ENABLING SMART CITY SERVICES FOR HETEROGENEOUS WIRELESS NETWORKS

A city can be transformed into a smart city if there is a resource-rich and reliable communication infrastructure available. A smart city in effect improves the quality of life of citizens by providing the means to convert the existing solutions to smart ones. Thus, there is a need for finding a suitable network structure that is capable of providing sufficient capacity and satisfactory quality-of-service in terms of latency and reliability. In this thesis, we propose a wireless network structure for smart cities. Our proposed network provides two wireless interfaces for each smart city node. One is supposed to connect to a public WiFi network, while the other is connected to a cellular network (such as LTE). Indeed, Multi-homing helps different applications to use the two interfaces simultaneously as well as providing the necessary redundancy in case the connection of one interface is lost. The performance of our proposed network structure is investigated using comprehensive ns-2 computer simulations. In this study, high data rate real-time and low data rate non-real-time applications are considered. The effect of a wide range of network parameters is tested such as the WiFi transmission rate, LTE transmission rate, the number of real-time and non-real-time nodes, application traffic rate, and different wireless propagation models. We focus on critical quality-of-service (QoS) parameters such as packet delivery delay and packet loss. We also measured the energy consumed in packet transmission. Compared with a single-interface WiFi-based or an LTE-based network, our simulation results show the superiority of the proposed network structure in satisfying QoS with lower latency and lower packet loss. We found also that the proposed multihoming structure enables the smart city sensors and other applications to realize a greener communication by consuming a lesser amount of transmission power rather than single interface-based networks

A Proposal for Dynamic Frequency Sharing in Wireless Networks

Wireless networks are today employed as complementary access technology, implemented on the last hop towards the Internet end-user. The shared media that wireless deployments provide and which is relevant to interconnect multiple users has a limited technical design, as only one device can be served per unit of time, design aspect that limits the potential applicability of wireless in dense environments. This paper proposes and evaluates a novel MAC-layer mechanism that extends current wireless networks with the possibility to perform downstream transmission to multiple devices within a single transmission time-frame, resulting in improved fairness for all devices. The mechanism, which is software-defined, is backward-compatible with current wireless standards and does not require any hardware changes. The solution has been validated in a realistic testbed, and the paper provides details concerning the computational aspects of our solution; a description of the implementation; and results extracted under different realistic scenarios in terms of throughput, packet loss, as well as jitter

Load balancing using cell range expansion in LTE advanced heterogeneous networks

The use of heterogeneous networks is on the increase, fueled by consumer demand for more data. The main objective of heterogeneous networks is to increase capacity. They offer solutions for efficient use of spectrum, load balancing and improvement of cell edge coverage amongst others. However, these solutions have inherent challenges such as inter-cell interference and poor mobility management. In heterogeneous networks there is transmit power disparity between macro cell and pico cell tiers, which causes load imbalance between the tiers. Due to the conventional user-cell association strategy, whereby users associate to a base station with the strongest received signal strength, few users associate to small cells compared to macro cells. To counter the effects of transmit power disparity, cell range expansion is used instead of the conventional strategy. The focus of our work is on load balancing using cell range expansion (CRE) and network utility optimization techniques to ensure fair sharing of load in a macro and pico cell LTE Advanced heterogeneous network. The aim is to investigate how to use an adaptive cell range expansion bias to optimize Pico cell coverage for load balancing. Reviewed literature points out several approaches to solve the load balancing problem in heterogeneous networks, which include, cell range expansion and utility function optimization. Then, we use cell range expansion, and logarithmic utility functions to design a load balancing algorithm. In the algorithm, user and base station associations are optimized by adapting CRE bias to pico base station load status. A price update mechanism based on a suboptimal solution of a network utility optimization problem is used to adapt the CRE bias. The price is derived from the load status of each pico base station. The performance of the algorithm was evaluated by means of an LTE MATLAB toolbox. Simulations were conducted according to 3GPP and ITU guidelines for modelling heterogeneous networks and propagation environment respectively. Compared to a static CRE configuration, the algorithm achieved more fairness in load distribution. Further, it achieved a better trade-off between cell edge and cell centre user throughputs. [Please note: this thesis file has been deferred until December 2016

Project Final Report – FREEDOM ICT-248891

This document is the final publishable summary report of the objective and work carried out within the European Project FREEDOM, ICT-248891.This document is the final publishable summary report of the objective and work carried out within the European Project FREEDOM, ICT-248891.Preprin

Energy efficiency and interference management in long term evolution-advanced networks.

