Multi-Criteria Handover Using Modified Weighted TOPSIS Methods for Heterogeneous Networks

Ultra-dense small cell deployment in future 5G networks is a promising solution to the ever increasing demand of capacity and coverage. However, this deployment can lead to severe interference and high number of handovers, which in turn cause increased signaling overhead. In order to ensure service continuity for mobile users, minimize the number of unnecessary handovers and reduce the signaling overhead in heterogeneous networks, it is important to model adequately the handover decision problem. In this paper, we model the handover decision based on the multiple attribute decision making method, namely Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The base stations are considered as alternatives, and the handover metrics are considered as attributes to selecting the proper base station for handover. In this paper, we propose two modified TOPSIS methods for the purpose of handover management in the heterogeneous network. The first method incorporates the entropy weighting technique for handover metrics weighting. The second proposed method uses a standard deviation weighting technique to score the importance of each handover metric. Simulation results reveal that the proposed methods outperformed the existing methods by reducing the number of frequent handovers and radio link failures, in addition to enhancing the achieved mean user throughput

Unnecessary Handover Minimization in Two-Tier Heterogeneous Networks

Ultra-dense deployment of small cells (SC) can be foreseen in 5G network under the coverage area of the macrocell (MC). A mobile user equipment (UE) should be able to discover adjacent SCs to perform the handover (HO). This process can be done by frequent neighbour cell scanning. However, extensive scanning for every SC in a dense deployment scenario is a resource wasting strategy, which results in a power dissipation of the UE battery and also lowers the throughput gain. This also means that a high number of SCs would be available for the UE to HO to. Hence, the probability of unnecessary HO will increase and in turn degrade the UE's quality of service (QoS). This paper aims to minimize unnecessary HOs in two tier heterogeneous network with dense deployment of SCs. In the proposed method, we utilise the actual distance between the UE and the SCs and the UE angle of movement to construct a shortened candidate list which helps in reducing the signal overhead of scanning and the number of unnecessary HOs. UE's movement velocity threshold based on average human walking speed is used to control the HO to the SC. Simulation results show that the proposed algorithm outperformed the conventional HO method with reduced unnecessary HOs and increased throughput for the network particularly for medium to high speed UEs resulting in good UE QoS

Decentralized Resource Allocation for Heterogeneous Cellular Networks

Heterogeneous Cellular Network (HetNet) is a promising technology for 5th generation mobile networks (5G) that can potentially improve spatial resource reuse and extend coverage, therefore allowing it to achieve significantly higher data rates than single tier networks. However, the performance of HetNet is limited by co-channel (inter-UE, inter-cell) interference. Hence, resource allocation is carefully done in this paper to ensure that the likely loss in achievable data rate due to interference doesn't diminish the gain in the achievable data rate due to higher spatial reuse. The resources which we consider in this paper are the spatial resource (unit-beamformer) and the power resource. We formulate our distributed spatial resource allocation problem as a quadratic optimization problem with non-convex quadratic constraints and solved it by exploiting stationarity karush-Kuhn-Tucker (KKT) conditions. While our proposed power resource allocation scheme is formulated as a convex optimization problem and is solved by exploiting karush-Kuhn-Tucker (KKT) conditions. Simulation results of our proposed method, when compared with other existing methods show significant improvement

Load-dependent Handover Margin for Throughput Enhancement and Load Balancing in HetNets

