Abstract: The ongoing call or data session must be maintained to ensure a good quality of service. This can be accomplished by performing handover procedure while the user is on the move. However, dense deployment of small cells in 5G networks is a challenging issue due to the extensive number of handovers. In this paper, a neighbour cell list method is proposed to reduce the number of target small cells and hence minimizing the number of handovers. The neighbour cell list is built by omitting cells that could cause an unnecessary handover and/or handover failure because of short time of stay of a user in these cells. A multi-attribute decision making technique, simple additive weighting, is then applied to the optimized neighbour cell list. The performance of the proposed method is analysed and compared with that of the existing methods. Results disclose that our method decreases the candidate small cell list, unnecessary handovers, handover failure and short time of stay cells compared to the competitive method.
Abstract: In this paper, a non-cooperative game method is
formulated where all players compete to transmit at higher
power. Every base station represents a player in the game.
The game is solved by obtaining the Nash equilibrium (NE)
where the game converges to optimality. The proposed method,
named Power Efficient Handover Game Theoretic (PEHO-GT)
approach, aims to control the handover in dense small cell
networks. Players optimize their payoff by adjusting the
transmission power to improve the performance in terms of
throughput, handover, power consumption and load balancing.
To select the desired transmission power for a player, the payoff
function considers the gain of increasing the transmission power.
Then, the cell selection takes place by deploying Technique for
Order Preference by Similarity to an Ideal Solution (TOPSIS).
A game theoretical method is implemented for heterogeneous
networks to validate the improvement obtained. Results reveal
that the proposed method gives a throughput improvement while
reducing the power consumption and minimizing the frequent
handover.
Abstract: The dense deployment of small cells is a promising
solution to enhance the coverage and capacity of the
heterogeneous networks (HetNets). However, the unplanned
deployment could bring new challenges to the network ranging
from interference, unnecessary handovers and handover failures.
This will cause a degradation in the quality of service (QoS)
delivered to the end user. In this paper, we propose an integrated
Grey Rational Analysis Standard Deviation based handover
method (GRA-SD) for HetNet. The proposed method integrates
the Standard Deviation (SD) technique to acquire the weight of
the handover metrics and the GRA method to select the best
handover base station. The performance of the GRA-SD method
is evaluated and compared with the traditional Multiple Attribute
Decision Making (MADM) methods including Simple Additive
Weighting (SAW) and VIKOR methods. Results reveal that the
proposed method has outperformed the other methods in terms of
minimizing the number of frequent unnecessary handovers and
handover failures, in addition to improving the energy efficiency.