 3, pp. 52-56, 2020. Crossref, https://doi.org/10.14445/23497157/IJRES-V7I3P111
[8] Kowalski P.A, Łukasik S, “Experimental Study of Selected Parameters of the Krill Herd Algorithm,” In: Angelov P. et al. eds., Intelligent Systems' 2014, Advances in Intelligent Systems and Computing, Springer, Cham, vol. 322, pp. 473-485, 2015.
[9] Bulbul, Sk&Pradhan, Moumita& Roy, Provas & Pal, Tandra, “Opposition-Based Krill Herd Algorithm Applied to Economic Load Dispatch Problem,” Ain Shams Engineering Journal, vol. 9, no. 3, pp. 423-440, 2018.
[10] Moein, Sara and Rajasvaran Logeswaran, “KGMO: A Swarm Optimization Algorithm Based on the Kinetic Energy of Gas Molecules,” Journal of Information Science, vol. 275, pp. 127–144, 2014.
[11] P. Sreesudha and B. L. Malleswari, “An Efficient Channel Estimation for BER Improvement of MC CDMA System using KGMO Algorithm,” 2017 International Conference on Communication and Signal Processing (ICCSP), pp. 1004-1009, 2017.
[12] N. Kumaratharan, E. E. Arnold, J. Venkatesan and P. Dananjayan, “Performance Improvement of ICE for Orthogonal STBC MCCDMA Systems over MIMO Channels,” 2008 IEEE Region 10 and the Third International Conference on Industrial and Information Systems, pp. 1-5, 2008.
[13] Marousis A.D, Skentos N.D & Constantinou P, “An Enhanced Embedded-Pilot Channel Estimation Architecture for MIMO MCCDMA Systems,” Wireless Personal Communications, vol. 59, pp. 713-739, 2011.
[14] S. Ashrafinia, M. Naeem and D. Lee, “A Low Complexity Evolutionary Algorithm for Multi-User MIMO Detection,” 2011 IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making (MDCM), pp. 8-13, 2011.
[15] A. Askarzadeh, L. dos Santos Coelho, C. E. Klein and V. C. Mariani, “A Population-Based Simulated Annealing Algorithm for Global Optimization,” 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 004626-004633, 2016.
[16] R. Tang, X. Zhou and C. Wang, “Kalman Filter Channel Estimation in 2 × 2 and 4 × 4 STBC MIMO-OFDM Systems,” in IEEE Access, vol. 8, pp. 189089-189105, 2020.
[17] M. S. Arifianto, A. Chekima, L. Barukang and M. Y. Hamid, “Binary Genetic Algorithm Assisted Multiuser Detector for STBC MCCDMA,” 2007 IFIP International Conference on Wireless and Optical Communications Networks, pp. 1-5, 2007.
[18] L. D'Orazio, C. Sacchi, M. Donelli and F. G. B. De Natale, “MMSE Multi-User Detection with GA-Assisted Channel Estimation for STBC MC-CDMA Mobile Communication Systems,” 2008 IEEE 10th International Symposium on Spread Spectrum Techniques and Applications, pp. 182-187, 2008.
[19] Amarendra Alluri, "Enhancement of Power System Security using Meta-heuristic Optimization Techniques," SSRG International Journal of Electrical and Electronics Engineering, vol. 4, no. 2, pp. 7-11, 2017. Crossref, https://doi.org/10.14445/23488379/IJEEEV4I2P102
[20] K. F. Man, K. S. Tang and S. Kwong, “Genetic Algorithms: Concepts and Applications in Engineering Design,” in IEEE Transactions on Industrial Electronics, vol. 43, no. 5, pp. 519-534, 1996.
[21] D'Orazio, L., Sacchi, C., Donelli, M. et al., “A Near-Optimum Multiuser Receiver for STBC MC-CDMA Systems Based on Minimum Conditional BER Criterion and Genetic Algorithm-Assisted Channel Estimation,” Journal on Wireless Communications and Networking, vol. 2011, pp. 351494, 2011.
[22] The 3GPP Portal Website. [Online]. Available: https://www.3gpp.org/ftp/Specs/archive/25_series/25.943/
[23] Salma S. Shahapur, Dr. Rajashri Khanai, Dr. D.A. Torse, "Channel Coding in Underwater Communication Using Turbo Code," SSRG International Journal of Electronics and Communication Engineering, vol. 6, no. 6, pp. 19-22, 2019. Crossref, https://doi.org/10.14445/23488549/IJECE-V6I6P105
[24] J. Yang, Y. Sun, J. M. Senior and N. Pem, “Channel Estimation for Wireless Communications using Space-Time Block Coding Techniques,” in Proceedings of the 2003 International Symposium on Circuits and Systems, 2003, ISCAS '03., pp. 2-2, 2003.
[25] Gandomi, Amir & Alavi, Amir., “Krill Herd: A New Bio-Inspired Optimization Algorithm,” Communications in Nonlinear Science and Numerical Simulation, vol. 17, no. 12, pp. 4831–4845, 2012.