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Modelling and Analysis of Resource Management Schemes in Wireless Networks. Analytical Models and Performance Evaluation of Handoff Schemes and Resource Re-Allocation in Homogeneous and Heterogeneous Wireless Cellular Networks.
Over recent years, wireless communication systems have been experiencing a dramatic and continuous growth in the number of subscribers, thus placing extra demands on system capacity. At the same time, keeping Quality of Service (QoS) at an acceptable level is a critical concern and a challenge to the wireless network designer. In this sense, performance analysis must be the first step in designing or improving a network. Thus, powerful mathematical tools for analysing most of the performance metrics in the network are required. A good modelling and analysis of the wireless cellular networks will lead to a high level of QoS.
In this thesis, different analytical models of various handoff schemes and resource re-allocation in homogeneous and heterogeneous wireless cellular networks are developed and investigated. The sustained increase in users and the request for advanced services are some of the key motivations for considering the designing of Hierarchical Cellular Networks (HCN). In this type of system, calls can be blocked in a microcell flow over to an overlay macrocell. Microcells in the HCN can be replaced by WLANs as this can provide high bandwidth and its users have limited mobility features. Efficient sharing of resources between wireless cellular networks and WLANs will improve the capacity as well as QoS metrics.
This thesis first presents an analytical model for priority handoff mechanisms, where new calls and handoff calls are captured by two different traffic arrival processes, respectively. Using this analytical model, the optimised number of channels assigned to
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handover calls, with the aim of minimising the drop probability under given network scenarios, has been investigated. Also, an analytical model of a network containing two cells has been developed to measure the different performance parameters for each of the cells in the network, as well as altogether as one network system. Secondly, a new solution is proposed to manage the bandwidth and re-allocate it in a proper way to maintain the QoS for all types of calls. Thirdly, performance models for microcells and macrocells in hierarchical cellular networks have been developed by using a combination of different handoff schemes. Finally, the microcell in HCN is replaced by WLANs and a prioritised vertical handoff scheme in an integrated UMTS/WLAN network has been developed. Simulation experiments have been conducted to validate the accuracy of these analytical models. The models have then been used to investigate the performance of the networks under different scenarios
Load Balancing of Elastic Data Traffic in Heterogeneous Wireless Networks
The increasing amount of mobile data traffic has resulted in an architectural innovation in cellular networks through the introduction of heterogeneous networks. In heterogeneous networks, the deployment of macrocells is accompanied by the use of low power pico and femtocells (referred to as microcells) in hot spot areas inside the macrocell which increase the data rate per unit area.
The purpose of this thesis is to study the load balancing problem of elastic data traffic in heterogeneous wireless networks. These networks consist of different types of cells with different characteristics. Individual cells are modelled as an M/G/1 - PS queueing system. This results in a multi-server queueing model consisting of a single macrocell with multiple microcells within the area. Both static and dynamic load balancing schemes are developed to balance the data flows between the macrocell and microcells so that the mean flow-level delay is minimized. Both analytical and numerical methods are used for static policies. For dynamic policies, the performance is evaluated by simulations.
The results of the study indicate that all dynamic policies can significantly improve the flow-level delay performance in the system under consideration compared to the optimal static policy. The results also indicate that MJSQ and MP are best policies although MJSQ needs less state information. The performance gain of most of the dynamic polices is insensitive with respect to the flow size distribution. In addition, many interesting tests are conducted such as the effect of increasing the number of microcells and the impact of service rate difference between macrocell and microcells
Modeling, Analysis and Design for Carrier Aggregation in Heterogeneous Cellular Networks
Carrier aggregation (CA) and small cells are two distinct features of
next-generation cellular networks. Cellular networks with small cells take on a
very heterogeneous characteristic, and are often referred to as HetNets. In
this paper, we introduce a load-aware model for CA-enabled \textit{multi}-band
HetNets. Under this model, the impact of biasing can be more appropriately
characterized; for example, it is observed that with large enough biasing, the
spectral efficiency of small cells may increase while its counterpart in a
fully-loaded model always decreases. Further, our analysis reveals that the
peak data rate does not depend on the base station density and transmit powers;
this strongly motivates other approaches e.g. CA to increase the peak data
rate. Last but not least, different band deployment configurations are studied
and compared. We find that with large enough small cell density, spatial reuse
with small cells outperforms adding more spectrum for increasing user rate.
More generally, universal cochannel deployment typically yields the largest
rate; and thus a capacity loss exists in orthogonal deployment. This
performance gap can be reduced by appropriately tuning the HetNet coverage
distribution (e.g. by optimizing biasing factors).Comment: submitted to IEEE Transactions on Communications, Nov. 201
Performance Analysis of Hierarchical Routing Protocols in Wireless Sensor Networks
This work focusses on analyzing the optimization strategies of routing
protocols with respect to energy utilization of sensor nodes in Wireless Sensor
Network (WSNs). Different routing mechanisms have been proposed to address
energy optimization problem in sensor nodes. Clustering mechanism is one of the
popular WSNs routing mechanisms. In this paper, we first address energy
limitation constraints with respect to maximizing network life time using
linear programming formulation technique. To check the efficiency of different
clustering scheme against modeled constraints, we select four cluster based
routing protocols; Low Energy Adaptive Clustering Hierarchy (LEACH), Threshold
Sensitive Energy Efficient sensor Network (TEEN), Stable Election Protocol
(SEP), and Distributed Energy Efficient Clustering (DEEC). To validate our
mathematical framework, we perform analytical simulations in MATLAB by choosing
number of alive nodes, number of dead nodes, number of packets and number of
CHs, as performance metrics.Comment: NGWMN with 7th IEEE International Conference on Broadband and
Wireless Computing, Communication and Applications (BWCCA 2012), Victoria,
Canada, 201
Statistical Delay Bound for WirelessHART Networks
In this paper we provide a performance analysis framework for wireless
industrial networks by deriving a service curve and a bound on the delay
violation probability. For this purpose we use the (min,x) stochastic network
calculus as well as a recently presented recursive formula for an end-to-end
delay bound of wireless heterogeneous networks. The derived results are mapped
to WirelessHART networks used in process automation and were validated via
simulations. In addition to WirelessHART, our results can be applied to any
wireless network whose physical layer conforms the IEEE 802.15.4 standard,
while its MAC protocol incorporates TDMA and channel hopping, like e.g.
ISA100.11a or TSCH-based networks. The provided delay analysis is especially
useful during the network design phase, offering further research potential
towards optimal routing and power management in QoS-constrained wireless
industrial networks.Comment: Accepted at PE-WASUN 201
Wireless Communications in the Era of Big Data
The rapidly growing wave of wireless data service is pushing against the
boundary of our communication network's processing power. The pervasive and
exponentially increasing data traffic present imminent challenges to all the
aspects of the wireless system design, such as spectrum efficiency, computing
capabilities and fronthaul/backhaul link capacity. In this article, we discuss
the challenges and opportunities in the design of scalable wireless systems to
embrace such a "bigdata" era. On one hand, we review the state-of-the-art
networking architectures and signal processing techniques adaptable for
managing the bigdata traffic in wireless networks. On the other hand, instead
of viewing mobile bigdata as a unwanted burden, we introduce methods to
capitalize from the vast data traffic, for building a bigdata-aware wireless
network with better wireless service quality and new mobile applications. We
highlight several promising future research directions for wireless
communications in the mobile bigdata era.Comment: This article is accepted and to appear in IEEE Communications
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