Nonclassical traffic modeling and performance analysis of cellular mobile networks with and without channel reservation

Mobility modeling is a critical step in the design of mobile self-organizing networks. With the emergence of small-scale and short-range wireless communication devices, the communication sphere shrinks (radio range or sensing range), which leads to an increase in the need for fine-grained representations of mobility. In fact, mobility models must scale accordingly to the application and reflect real scenarios in which wireless devices are deployed. Currently, self-organizing networks are evaluated using mobility models that do not represent the precise motion of mobile individuals at small scales. In this article we present a new class of mobility models, namely, behavioral mobility (BM) models, which decomposes mobility into simple atomic individual behaviors. Combined, these behaviors yield realistic displacement patterns by reproducing the mobility observed at small scales in every day life, in both space and time

The high-level contributions of this paper are: (1) A generic algorithm to determine connected dominating sets (CDS) for mobile ad hoc networks and its use to find CDS of different categories: maximum density-based (MaxD-CDS), node ID-based (ID-CDS) and stability-based (minimum velocity-based, MinV-CDS); (2) Performance comparison of the above three categories of CDS algorithms with respect to two categories of mobility models: random node mobility models (Random Waypoint model) and the grid-based vehicular ad hoc network (VANET) mobility models (City Section and Manhattan mobility models), with respect to the CDS Node Size and Lifetime. The performance of a CDS is observed to depend on the criteria used to form the CDS (i.e., the node selection criteria of the underlying algorithm) and the mobility model driving the topological changes. For each category of CDS, we identify the mobility model under which one can simultaneously maximize the lifetime and node size, with minimal tradeoff. For the two VANET mobility models, we also evaluate the impact of the grid block length on the CDS lifetime and node size.

Simulation is the most important and widely used method in the research of Mobile Ad hoc NETworks (MANET). The topology of MANET and the mobility of mobile nodes are the key factors that have impact on the performance of protocols. However, most of the existing works are based on random movement, and the fact that the network topology is highly related to the environment of MANET is overlooked. In this paper, we propose a novel Environment-Aware Mobility (EAM) model which models a more realistic movement of mobile nodes. Environment objects such as Route and Hotspot, etc are introduced to represent the environment components by Scalable Vector Graphics (SVG). This model is considered to be a complex model with a combination of existing conventional mobility models and network environments. The results show that the intrinsic characteristics and properties of the environments have a significant influence on the performance of MANET protocols.

Performance Analysis of Wireless Adhoc Networks in Flat Fading and Frequency Selective Fading channels

Unmanned aerial vehicle (UAV) provides a quick and feasible solution to urgent communications in isolated region, in which reliable wireless communication link is unavailable through conventional terrestrial base stations (BSs). In this paper, we model the UAV- assisted cellular network with isolated region as a homogeneous Poisson point process in the infinite 2D plane with a circular nulling area. Within the circular area, users are served by a UAV-mounted BS hovering at the center of this area. We apply a probabilistic multi-slope path-loss large-scale model as well as Nakagami-m small-scale model to characterize the air- to-ground channel. With mathematical tools from stochastic geometry, we derive the coverage probability of the users located within the isolated region. Based on the derived expression, we show the existence of the optimal UAV altitude to achieve the maximal coverage probability. We further investigate the impacts of isolated region size and ground BS density on the optimal UAV altitude and the achievable maximal coverage probability.

This paper extends previous research efforts related to the simulation performance modelling and analysis of satellite communication networks. Specifically, the use of low earth orbit (LEO) satellite networks for personal communications is examined. Six different satellite constellation configurations are investigated in a packet-switched operating environment. Performance metrics examined are the end-to-end packet delay and the utilization of satellite channels in the dynamic environment. Realistic and accurate models of the physical satellite network and its terrestrial transmitters require that numerous operating characteristics and assumptions be specified. These are based on proposed design requirements of commercial systems, such as Iridium. Via the use of simulation, we show the relative delay and utilization performance of differing satellite network architectures. From these simulation models, mathematical metamodels are derived for the system delays. These innovative models are used to predict the delay performance of different network architectures not previously simulated. Comparison of these metamodels with simulation results show that metamodels provide an accurate means for performance prediction. Copyright © 1999 John Wiley & Sons, Ltd.

