# INTRODUCTION ecent time, the world has witnessed different standards of mobile communication network, ranging from second generation (2G) to third generation (3G) standards. What gave room to this change is human quest to have better coverage quality, Grade of Service (GOS) and capacity (Gunner, 1998). Despite all these evolution from one stage to another, mobile communication subscribers, still have some difficulties when making calls or initiating calls during some particular period of time. For us to determine the performance of the mobile communication, the grade of service must be determined, firstly the peak busy hour must also be determine, the peak busy hour it is the given period within a day that bears the highest traffic intensity. The 'peak busy hour' traffic is use to determine the equipment quantities of the network. The reason to use busy hour traffic is that this period usually has the highest amount of blocked or lost calls. If the dimensioning of equipment at this period is correct and blocked calls can be minimized, all other non-busy hour traffic should then be handled satisfactorily (Sanjay;2010). The operation and maintenance centre (OMC), the OMC-counter is in-built inside the mobile communication system. These OMC-counter is used to measure the traffic variation on the traffic interfaces. The operation and maintenance centre is subdivided into three. They are; ? Fault management ? Configuration management ? Performance management The performance management unit is responsible for monitoring the performance of all the event (activities). Example are, calls intensity, time duration per call and time duration per hour. Etc. the traffic activities is being handled by sub-section known as (PMR) performance management traffic recording unit (John;. # II. EXPERIMENTAL PROCEDURE To determine the peak busy hour of traffic saturation in mobile communication network in Nigeria, we can measure traffic by three different methods, they are; ? Driving test ? Protocol analyzer ? OMC-counter (Operational and Maintenance Centre-Counter) (Gunner, 1998). In this experiment we deployed the use of the OMC-counter for measurement, which is in-built in mobile communication network, measurement have shown, that traffic is characterized by two major components they are; ? # DATA PRESENTATION The data obtained from operation and maintenance centre was presented in the following table below: # RESULT ANALYSIS The graphics below shows different peak busy hour of call intensity for various routes and six areas in Lagos State from a leading Mobile Communication Network in Nigeria. Data obtained was simulated by Excel package to obtain a resultant graphics. The highest call intensity was also determined for days of the week. From table 1.2 the resultant output shows that Monday has the highest call intensity, followed by Friday, Tuesday, Wednesday, Thursday, Saturday and Sunday. Shown in figure 2.7. For easy comparison the bar chart was used for different days of the week. V. # DISCUSSION The data obtained are represented in graphys for easy interpretation for various routes in fig. 2 # CONCLUSION From this thesis, the data was obtained from operation and maintenance centre (OMC-Counter). The data obtained was analyzed by Excel package. It was observed that there are two active busy hour, they are 10:00 hr and 19:00 hr. graphical representation of all the routes was shown in fig. 2 The call intensity for various days of the week was examined. Monday with the highest call intensity 27,567, followed by Friday, Tuesday, Wednesday, Thursday, Saturday and Sunday, shown in figure 2.7. # Calls Intensity Series1 ![Stochastic component ? Random generation of calls by subscribers (man) ? Deterministic component (machine) ? Structure (hardware) ? Operational strategy (software) (ITU-D, 2006). Data was obtained from the above mentioned technique for a duration of one-year from the experiment, it was show that traffic has two types of variation associated with the stochastic component. They are; 1. Number of calls variation 2. Services times variation This variation are the parameters used to determine the peak busy hour (Moltchanor, 2005). III.](image-2.png "") 1S/NO AREAROUTEPEAK BUSYATTEMPTIDHOURCALLS1.MUSHINBSC 0-1019:001092BSC 1-1019:00818BSC 2-1019:0015112.IKOTUNBSC 0-1020:00858BSC 1-1019:001218BSC 2-1019:0019153.EJIGBOBSC 0-1020:00672BSC 1-1019:001083BSC 2-1019:008384.APAPABSC 0-1019:00806BSC 1-1015:001345BSC 2-1011:006665.ALABABSC 0-1020:00247BSC 1-1019:001071BSC 2-1019:0013376.OYINGBO BSC 0-1019:001185BSC 1-1019:00847BSC 2-1019:00722The above table have, different areas such areMushin, Apapa, Alaba, Oyingbo, Ejigbo and Ikotun wasconsider in this research work due to their populationintensity in Lagos.Each area have a routes incorporated into 3Base Station Controller (BSC). While 3 routes wereconsider under one base station controller (IBSC). Theattempts calls for 24 hours, in each route are alsorecorded. 1S/No Call Intensity Days of the Week1.Sunday12,1192.Monday26,4923.Tuesday19,0804.Wednesday17,8925.Thursday16,4676.Friday23,1387.Saturday15,491IV. VI. Determination of Busy Hour in Mobile Communication in Nigeria©2011 Global Journals Inc. (US) Determination of Busy Hour in Mobile Communication in Nigeria©2011 Global Journals Inc. (US) * Introduction to 3G Mobile Communication, 2 nd edition Artech House KJuha 2003 Boston, London * Pocket Guild to the world of E1' wavetek wandel Goltermann Eurotech House pp TJohn 2005 * Computer networks SSanjay S.K. Kataria & Sons 2010 1 st edition * Wireless communications principles and practice, 2 nd Edition STRappaport 2003 Prentice, Hall of India Private Limited New Delhi * GSM Network" 1 st Edition Artech House Boston HGunner 1998 * Teletraffic Engineering Itu-D 2006 * Traffic modeling DMoltchanov Traffic Analysis for GSM Network 2005