Neighbor Cell List Optimization based on Game Theory and Location Information for the Handover Process in Dense Fcns
Ahmed I. Mohamed1, Amr A. Al-Awamry2, Ashraf S. Mohra3

1Ahmed I. Mohamed, M.Sc. Student, ECE, Benha University, Benha, Egypt.
2Amr A. Al-Awamry. Assistant Professor, ECE, Benha University, Benha, Egypt.
3Ashraf S. Mohra, Professor, ECE, Benha University, Benha, Egypt.

Manuscript received on April 02, 2020. | Revised Manuscript received on April 15, 2020. | Manuscript published on May 30, 2020. | PP: 120-126 | Volume-9 Issue-1, May 2020. | Retrieval Number: A1273059120/2020©BEIESP | DOI: 10.35940/ijrte.A1273.059120
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Abstract: The integration of cellular networks allows mobile users to eliminate poor indoor coverage and call dropping probability. Femto stations (FS’s) appeared to be one of the innovative solutions that enhanced network coverage and the Quality of Service (QoS) when servicing indoor users. The cellular network Operator can potentially benefit by employing FS inside buildings and shares the allocated spectrum among different network entities. The seamless handover (HO) process between network entities is a major challenge of the Femto cellular networks (FCNs). Furthermore, the minimum and appropriate neighbor Femto list (NFL) is the main aim to guarantee the complete execution of the HO process. In this paper, an algorithm is proposed for power control in dense Femto Stations environment as long as possible through the Nash non-cooperative game theory. additionally, it provides location information mechanism to ensure a seamless transition between different network entities based on detected frequency from neighbor FS’s, signal to interference noise ratio (SINR), as well as the location information of FS in the coverage area. Simulation results show that the proposed algorithm reduces the HO failure probability through improving the NFL by deducting 40% of the amount of FSs in the NFL. As compared to the traditional scheme based on RSSI and frequency allocation, with increasing the number of FSs, there is around 40- 50% reduction in the probability that the target FS is not included in the NFL which improves the network performance and lowers HO failure probability. 
Keywords:  Femto Station, Handover, Neighbor Femto List (NFL), Signal to Interference Noise Ratio (SINR), Dense Femto Station.
Scope of the Article: Discrete Optimization.