Handover Analysis and Dynamic Mobility Management for Wireless Cellular Networks

Handover Analysis and Dynamic Mobility Management for Wireless Cellular Networks

Ramón M. Rodríguez-Dagnino, Hideaki Takagi
DOI: 10.4018/978-1-61520-680-3.ch012
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Dynamic location of mobile users aims to deliver incoming calls to destination users. Most location algorithms keep track of mobile users through a predefined location area. The design of these location algorithms is focused to minimize the generated signaling traffic. There are three basic approaches to design location algorithms, namely distance-based, time-based and movement-based. In this Chapter we focus only on the movement-based algorithm since it achieves a good compromise between complexity and performance. We minimize a cost function for this dynamic movement-based location algorithm in order to find an optimum threshold in the number of updates. Counting the number of wireless cell crossing during inter-call times is a fundamental issue for our analysis. We use renewal theory to capture the probabilistic structure of this model, and it is general enough to include a variety of probability distributions for modeling cell residence times (CRT) in exponentially distributed location areas and hyperexponentially distributed intercall times. We present numerical results regarding some important distributions.
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1. Introduction

Counting the number of handovers (or wireless cell crossings) is an important problem in cellular wireless networks. In a typical cellular topology, the area to cover a city is designed as an irregular or regular layout having non-overlapping hexagon-shaped wireless cells. During a random duration call, mobile users will cross several cell boundaries spending a random time in each of the cells. The handover process is a complex function of many factors such as: size of wireless cells, user's mobility path, call patterns, (i.e., the number of renewals or handovers in random interval of duration T or CHT). This problem has been solved in several specific cases by Cox in his monograph. The CRTs are denoted by the sequence of random variables978-1-61520-680-3.ch012.m01 or renewal times, see Figure 1. Most of the results studied by Cox are based on the ordinary renewal process, i.e., all the random variables 978-1-61520-680-3.ch012.m02 come from the same distribution with probability density function (pdf)978-1-61520-680-3.ch012.m03 We denote 978-1-61520-680-3.ch012.m04 as the number of renewals in a fixed time interval (0, t], and the first renewal 978-1-61520-680-3.ch012.m05 is started at time 0. We assume that T is independent of978-1-61520-680-3.ch012.m06. Hence, 978-1-61520-680-3.ch012.m07 gives the counts of the number of renewals (handovers) in a random interval (0, T]. This basic model studied by Cox results restrictive in common cellular networks scenarios. It is common that a mobile user begins his call somewhere inside a wireless cell. Thus, we should consider the case in which only 978-1-61520-680-3.ch012.m08 have pdf 978-1-61520-680-3.ch012.m09 while 978-1-61520-680-3.ch012.m10 may come from a different distribution. When 978-1-61520-680-3.ch012.m11 is the residual life or forward recurrence-time of 978-1-61520-680-3.ch012.m12 (Cox, 1962, page 27), we have the equilibrium renewal process, which we have studied in (Rodríguez-Dagnino, Takagi, 2003). Another important situation occurs when 978-1-61520-680-3.ch012.m13 has a different pdf from the remaining CRTs 978-1-61520-680-3.ch012.m14 and it is called the modified or delayed renewal process. We have also studied a more general case where all the pdf’s of the CRTs 978-1-61520-680-3.ch012.m15 may be different. We call this case as the generalized renewal process (Rodríguez-Dagnino, Takagi, 2005) that is applicable to irregular layout typologies. In Figure 1 we show a basic layout where we emphasize the fact of a different pdf for the first CRT.

Figure 1.

Cellular cell layout and cell residence time 978-1-61520-680-3.ch012.m16


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