BUSY HOUR TRAFFIC CONGESTION ANALYSIS IN MOBILE MACROCELLS

A Ozovehe; OU Okereke; EC Anene; AU Usman

doi:10.4314/njt.364.1501

BUSY HOUR TRAFFIC CONGESTION ANALYSIS IN MOBILE MACROCELLS

Authors

A Ozovehe TRIFIELD TECHNOLOGY LIMITED, 14 ISHAQ MAAJI CRESCENT, GWAGWALADA ABUJA, NIGERIA
OU Okereke DEPT. OF ELECTRICAL & ELECTRONICS ENGR., ABUBAKAR TAFAWA BALEWA UNIV. BAUCHI, BAUCHI STATE, NIGERIA
EC Anene DEPT. OF ELECTRICAL & ELECTRONICS ENGR., ABUBAKAR TAFAWA BALEWA UNIV. BAUCHI, BAUCHI STATE, NIGERIA
AU Usman DEPT. OF ELECTRICAL & ELECTRONICS ENGR, FEDERAL UNIVERSITY OF TECHNOLOGY, MINNA, NIGER STATE, NIGERIA

DOI:

https://doi.org/10.4314/njt.364.1501

Keywords:

traffic congestion, correlation coefficient, macrocells and key performance indicator

Abstract

Traffic congestion during busy hour (BH) deteriorates the overall performance of cellular network and may become unmanageable unless effective and efficient methods of congestion control are developed through real live traffic data measurement and analysis. In this work, real live traffic data from integrated GSM/GPRS network was used for traffic congestion analysis. The analysis was carried out on 10 congesting cells using network management system (NMS) statistics data span for three years period. Correlation test showed that traffic channel (TCH) congestion depend only on call setup success rate (CSSR) and BH traffic at cell level. An average correlation coefficient value of 0.9 was observed between TCH congestion and CSSR while 0.6 was observed between TCH congestion and BH traffic. The correlation test is important when selecting input for congestion prediction modeling.

http://dx.doi.org/10.4314/njt.v36i4.37

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Published

2017-09-29

Issue

Vol. 36 No. 4 (2017)

Section

Computer, Telecommunications, Software, Electrical & Electronics Engineering

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How to Cite

BUSY HOUR TRAFFIC CONGESTION ANALYSIS IN MOBILE MACROCELLS. (2017). Nigerian Journal of Technology, 36(4), 1265-1270. https://doi.org/10.4314/njt.364.1501