GRA-based Handover for Dense Small Cells Heterogeneous Networks

Ultra-dense small cell (SC) deployment in the future 5G network makes the architecture of the network as heterogeneous networks (HetNets). This is a good solution to boost the capacity of the network and extend its coverage. However, the dense SCs deployment has brought new challenges to the network including interference, frequent unnecessary handovers, and handover failures. Therefore, user equipment will suffer from a degraded quality of service. In this paper, the authors propose a grey rational analysis-based handover (GRA-HO) method in dense SCs HetNet. The proposed method combines the analytical hierarchy process technique to obtain the weight of the handover metrics and the GRA method to rank the available cells for the best handover target. The performance of the proposed method is evaluated and compared with the traditional multiple attribute decision-making methods including simple additive weighting and VIKOR methods. Results show that the GRA-HO method has outperformed the existing methods in terms of reducing the number of frequent handovers and link failures, in addition to enhancing energy efficiency

Handover Management Techniques for Heterogeneous Cellular Networks

The rapid growth in the mobile users of cellular networks has brought big challenges for the networks and their providers in tackling the coverage extension and capacity boosting. The Heterogeneous Networks (HetNets) is considered as one of the best solutions to meet the ever increasing data rate and coverage demands. The HetNets consists of the deployment of smaller base stations (known as small cells) overlaying the traditional macrocells. Indeed, small cells can cover some areas where it is not possible to be covered by the macrocells. Despite the potential benefits of deploying small cells along with the traditional macrocell, the ultra-dense deployment brought the concerns of interference and mobility management. As a result of mobility, users will have to perform handover between base stations to maintain service continuity. However, the ultra-dense small cells will cause a huge number of frequent handovers resulting in many issues including high signalling overhead, handover failures, unbalanced load distribution and high energy consumption. Unfortunately, these issues will limit the benefits of deploying small cells. In summary, the purpose of this thesis is to investigate the existing literature works and then propose techniques to address the problems mentioned above in HetNets. Firstly, a handover technique is proposed to reduce the number of target small cells for the user and to minimize the unnecessary handovers in the HetNets which eventually enhances the overall quality of service delivered to the end user. Then, we considered both of the unnecessary handover and handover failure where the number of target small cells is also reduced by considering interference, predicted time that a user may stay in the coverage area of a small cell and the small cell capacity. Additionally, a novel handover technique is proposed to improve the throughput and load balancing is proposed where an offloading strategy, by forcing the handover considering the load and interference, is considered to derive a handover margin. The margin is then used to perform the handover to the target base station. Moreover, the multiple attribute decision making principle is used to model the handover problem in HetNets and to address the user energy efficiency. First, we propose a handover mechanism to minimize the unnecessary handover and radio link failure, in addition to enhancing the throughput. This is obtained by deploying multiple attribute decision making weighted methods, Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), in which selected handover parameters are weighted to evaluate their importance prior to the handover process. Second, a user-energy efficient handover mechanism is investigated via multiple attributes decision making weighted strategy, Grey Rational Analysis (GRA), which accounts for the minimization of the unnecessary handover and radio link failure, in addition to enhancing the user experience in terms of reducing its power consumption. Finally, a game theory framework is used to manage the handover problem in terms of energy efficiency. First, we propose a novel handover method for energy efficiency in HetNets where a game theory approach is used to manage the transmission power of the base stations by reducing/halting the transmission power for light-loaded base stations prior to the handover process. The game is solved mathematically using the principle of coarse correlated equilibrium. The Regret Matching-based Learning is deployed to learn the equilibrium in this game. Second, a non-cooperative game approach is formulated where base stations behave selfishly to obtain higher gain. The payoff function is defined to consider the gain from increasing the base station transmission power (the utility function) against the cost resulted from energy consumption, base station load and unnecessary handovers performed to this base station. In order to solve the game, we proved the existence of at least one Nash equilibrium