Doctoral Degree. University of KwaZulu-Natal, Durban.Cellular networks are continuously undergoing fast extraordinary evolution to overcome technological challenges. The fourth generation (4G) or Long Term Evolution-Advanced (LTE-Advanced) networks offer improvements in performance through increase in network density, while allowing self-organisation and self-healing. The LTE-Advanced architecture is heterogeneous, consisting of different radio access technologies (RATs), such as macrocell, smallcells, cooperative relay nodes (RNs), having various capabilities, and coexisting in the same geographical coverage area. These network improvements come with different challenges that affect users’ quality of service (QoS) and network performance. These challenges include; interference management, high energy consumption and poor coverage of marginal users. Hence, developing mitigation schemes for these identified challenges is the focus of this thesis. The exponential growth of mobile broadband data usage and poor networks’ performance along the cell edges, result in a large increase of the energy consumption for both base stations (BSs) and users. This due to improper RN placement or deployment that creates severe inter-cell and intracell interferences in the networks. It is therefore, necessary to investigate appropriate RN placement techniques which offer efficient coverage extension while reducing energy consumption and mitigating interference in LTE-Advanced femtocell networks. This work proposes energy efficient and optimal RN placement (EEORNP) algorithm based on greedy algorithm to assure improved and effective coverage extension. The performance of the proposed algorithm is investigated in terms of coverage percentage and number of RN needed to cover marginalised users and found to outperform other RN placement schemes. Transceiver design has gained importance as one of the effective tools of interference management. Centralised transceiver design techniques have been used to improve network performance for LTE-Advanced networks in terms of mean square error (MSE), bit error rate (BER) and sum-rate. The centralised transceiver design techniques are not effective and computationally feasible for distributed cooperative heterogeneous networks, the systems considered in this thesis. This work proposes decentralised transceivers design based on the least-square (LS) and minimum MSE (MMSE) pilot-aided channel estimations for interference management in uplink LTE-Advanced femtocell networks. The decentralised transceiver algorithms are designed for the femtocells, the macrocell user equipments (MUEs), RNs and the cell edge macrocell UEs (CUEs) in the half-duplex cooperative relaying systems. The BER performances of the proposed algorithms with the effect of channel estimation are investigated. Finally, the EE optimisation is investigated in half-duplex multi-user multiple-input multiple-output (MU-MIMO) relay systems. The EE optimisation is divided into sub-optimal EE problems due to the distributed architecture of the MU-MIMO relay systems. The decentralised approach is employed to design the transceivers such as MUEs, CUEs, RN and femtocells for the different sub-optimal EE problems. The EE objective functions are formulated as convex optimisation problems subject to the QoS and transmit powers constraints in case of perfect channel state information (CSI). The non-convexity of the formulated EE optimisation problems is surmounted by introducing the EE parameter substractive function into each proposed algorithms. These EE parameters are updated using the Dinkelbach’s algorithm. The EE optimisation of the proposed algorithms is achieved after finding the optimal transceivers where the unknown interference terms in the transmit signals are designed with the zero-forcing (ZF) assumption and estimation errors are added to improve the EE performances. With the aid of simulation results, the performance of the proposed decentralised schemes are derived in terms of average EE evaluation and found to be better than existing algorithms

PERFORMANCE STUDY FOR CAPILLARY MACHINE-TO-MACHINE NETWORKS

Communication technologies witness a wide and rapid pervasiveness of wireless machine-to-machine (M2M) communications. It is emerging to apply for data transfer among devices without human intervention. Capillary M2M networks represent a candidate for providing reliable M2M connectivity. In this thesis, we propose a wireless network architecture that aims at supporting a wide range of M2M applications (either real-time or non-real-time) with an acceptable QoS level. The architecture uses capillary gateways to reduce the number of devices communicating directly with a cellular network such as LTE. Moreover, the proposed architecture reduces the traffic load on the cellular network by providing capillary gateways with dual wireless interfaces. One interface is connected to the cellular network, whereas the other is proposed to communicate to the intended destination via a WiFi-based mesh backbone for cost-effectiveness. We study the performance of our proposed architecture with the aid of the ns-2 simulator. An M2M capillary network is simulated in different scenarios by varying multiple factors that affect the system performance. The simulation results measure average packet delay and packet loss to evaluate the quality-of-service (QoS) of the proposed architecture. Our results reveal that the proposed architecture can satisfy the required level of QoS with low traffic load on the cellular network. It also outperforms a cellular-based capillary M2M network and WiFi-based capillary M2M network. This implies a low cost of operation for the service provider while meeting a high-bandwidth service level agreement. In addition, we investigate how the proposed architecture behaves with different factors like the number of capillary gateways, different application traffic rates, the number of backbone routers with different routing protocols, the number of destination servers, and the data rates provided by the LTE and Wi-Fi technologies. Furthermore, the simulation results show that the proposed architecture continues to be reliable in terms of packet delay and packet loss even under a large number of nodes and high application traffic rates