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Design of Ternary Codes for Various Lengths using MSAA

International Journal of Computer Applications
© 2015 by IJCA Journal
Volume 116 - Number 6
Year of Publication: 2015
Mohammed Khaleel Anwar
Mohammed Al-gawagzeh
Syed Mujeebuddin

Mohammed Khaleel Anwar, Mohammed Al-gawagzeh and Syed Mujeebuddin. Article: Design of Ternary Codes for Various Lengths using MSAA. International Journal of Computer Applications 116(6):20-26, April 2015. Full text available. BibTeX

	author = {Mohammed Khaleel Anwar and Mohammed Al-gawagzeh and Syed Mujeebuddin},
	title = {Article: Design of Ternary Codes for Various Lengths using MSAA},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {116},
	number = {6},
	pages = {20-26},
	month = {April},
	note = {Full text available}


Pulse Compression Sequence is wide utilized inthe field of radar, communication to extend the range resolution. Sequences with good discriminating and merit factor are useful for channel estimation, radar and spread spectrum communication application. Binary sequence has the limitation that the compression ratio is small. Ternary alphabets are suggested as an alternative. The design of ternary codes with good merit factor and discriminating factor can be considered as a nonlinear multivariable mathematical problem which is difficult find a optimal solution. To get the solution for the this problem many global optimization algorithms like Simulated Annealing Algorithm(SA), Genetic Algorithm (GA), Tunneling algorithm (TA) and particle swarm optimization algorithm (PSO) could be used. Further a set of pulse compression sequence are required for spread spectrum and CDMA application such that the individual autocorrelation function of each sequence is like an impulse and the cross correlation between any two sequences in the set must be zero for all lags unfortunately. In this paper, it is proposed to use a new method of algorithm for the design of best ternary codes sets for various lengths by using Modified Simulated Annealing Algorithm. The general features such as global convergence and robustness of the statistical algorithm are revealed.


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