Abstract
Cellular concept is major breakthrough in solving spectral congestion but it faces spectrum availability crisis due to increase in requirement of data rate. In order to satisfy the growing traffic demand and to optimize channel allocation, cognitive cellular network (CCN) is taken into consideration. CCN consists of primary (cellular) and secondary (cognitive) users where secondary users try to accommodate in primary band without causing interference to them. Artificial Bee Colony (ABC) and Teaching Learning Based Optimization (TLBO) algorithms are the population based optimization techniques, taken into account to analyze and improvise the network capacity. In this paper, these techniques are studied and used to find SINR in terms of data rate in Mbps with the help of fitness function. The obtained results of ABC and TLBO are compared with reported work of Particle Swarm Optimization (PSO). The proposed techniques are found to be better than PSO.
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Ohatkar, S., Gunjkar, Y. (2016). ABC and TLBO Technique for Evaluating Data Rate in Wireless Network. In: Unal, A., Nayak, M., Mishra, D.K., Singh, D., Joshi, A. (eds) Smart Trends in Information Technology and Computer Communications. SmartCom 2016. Communications in Computer and Information Science, vol 628. Springer, Singapore. https://doi.org/10.1007/978-981-10-3433-6_47
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DOI: https://doi.org/10.1007/978-981-10-3433-6_47
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