Inbound handover (HO) or hand-in is done when the user equipment (UE) performs HO from a macrocell (MC) to a small cell (SC), while the outbound HO or handout is done when a UE hands over from SC to MC. On the other hand, the inter-SC HO is done when a UE performs HO between two SCs. The outbound HO is not as complex as the other two types, because the UE has only one HO target base station, i.e., the MC. Therefore, in this paper, we only consider the inbound and inter-SC HO types. The user may associate with a small cell for a very short time of stay (ToS), smaller than a short time of stay threshold, and this may cause frequently unnecessary HOs and result in service interruption causing degradation in the quality of service (QoS). In this paper, we propose a novel HO method for the purpose of load balancing and throughput improvement in heterogeneous networks (HetNets). The influence of interference from both MC and SC base stations is taken into account so as to offloaded the user from the congested cell and forced it to HO to the SC that gives a good data rate by choosing the best SC, which has the highest signal to interference plus noise ratio (SINR), from a reduced neighbor cell list (NCL). The NCL is optimized utilizing the SINR threshold and ToS. The proposed method utilizes a modified A3 HO initiation event taking into account the cell load and the interference. Results show that the proposed method can perform HO while maintaining the throughput to a good level. In addition, the proposed method has significantly reduced the inter-SC HOs and inbound HO and radio link failures compared to the existing methods. Under different network conditions, load factors, and call arrival rates, results show that the proposed method can give significantly better performance, thereby producing higher throughput for the user and the network

Handover for Dense Small Cells Heterogeneous Networks: A Power-efficient Game Theoretical Approach

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

Energy Efficient Handover for Heterogeneous Networks: A Non-Cooperative Game Theoretic Approach

The small cell technology is considered as a key technology for 5G networks. The capacity expansion and coverage extension are both achieved through this deployment. However, the ultra-dense small cells deployment can cause a severe interference, a high number of frequent unnecessary handovers and/or handover failure and hence, high power consumption is expected due to the signalling overhead. Placing some small cells into idle mode, without causing degradation to the quality of service, is a good strategy to enhance the energy efficiency in the network. In this paper, we propose an energy efficient game theoretical method to reduce the energy consumption in dense small cells network. The proposed method enables the small cells to adjust their transmitting power while considering to balance the load among themselves. A non-cooperative game is formulated among the cells in the network to solve the cost function which considers both the power mode and its load. The game is solved using the regret matching-based learning distribution approach in which each cell chooses its optimal transmit power strategy to reach the equilibrium. The cell selection for handover is then made using a multiple attribute TOPSIS technique. Results show that the proposed method significantly reduces the power consumption and unnecessary handovers, in addition to improving the average small cell throughput compared to the conventional method

Hybrid Weighted Multiple Attribute Decision Making Handover Method for Heterogeneous Networks

Small cell deployment in 5G networks is a promising technology to enhance the capacity and coverage. However, unplanned deployment may cause high interference levels and high number of unnecessary handovers, which in turn result in an increase in the signalling overhead. To guarantee service continuity, minimize unnecessary handovers and reduce signalling overhead in heterogeneous networks, it is essential to properly model the handover decision problem. In this paper, we model the handover decision problem using Multiple Attribute Decision Making (MADM) method, specifically Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), and propose a hybrid TOPSIS method to control the handover in heterogeneous network. The proposed method adopts a hybrid weighting policy, which is a combination of entropy and standard deviation. A hybrid weighting control parameter is introduced to balance the impact of the standard deviation and entropy weighting on the network selection process and the overall performance. Our proposed method show better performance, in terms of the number of frequent handovers and the mean user throughput, compared to the existing methods

A Trade-off Between Unnecessary Handover and Handover Failure for Heterogeneous Networks

With fast growing traffic, high-density small cells (SC) deployment is envisioned in 5G network under the macrocell (MC) coverage area. This will improve the capacity and the cellular coverage, however, it will also introduce unnecessary handovers (UHO) and handover failures (HOF) due to user mobility and, in turn, degrades the user's quality of service (QoS). This paper aims to reduce the UHOs in a SC heterogeneous networks (HetNets) and to maintain the HOF to an acceptable level specified by the operator. Time metric is used to find a trade-off between UHO and HOF. In order to reduce the target SC list for handover, the estimated time of stay is used to avoid long neighbour list. Interference from different base stations is taken into account through the use of signal to interference plus noise ratio (SINR) metric. Simulations are performed to evaluate the performance of the proposed method. Results show that the proposed method outperformed the competitive methods presented in the literature with a lower level of UHOs and HOFs