Flowchart for Clustered-Based Channel Allocation Management Scheme

Isaac A. Ezenugu, James Eke, G. N. Onoh

Abstract


In the GSM system, several Base Transceiver Station (BTS) are controlled by a single Base Station Controller (BSC). In this paper, the BTSs in a given BSC is referred to as a cluster.  In this paper, flowchart for clustered-based channel allocation management scheme is presented. The mechanism is meant to reduce call blocking/dropping to the barest minimum. Usually, traffic intensity value varies from one BTS to another, as it is directly proportional to the number of GSM users that make or receive calls within a particular period of time. In order to maintain a reliable GSM network that will provide minimum call blocking/dropping, the paper presents the flowchart for network resource management scheme that will adopt sharing of traffic loads among BTSs that belong to a particular network cluster. The scheme also considers the following; available channels, mobility factor, offered traffic, number of nearby BTSs, new call arrival rate, handoff call arrival rate and mean call duration. With limited available channels per BTS, instead of blocking a new call or dropping a handoff call whenever a particular BTS reaches its maximum allowable capacity, this newly proposed scheme however checks for a nearby BTS within that cluster that has free channels, and then performs a routine operation that will transfer some percentage of the traffic load to the free nearby BTS. This routine operation therefore allows the BTS to admit more calls.

Keywords


Call blocking; Call dropping; Mobility factor; New call arrival rate; Handoff call arrival rate; Call duration

Full Text:

PDF

References


Fang, Y. (2005). Performance Evaluation of Wireless Cellular Networks under More Realistic Assumptions: Wireless Communications and Mobile Computing Wirel. Commun. Mob. Comput.; 5:867–885 Published Online In Wiley Interscience (www.interscience.wiley.com). DOI: 10.1002/wcm.352.

Lindemann, C., Lohmann, M., & Thümmler, A. (2004). Adaptive call admission control for QoS/revenue optimization in CDMA cellular networks. Wireless Networks, 10(4), 457-472.

Khedher, H., Valois, F. & Tabbane, S. (2002). Traffic Characterization for Mobile Networks Proceedings IEEE 56th Vehicular Technology Conference, vol.3. 1485-1489.

Boggia, G., Camarda, P., D’Alconzo, A., De Biasi, A.&Siviero, M. (2005). Drop Call Probability in Established Cellular Networks: from Data Analysis to Modeling: DEE – Politecnico di Bari, Via E.Orabona, 4 – 70125 Bari (Italy), Proc. IEEE VTC Spring 2005, 5, 2775- 2779.

Tarkaa, N.S, Mom, J.M. & Ani, C.I. (2011). Drop Call Probability Factors in Cellular Networks. International Journal of Scientific & Engineering Research, 2(10), 1-5.

Dharmaraja, S., Trivedi, K. S., & Logothetis, D. (2003). Performance modeling of wireless networks with generally distributed handoff interarrival times. Computer Communications, 26(15), 1747-1755.

Liu, H., Xu, Y. & Zeng Q. (2005). Modeling and Performance Analysis of Future Generation Multimedia Wireless and Mobile Networks Using Smart Antennas. IEEE Wireless Communications and Networking Conference, Vol. 3, 1286-1291.

Xie, H., & Kuek, S. (1994). Priority handoff analysis. International Journal of Wireless Information Networks, 1(2), 141-148.

Samanta, R. K., Bhattacharjee, P., and Sanyal, G. (2009). Performance Analysis of Cellular Wireless Network by Queuing Priority Handoff calls. International Journal of Electrical and Electronics Engineering, 3(8), 472-477.

Giambene, G. (2005). Queuing Theory and Telecommunications Networks and Applications: Rome: Springer Science + Business Media, Inc., pp. 238-400.

Donaldson, A.E., Kalu, C., and Dialoke, I.C. (2016). Cluster-Based Call Acceptance Principle for Optimum Reduction of Call Failures in a GSM Network System, Mathematical and Software Engineering, Vol. 2, No. 2, 48-56. Varεpsilon Ltd, varepsilon.com.


Refbacks

  • There are currently no refbacks.