Fuzzy-logic framework for future dynamic cellular systems

There is a growing need to develop more robust and energy-efficient network architectures to cope with ever increasing traffic and energy demands. The aim is also to achieve energy-efficient adaptive cellular system architecture capable of delivering a high quality of service (QoS) whilst optimising energy consumption. To gain significant energy savings, new dynamic architectures will allow future systems to achieve energy saving whilst maintaining QoS at different levels of traffic demand. We consider a heterogeneous cellular system where the elements of it can adapt and change their architecture depending on the network demand. We demonstrate substantial savings of energy, especially in low-traffic periods where most mobile systems are over engineered. Energy savings are also achieved in high-traffic periods by capitalising on traffic variations in the spatial domain. We adopt a fuzzy-logic algorithm for the multi-objective decisions we face in the system, where it provides stability and the ability to handle imprecise data

Modeling Seamless Vertical Handovers in Heterogeneous Wireless Networks

Vertical handover in heterogeneous wireless networks provides customers with better Quality of Service (QoS) experience. For seamless handover, timely initiation of handover process plays a key role. Various vertical handover management protocols have been proposed and standardized to support mobility across heterogeneous networks. In Media Independent Handover (MIH) based schemes, distributed handover decision is made via certain predefined triggers that consider user context. In this paper, we present a comprehensive review of the modeling techniques used during management of vertical handover. We have also defined a novel architecture, HRPNS: Handoff Resolving and Preferred Network Selection module enabling vertical handover that ensures QoS. The construction of HRPNS module involves integration of fuzzy logic and Markov Decision Process (MDP) for providing precise decision of handover

Vertical Handover Decision Algorithm in Heterogeneous Wireless Networks

[EN] With the recent progress in the area of cellular communication the issue of inter cells handover without dropping an ongoing connection with the base station has arisen. In this paper, the focus is on the performance of vertical handover. Various proposed interconnection architectures for vertical handover in heterogeneous networks were studied. Two different algorithms to make the decision on when and to which network perform a handover were considered. In the first of them the decision is based on the received signal strength (RSS). In the second one a fuzzy logic system that uses RSS, bandwidth, battery power and packet loss as the input parameters is proposed. The simulation results show that the algorithm based on fuzzy logic leads to a reduction of the number of handovers and a minimisation of the power consumption as compared to the first algorithm used here and the existing algorithms.This work was supported by the Spanish Ministry of Economy and Competitiveness through Grants TIN2013-47272-C2-1-R and BES-2011-045551.Benaatou, W.; Latif, A.; Pla, V. (2017). Vertical Handover Decision Algorithm in Heterogeneous Wireless Networks. International Journal of Internet Protocol Technology (Online). 10(4):197-213. https://doi.org/10.1504/IJIPT.2017.08891419721310

A Genetic Algorithm-based Framework for Soft Handoff Optimization in Wireless Networks

In this paper, a genetic algorithm (GA)-based approach is used to evaluate the probability of successful handoff in heterogeneous wireless networks (HWNs) so as to increase capacity and network performance. The traditional handoff schemes are prone to ping pong and corner effects and developing an optimized handoff scheme for seamless, faster, and less power consuming handoff decision is challenging. The GA scheme can effectively optimize soft handoff decision by selecting the best fit network for the mobile terminal (MT) considering quality of service (QoS) requirements, network parameters and user’s preference in terms of cost of different attachment points for the MT. The robustness and ability to determine global optima for any function using crossover and mutation operations makes GA a promising solution. The developed optimization framework was simulated in Matrix Laboratory (MATLAB) software using MATLAB’s optima tool and results show that an optimal MT attachment point is the one with the highest handoff success probability value which determines direction for successful handoff in HWN environment. The system maintained a 90%  with 4 channels and more while a 75% was obtained even at high traffic intensity

Regressive Prediction Approach to Vertical Handover in Fourth Generation Wireless Networks

The over increasing demand for deployment of wireless access networks has made wireless mobile devices to face so many challenges in choosing the best suitable network from a set of available access networks. Some of the weighty issues in 4G wireless networks are fastness and seamlessness in handover process. This paper therefore, proposes a handover technique based on movement prediction in wireless mobile (WiMAX and LTE-A) environment. The technique enables the system to predict signal quality between the UE and Radio Base Stations (RBS)/Access Points (APs) in two different networks. Prediction is achieved by employing the Markov Decision Process Model (MDPM) where the movement of the UE is dynamically estimated and averaged to keep track of the signal strength of mobile users. With the help of the prediction, layer-3 handover activities are able to occur prior to layer-2 handover, and therefore, total handover latency can be reduced. The performances of various handover approaches influenced by different metrics (mobility velocities) were evaluated. The results presented demonstrate good accuracy the proposed method was able to achieve in predicting the next signal level by reducing the total handover latency

Optimization of Vertical Handover Performance Using Elimination Based MCDM Algorithm

In heterogeneous networks environment, Vertical Handover Decision (VHD) algorithms help mobile terminals to choose the best network between all the available networks. VHD algorithms provide the QoS to a wide range of applications anywhere at any time. In this paper, a generic and novel solution to solve the Vertical Handover (VHO) problem has been developed. This solution contains two major subsystems: The first subsystem is called elimination system. Elimination system is received the different VHO criteria such as received signal strength, network load balancing and mobile station speed from the different available networks. After that, the inappropriate alternatives are eliminated based on the elimination conditions. The second subsystem is a Multiple Criteria Decision Making (MCDM) system that chooses the appropriate alternative from the remaining alternatives of the elimination phase. For simulate the proposed solution, MATLAB program is used with aid of MATLAB-based toolbox that is called RUdimentary Network Emulator (RUNE). The combination of both subsystems avoids the processing delay caused by unnecessary computation over available networks which do not ensure connection performance. Also it avoids increasing the number of unnecessary handovers, ping pong effect, blocking rate and dropping rate by reducing the handover failure rate. A performance analysis is done and results are compared to other reference algorithms. These results demonstrate a significant improvement over other reference algorithms in terms of handover failure rate, percentage of satisfied users, and percentage of the low cost network usage

Applications of Soft Computing in Mobile and Wireless Communications

Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications