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Generation of Spreading Codes with Minimum Correlation using Sorting Genetic Algorithm-II
Shibashis Pradhan1, Deepak Kumar Barik2, M Vamshi Krishna3, Sujatarani Raut4

1Shibashis Pradhan*, Department of Electronics and Communication Engineering, Centurion University of Technology and Management, Bhubaneswar, India.
2Deepak Kumar Barik, Department of Electronics and Communication Engineering, Centurion University of Technology and Management, Bhubaneswar, India.
3M Vamshi Krishna, Department of Electronics and Communication Engineering, Centurion University of Technology and Management, Parlakhemundi, India.
4Sujatarani Raut, Department of Electronics,P.N Autonomous College, Khurda, India.

Manuscript received on October 14, 2019. | Revised Manuscript received on 27 October, 2019. | Manuscript published on November 10, 2019. | PP: 1744-1749 | Volume-9 Issue-1, November 2019. | Retrieval Number: I7758078919/2019©BEIESP | DOI: 10.35940/ijitee.I7758.119119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In a code division multiple access (CDMA) system, multiple access interference (MAI) and Inter-symbol interference (ISI) appears if generated spreading codes are not maintained orthogonally and the communication channel is taken as multi-path communication channel. When generated spreading codes are multi-path spread and then channel delay occurs, it shows that ortho-gonality of the spreading codes is not maintained. The effect of MAI can be mitigated by maintaining low cross-correlation values as much as low between the large numbers of spreading codes. The code division multiple technique spreading codes must maintain absolutely impulsive autocorrelation at origin and very low cross correlation other than origin to avoid false synchronisation. i.e autocorrelation must be maximum at origin and cross correlation must be minimum at non origin point. In this paper, we propose multi-objective Genetic Algorithm approach –Genetic Algorithm-II (NSGA-II) to reduce the out-of-phase average mean-square aperiodic autocorrelation and average mean-square aperiodic cross-correlation value of randomly initialized binary spreading code set.
Keywords: Inter Symbol Interference (ISI), Multiple Access Interference (MAI), Code Division Multiple Access (CDMA), Non-dominated Sorting Genetic Algorithm-II (NSGA-II)
Scope of the Article: Algorithm Engineering