Fuzzy Logic Based Decision Making Algorithm to Optimize the Handover Performance in HetNets

Abstract

A prominent growth in a wireless communication system provides a wide range of services for a heterogeneous wireless network thus accomplishing user's needs. These real time services are delay sensitive which requires a continuous internet connection. Assuring a seamless end-end connectivity without link outages at the mid of an action is a crucial ongoing problem. Thus the main objective relies on designing a cognitive algorithm to achieve the practical impossibility of having a sustainable net connection while roaming across various technologies. Hence, to fulfill this and degrade vertical handover (VHO) issues an enhanced fuzzy logic based algorithm is proposed. Further, it focuses on improving the transmission quality with low handover latency, less packet loss and reduced false handover. Along with this the algorithm achieves an accurate prediction in the decision making of an optimal network to which the idle node gets connected. The networking environment also has an efficient mobility management, where the functioning network controls the mobility of concerned mobile nodes. Finally the simulation process of this proposal on a comprehensive test-bed infers the fuzzy logic based algorithm, guaranteed seamless connection. Further, the system has a 1.6% improvement in reducing the handover delay and 1.3% in packet loss reduction than the existing approaches, which in turn improves the transmission quality.

New Manhattan distance‐based fuzzy MADM method for the network selection

“…based on the received signal strength, the available bandwidth etc.) [5], game theory algorithms [6], genetic algorithms [7], artificial intelligence and fuzzy logic [8][9][10], neural networks, multi-attribute decision-making (MADM) methods [11][12][13][14][15], and hybrid methods combining more than one methodology [16][17][18][19]. However, the majority of these algorithms are either basic and thus inefficient or too complex that it could cause additional computational overhead, which could, in turn, break the current session.…”

“…Then, we tried the combination of MADM methods and fuzzy sets in the network selection context [18]. The fuzzy theory was developed to deal with the vagueness and uncertainties of the metrics in the industry, so as to make more precise and efficient decisions [8,10]. In this contribution, we present a new fuzzy MADM method, based on Manhattan distance, named fuzzy Manhattan distance to the ideal alternative (FMDIA).…”

“…The fuzzy decision cell, noted FD m * n , is filled like in (10), from fuzzy sets instead of numeric values as values of attributes. We note fd i j = (l i j , m i j , u i j ) its elements (fuzzy sets), to each set corresponds a linguistic level (i.e.…”

Analysis of The Impact of Fuzzy Logic Algorithm On Handover Decision in A Cellular Network

“…There is no output distribution, in this case, just the weighted average of the outputs from the computational paradigm that is based on how humans think. The advantages of the Sugeno Method that makes it more suitable for this work, is that it works well with adaptive techniques and optimization and is well suited for mathematical analysis [17]. Zero-order Sugeno…”

Ingenious Method for Conducive Handoff Appliance in Cognitive Radio Networks

“…This is carried out by allowing the unlicensed or secondary user to access the spectrum temporarily wherin the primary user is not deployed [2]. On the arrival of the primary user it is mandatory for the unlicensed user to vacate the access on spectrum thereby switching over to another unoccupied channel to prevent them from harmful interference [3].This process of change over of state or quitting the channel is referred to as handoff [4]. It is essential to note that the handoff process should take place in a swift manner without any hindrance to ensure optimal spectrum handling that is achieved by analyzing handoff performance indicators [5].…”