Employing a cross-layer approach, the explicit relationships between the fading channel characteristics and the significant teletraffic variables as well as the performance metrics in wireless network evaluation are formulated. In particular, the channel holding time, handoff probability, handoff call arrival rate, call blocking probability, call completion probability, and forced termination probability are developed, taking into account the carrier frequency (or equivalently wavelength), maximum Doppler frequency, and fade margin. In addition, the set of formulas are derived with the generalized assumptions for the call holding time and cell residence time. The analytical model has been validated by the simulation with the conventional exponential model and, additionally, the relaxed models for call holding time and cell residence time, e.g., Erlang and hyper-Erlang. The comparison demonstrates that the traditional result without considering the fading channel characteristics leads to substantially overestimated call blocking probability and call completion probability. The methodology presented in this paper provides a feasible manner for the wireless network cross-layer design and optimization

Video modeling and performance analysis of ATM networks by Kwok-leung Chung thesis 1995 xii, 81 leaves : ill. ; 30 cm Video sources will become one of the major traffic in future ATM networks. The video sources should be transmitted…Read more ›

By controlling the beam directions, intelligent re-flecting surfaces (IRSs) are expected to reconstruct wireless propagation environments. In order to fully understand the potential of IRSs to improve cellular network performance, accurate system modeling and analysis of the IRS assisted cellular networks are particularly important. In this paper, using stochastic geometry, we provide an analytical framework for IRS-assisted cellular networks. Particularly, we model the 3D dynamic beamforming of BSs and IRSs based on geometry and radiation patterns to characterize the interference from both BSs and IRSs. Correspondingly, we derive the expression of the coverage prob-ability. Numerical results also show that the deployment of IRSs significantly enhances the system performance compared with traditional cellular networks without IRSs. Besides, we reveal the impact of system parameters related to BSs and IRSs (such as height, mainlobe beamwidth, etc.) on the coverage performance, thereby providing technical guidelines for the deployment of IRSs in the future cellular network.

In this paper, we propose intelligent call admission control for wideband code-division multiple-access (CDMA) cellular systems to support differentiated quality-of-service (QoS) requirements, guarantee the forced termination probability of handoffs, and maximize the spectrum utilization. The intelligent call admission controller (ICAC) contains a fuzzy call admission processor to make admission decision for a call request by considering QoS measures such as the forced termination (drop call) probability of handoff, the outage probability of all service types, the predicted next-step existing-call interference, the link gain, and the estimated equivalent interference of the call request. The pipeline recurrent neural network (PRNN) is used to accurately predict the next-step existing-call interference, and the fuzzy logic theory is applied to estimate the new/handoff call interference based on knowledge of effective bandwidth method. Simulation results indicate that ICAC achieves system capacity higher than conventional CAC schemes by an amount of more than 10% in both low and high moving speed cases. Moreover, ICAC can cope with the unpredictable statistical fluctuation of wireless multimedia traffic; it always fulfill QoS requirements for all service types and keep the forced termination probability satisfied, while the CAC of multimedia calls (MCAC) and SIR-based CAC with intercell interference prediction (PSIR-CAC) fail to adapt to the variation of traffic conditions.

Due to a tremendous increase in mobile traffic, mobile operators have started to restructure their networks to offload their traffic. New research directions will lead to fundamental changes in the design of future Fifth-generation (5G) cellular networks. For the formal reason, the study solves the physical network of the mobile base station for the prediction of the best characteristics to develop an enhanced network with the help of graph theory. Any number that can be uniquely calculated by a graph is known as a graph invariant. During the last two decades, innumerable numerical graph invariants have been portrayed and used for correlation analysis. In any case, no efficient assessment has been embraced to choose, how much these invariants are connected with a network graph. This paper will talk about two unique variations of the hexagonal graph with great capability of forecasting in the field of optimized mobile base station topology in setting with physical networks. Since K-banhatti sombor invariants (KBSO) and Contrharmonic-quadratic invariants (CQIs) are newly introduced and have various expectation characteristics for various variations of hexagonal graphs or networks. As the hexagonal networks are used in mobile base stations in layered, forms called honeycomb. The review settled the topology of a hexagon of two distinct sorts with two invariants KBSO and CQIs and their reduced forms. The deduced outcomes can be utilized for the modeling of mobile cellular networks, multiprocessors interconnections, microchips, chemical compound synthesis and memory interconnection networks. The results find sharp upper bounds and lower bounds of the honeycomb network to utilize the Mobile base station network (MBSN) for the high load of traffic and minimal traffic also.

