ANALYSIS AND OPTIMISATION OF INTER CELL HANDOVER DYNAMICS IN A GSM NETWORK
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ANALYSIS AND OPTIMISATION OF INTER CELL HANDOVER DYNAMICS IN A GSM NETWORK
The Global System for Mobile Communications (GSM) is a digital wireless network standard developed by standardisation committees of major European telecoms operators and manufacturers. Cells are the building units of the GSM.
A cell is a geographical area covered by a base transceiver station (BTS). GSM is defined by mobility and limited resources. Cells allow mobile users to be served. User movement during a call can cause a change in cell (Base transceiver station).
Mobility leads to handovers. Handover is the transfer of an ongoing call to another cell (Busra et al, 2010). GSM enables automatic hard handovers.
1.2 Handover Process
Handover is an important process in every cellular system. Improper execution of this important phase may lead to call loss. Dropped calls can be frustrating for users, leading to discontent and a desire to switch networks. GSM handover was a key focus in designing the GSM ETS standards (Ghaderi, 2006).
A mobile cellular telecommunications system is divided into smaller cells for optimal spectrum utilisation and coverage.
Mobile devices are supposed to maintain their connection even when moving across cell areas.
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Adegoke (2008) explains that the handover mechanism in cellular networks seamlessly transfers calls from one radio channel to another while maintaining high quality of service (QoS) levels.
To fulfil rising capacity demands, smaller cells are deployed, leading to a rise in cell borders. Handover takes network resources to route calls to the next base station (Jahangir, 2010).
Efficient handover algorithms improve the capacity and QoS of communication systems (Pollini, 1996). According to Corazza et al. (1994), the handover procedure consists of two phases:
the initiation phase, which involves making the decision to handover, and the execution phase, which involves assigning a new channel to the mobile station or terminating the connection. Handover algorithms typically handle the first phase.
Handover aims to maximise quality of service (QoS) and capacity through reliability and communication, while also maintaining cell borders and traffic balancing.
iii. Reduce the number of handovers and global interference.
These are the desirable characteristics of an effective handover algorithm. Handover can be complicated due to cell dynamics, including topography, propagation, traffic, mobility, latency, and system constraints.
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1.3 Motivation.
The motivation for this thesis is to enhance mobility management and optimise GSM channel utilisation. As Nigeria’s mobile network customer base grows, GSM service providers must expand their capacity.
This is mostly accomplished by expanding coverage regions and channel resources to align. Inefficient intercell handovers can lead to poor quality of service and call dropping, posing mobility management challenges. Dropped clls have a direct impact on customers and are a critical quality of service indicator for regulatory agencies to evaluate.
Improper handover can overwhelm the system processor, resulting in frequent breakdowns, revenue loss, and reduced service quality.
Evaluating cell performance can demonstrate how intercell handover affects service quality.
A dynamic algorithm will be used to adjust cutoff priority channels based on handover failure rates, allowing for efficient resource and mobility management.
1.4 Statement of the Research Problem
Handover in wireless cellular systems is crucial for managing mobility and allocating resources. The handover procedure is anticipated to be effective, seamless, and less frequent. Unsuccessful handovers can be highly frustrating for subscribers.
Forcefully terminating established connections might result in dropped calls and poor service quality (26). High intercell handover requests in highly populated places, such as Kano, can lead to more traffic, lower QoS, longer call setup times, and higher call drop and blocking rates. Inefficient channel allocation systems might result in frequent intercell handovers.
The study examines cell performance, focusing on the effects of blocking, predicted call dropping, handover failure rates, and traffic channel call drop. The performance evaluation will use the Nigerian Communication Commission’s suggested quality of service standards as a benchmark.
Real GSM cell call data statistics from an Airtel OMC in Kano are gathered and processed. Handover calls are optimised using a simulated cutoff priority-based performance model.
1.5 Research Methodology
The methods used in doing this work includes the following:
This study uses data from Airtel Network’s Network Operation Maintenance Centre (OMC) in Kano to analyse traffic, call success rates, handover success rates, SDCCH and TCH call drops, congestion, SDCCH and TCH call blocking, TCH availability, cell ID, time, and cell availability.
b. Analyse and extract relevant parameters from raw data in (a). c. Compute and present arithmetic averages of extracted values using MATLAB plot.
The retrieved parameters include call setup and handover success rates, traffic channel call drop rates, blocking likelihood, and standalone dedicated control channel drop rates.
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