No Detail Found!

Optimizing Satellite Handover Rate using Particle Swarm Optimization (PSO) Algorithm.

Author(s)
Tahir Rehman Department of Telecommunication Engineering, Balochistan University of Information Technology Engineering, Management Sciences Quetta,
Faizullah Khan Department of Telecommunication Engineering, Balochistan University of Information Technology Engineering, Management Sciences Quetta,
Surat Khan Department of Telecommunication Engineering, Balochistan University of Information Technology Engineering, Management Sciences Quetta,
Amjad Ali Department of Electrical Engineering, Sarhad University of Engineering and Information Technology Peshawar, Management Sciences Quetta,
Abstract
Low earth orbital satellites are able to provide access to worldwide wireless or regional mobile services. The Low Earth Orbit (LEO) satellite arrangement generally has a cellular type of contact, similar to the cellular telephone structure. Neighboring satellites are linked with each other through Inter Satellite Links (ISLs). The user device interconnects with the satellite through a user mobile link (UML) while Gateway Link (GWL) is used to link a satellite with an earth station. The consumer's call duration may exceed than the service duration of a satellite necessitating hand over of the call to another detectible satellite to avoid disruption of the call. At the time of handover a user may be covered by more than single satellite. Either the mobile stations at earth or the serving satellite must be intelligent enough to handover the call to a satellite having longest coverage time. In this paper, we suggest an algorithm which decreases the predictable hand over rate by selecting a satellite with the largest service time. Using the Particle Swarm Optimization (PSO) algorithm, the serving satellite itself calculates the service time of neighboring satellites and optimally handover the call to a satellite with a maximum coverage time. Simulations are performed using MATLAB and various results are obtained for two prominent LEO satellite constellations, IRIDIUM and GLOBALSTAR. The effects of the satellite parameters (elevation angle, height, angular velocity and trace angle) on service time are calculated mathematically by drawing different scenarios.
Publication Details
Page(s) 53-63
DOI DOI not available
Published Journal: Journal of Applied and Emerging Sciences , Volume: 7, Issue: 1, Year: 2017

Request the full text from PASTIC

References
Ÿ BaiQ., 2010.Analysis of Particle Swarm Optimization Algorithm,Computer and Information Science 3 180 -184
Ÿ ChiniP,Kota., 2012.Development status and comparative analysis of satellite mobile communication system,Satell. Netw. IEEE 5 38 -46
Ÿ Fenglin., 2015.A simple real-time handover management in the mobile satellite communication networks 175 - 179, -
Ÿ ForouzanBA.,McGraw-Hill Higher Education, 2013.Data Communications and Networking, -
Ÿ LeeWN,ParkJB, 2007.Development of an Educational Simulator for Particle Swarm Optimization and Economic Dispatch Applications,International Conference on Intelligent Systems Applications to Power Systems. -
Ÿ LiSF, 2011.Overlap area assisted guaranteed handover scheme for HAP communication system,Communication 131 -137
Ÿ LiaoM, 2015.Analysis of maximum traffic intensity under pre-set quality of service requirements in low earth orbit mobile satellite system for fix channel reservation,IET Communication 9 1575 -1582
Ÿ LinY,HeS,ZhengJ, 2010.,The Suggestionto ISL Technology Development of Global Navigation Satellites. Spacecraft Engineering 19 1 -7
Ÿ LiuY,WangB., 2015.An Improved Satellites Routing Handover Strategy, 290 -292
2012.Personal satellite communication: Technologies and challenges,IEEE Wireless Communications. -
Ÿ SeyediY,RahimiF., 2012.A trace-time framework for prediction of elevation angle over land mobile LEO satellites networks, 62 793 -804
Ÿ Shkelzen, 2014.The Coverage Analysis for Low Earth Orbiting Satellites at Low Elevation,IJACSA 5 -
Ÿ StallingsW., 2003.Wireless Communications and Networks, -
Vijayalakshmi S et al. (2014). Particle swarm optimization with aging leader and challenges for multi-swarm optimization Technology (IJARCET).Volume 3 Issue 3, March 2014.
0

Citations

0

Downloads

31

Views