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Bat Optimization Algorithm for Preamble Separation and Allocation using Prioritization Method

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2020
T. Kanchana, K. Deepa

T Kanchana and K Deepa. Bat Optimization Algorithm for Preamble Separation and Allocation using Prioritization Method. International Journal of Computer Applications 177(34):34-41, January 2020. BibTeX

	author = {T. Kanchana and K. Deepa},
	title = {Bat Optimization Algorithm for Preamble Separation and Allocation using Prioritization Method},
	journal = {International Journal of Computer Applications},
	issue_date = {January 2020},
	volume = {177},
	number = {34},
	month = {Jan},
	year = {2020},
	issn = {0975-8887},
	pages = {34-41},
	numpages = {8},
	url = {},
	doi = {10.5120/ijca2020919822},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Cellular networks will play an important role in realizing the newly emerging. One of the challenging issues is to support the quality of service (QoS) during the access phase. The random access (RA) mechanism of Long Term Evolution (LTE) networks is prone to congestion when a large number of devices attempt RA simultaneously, due to the limited set of preambles. If each RA attempt is made by means of transmission of multiple consecutive preambles (Code words) picked from a subset of preambles by priority classes, collision probability can be significantly reduced. Selection of an optimal preamble set size can maximize RA success probability in the presence of a trade-off between codeword ambiguity and code collision probability, depending on load conditions. In recent work developed the Load-Adaptive Throughput-Maximizing Preamble Allocation (LATMAPA). LATMAPA automatically adjusts the preamble allocation to the priority classes according to the random access load and a priority tuning parameter. However the latest researches are unsuccessful in the assignment of regulating the parameters of load balancing and delay reducing algorithm and hence, to overcome this issue, a novel approach termed Improved Load-Adaptive Throughput-Maximizing Preamble Allocation (ILATMAPA) is been introduced in this research work. Bat optimization algorithm based parameter tuning is employed to improve the throughput and an analysis is carried out to quantify the throughput, delay and drop ratio trade-offs of parting the preambles into two disjoint sets. For under loaded systems, realise a “safe” allocating region, in which class I prioritization is comparatively harmless for class II. An experimental result reveals that the proposed method decreases the delay access and increases the throughput.


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Random Access, Collision Probability, Throughput-Maximizing, Preamble Allocation and Prioritization.