Since mobile networks are not currently deployed on a large scale, research in this area is mostly by simulation. Among other simulation parameters, the mobility model plays a very important role in determining the protocol performance in MANET. Based on random direction mobility model, a high dynamic adaptive mobility network model is proposed in the paper. The algorithms and modeling are mainly studied and explained in detail. The technique keystone is that normal distribution is combined with uniform distribution and inertial feedback control is combined with kinematics, through the adaptive control on nodes speed and prediction tracking on nodes routes, an adaptive model is designed, which can be used in simulations to produce realistic and dynamic network scenarios. It is the adaptability that nodes mobile parameters can be adjusted randomly in three-dimensional space. As a whole, colony mobility can show some rules. Such random movement processes as varied speed and dwells are simulated realistically. Such problems as sharp turns and urgent stops are smoothed well. The model can be adapted to not only common dynamic scenarios, but also high dynamic scenarios. Finally, the mobility model performance is analyzed and validated based on random dynamic scenarios simulations.

Since multi-hop mobile ad hoc network (MANET) contains a set of wireless mobile nodes forming a temporary network, the topology is strongly influenced by the node mobility models. Numerous mobility models have been presented, including the Random Waypoint Mobility Model (RWMM), Manhattan Grid Mobility Model (MGMM), Freeway Mobility Model (FMM), and so on. In MGMM, the trajectories of mobile nodes are confined to a grid topology. MGMM is an important mobility model, and numerous objects following MGMM can be enumerated, such as the movement of cars in the city, the movement of people though department stores etc. The expected link life time (ELLT) is an important performance parameter in MANET. When a node wishes to transmit information to the other node directly, these two nodes must be within each other's transmission range for a period of time. This period is called the link life time (LLT). The ELLT is the expected value of LLT. The goal of this work largely focuses on identifying the ELLT of the MANET under MGMM by using mathematical analysis. Based on our observation, two nodes involved in constructing a connection under MGMM can be classified into three independent cases: namely parallel with opposite directions, parallel with same directions, and vertical cases. These three cases can be formulated independently. To verify these formulations numerous simulations are done by ns2, and the theoretical and simulation results are well matched.

The performance evaluation of ad hoc network components through simulation allows for isolation of parameters, easy access to global quantities and a statistically significant number of repeatable trials. In designing network protocols, it is important to investigate the relationship between global network performance and the underlying locally observed network characteristics. Mobility models are used to define the movement of nodes in the simulation space. A wide variety of mobility models exist, and the choice of mobility model has significant influence over locally observed metrics. Unfortunately, many mobility models exhibit spatial and temporal non-stationarity of important metrics, such that global averages of certain metrics are not representative of local observations. This finding impacts on the development of adaptive ad hoc architectures. This paper explores the spatial stationarity of frequently used mobility models. It focuses on the importance of stationarity in relation to the evaluation of performance studies. The spatial non-stationarity of link statistics, and the impact of this artefact on network performance evaluation is examined for the Toroidal Random Waypoint and Random Direction mobility models. We show that the Toroidal Random Waypoint model exhibits spatial stationarity of link statistics. Furthermore, we demonstrate that network performance studies in spatially stationary environments produce dissimilar results to those produced by non-stationary environments. This shows the importance of spatial stationarity when investigating global network performance and locally observed network characteristics.

In this paper we study the so-called random waypoint (RWP) mobility model in the context of cellular networks. In the RWP model the nodes, i.e., mobile users, move along a zigzag path consisting of straight legs from one waypoint to the next. Each waypoint is assumed to be drawn from the uniform distribution over the given convex domain. In this paper we characterise the key performance measures, mean handover rate and mean sojourn time from the point of view of an arbitrary cell, as well as the mean handover rate in the network. To this end, we present an exact analytical formula for the mean arrival rate across an arbitrary curve. This result together with the pdf of the node location, allows us to compute all other interesting measures. The results are illustrated by several numerical examples. For instance, as a straightforward application of these results one can easily adjust the model parameters in a simulation so that the scenario matches well with, e.g., the measured sojourn times in a cell.