This thesis presents research on transport layer behavior in wireless networks. As the Internet is expanding its reach to include mobile devices, it has become apparent that some of the original design assumptions for the dominant transport protocol, TCP, are approaching their limits. A key feature of TCP is the congestion control algorithm, constructed with the assumption that packet loss is normally very low, and that packet loss therefore is a sign of network congestion. This holds true for wired networks, but for mobile wireless networks non-congestion related packet loss may appear. The varying signal power inherent with mobility and handover between base-stations are two example causes of such packet loss. This thesis provides an overview of the challenges for TCP in wireless networks together with a compilation of a number of suggested TCP optimizations for these environments. A TCP modification called TCP-L is proposed. It allows an application to increase its performance, in environments where residual bit errors normally give a degraded throughput, by making a reliability tradeoff. The performance of TCP-L is experimentally evaluated with an implementation in the Linux kernel. The transport layer performance in a 4G scenario is also experimentally investigated, focusing on the impact of the link layer design and its parameterization. Further, for emulation-based protocol evaluations, controlled packet loss and bit error generation is shown to be an important aspect.

The sky-rocketing growth of multimedia infotainment applications and broadband-hungry mobile devices exacerbate the stringent demand for ultra high data rate and more spectrum resources. Along with it, the unbalanced temporal and geographical variations of spectrum usage further inspires those spectral-efficient networks, namely, cognitive radio and heterogeneous cellular networks (HCNs). This thesis focuses on the system design and performance enhancement of cognitive radio (CR) and HCNs. Three different aspects of performance improvement are considered, including link reliability of cognitive radio networks (CNs), security enhancement of CNs, and energy efficiency improvement of CNs and HCNs. First, generalized selection combining (GSC) is proposed as an effective receiver design for interference reduction and reliability improvement of CNs with outdated CSI. A uni- ed way for deriving the distribution of received signal-to-noise ratio (SNR) is developed in underlay spectrum sharing networks subject to interference from the primary trans- mitter (PU-Tx) to the secondary receiver (SU-Rx), maximum transmit power constraint at the secondary transmitter (SU-Tx), and peak interference power constraint at the PU receiver (PU-Rx), is developed. Second, transmit antenna selection with receive generalized selection combining (TAS/GSC) in multi-antenna relay-aided communica- tion is introduced in CNs under Rayleigh fading and Nakagami-m fading. Based on newly derived complex statistical properties of channel power gain of TAS/GSC, exact ergodic capacity and high SNR ergodic capacity are derived over Nakagami-m fading. Third, beamforming and arti cial noise generation (BF&AN) is introduced as a robust scheme to enhance the secure transmission of large-scale spectrum sharing networks with multiple randomly located eavesdroppers (Eves) modeled as homogeneous Poisson Point Process (PPP). Stochastic geometry is applied to model and analyze the impact of i BF&AN on this complex network. Optimal power allocation factor for BF&AN which maximizes the average secrecy rate is further studied under the outage probability con- straint of primary network. Fourth, a new wireless energy harvesting protocol is proposed for underlay cognitive relay networks with the energy-constrained SU-Txs. Exact and asymptotic outage probability, delay-sensitive throughput, and delay-tolerant through- put are derived to explore the tradeoff between the energy harvested from the PU-Txs and the interference caused by the PU-Txs. Fifth, a harvest-then-transmit protocol is proposed in K-tier HCNs with randomly located multiple-antenna base stations (BSs) and single antenna mobile terminals (MTs) modeled as homogeneous PPP. The average received power at MT, the uplink (UL) outage probability, and the UL average ergodic rate are derived to demonstrate the intrinsic relationship between the energy harvested from BSs in the downlink (DL) and the MT performance in the UL. Throughout the thesis, it is shown that link reliability, secrecy performance, and energy efficiency of CNs and HCNs can be signi cantly leveraged by taking advantage of multiple antennas, relays, and wireless energy harvesting.

Message brokers are the backbone of modern publish subscribe messaging systems. These brokers can degrade or fail for a variety of reasons. This research specifically looks at the detection, prediction and mitigation of bottlenecks in brokers. The message-oriented-middleware framework here uses either a cluster of brokers on a Local Area Network (LAN) or a federation of brokers on a Wide Area Network (WAN) to route messages, facilitate multicasting and ameliorate demand surges and geographically related faults. Sensors have been constructed to monitor brokers and controllers to run the bottleneck detection algorithms. An overlay manager controls broker and topic pairing. Each topic is assigned a primary and secondary broker. When a failure is predicted, the overlay manager routes messages from the failing broker by switching topics to its secondary broker(s). The application for bottleneck forecasting is to allow us to pre-empt a broker failure and hence reroute messages to other brokers to increase resilience and reliability. The key contributions of this research are an abstract model of message-oriented-middleware broker based on the Apache Qpid message broker coupled with the use of analytical autoregressive exogenous (ARX) models that describes the broker behaviour during bottleneck conditions. The Apache Qpid message broker is a message broker that implements the Advanced Message Queuing Protocol (AMQP) for publish-subscribe messaging. ARX models are autoregressive models where the output depends on the previous output as well as external stimuli. These components are integrated to produce a generalised technique for calibrating broker performance and detection of bottlenecks in the broker. This research show how models were initially constructed using a complete range of input data. As bottlenecks occur only when the broker is heavily loaded, input data during idle periods can cause corruption to the model fit. Models were constructed with segmented input data, with each segment covering the range of one peak period. The segmented input allows the modelling of the broker behaviour only when it is experiencing a bottleneck. The result of this is a much-improved fit of the predictive models. The work here is compared against previous work using Markov-chains for creating predictive models. The results of both approaches are compared and reported.

Infrastructure-based indoor geolocation systems utilizing a regular grid arrangement of sensors are being investigated for many applications in indoor wireless networks. One of the factors affecting the Quality of Estimation (i.e. location estimation accuracy) of these systems is node density. In this dissertation we study the effects of node density on indoor geolocation systems based on time of arrival (TOA). The effects of node density on the performance of various indoor communication networks (e.g. wireless LANs) in the presence of realistic indoor radio propagation models has been analyzed and reported in the literature. However, we have noted the lack of an equivalent analysis on the effects of node density on the performance of infrastructure-based indoor geolocation systems. The goal of this dissertation is to address this knowledge gap. Due to the complicated behavior of the indoor radio channel, the relationship between the node density and Quality of Estimation (QoE) is not straightforward. Specifically, QoE depends on factors such as the bandwidth used to make the TOA-based distance measurements, the existence of undetected direct path (UDP) conditions, and coverage. In this dissertation, we characterize these dependencies. We begin by characterizing the Quality of Estimation for closest-neighbor (CN), least-squares (LS) and weighted LS techniques in the presence of different node densities and a distance measurement error (DME) model based on ray tracing (RT) that was recently proposed in the literature. Then, we propose a new indoor geolocation algorithm, Closest Neighbor with TOA Grid (CN-TOAG), characterize its performance and show that it outperforms the existing techniques. We also propose an extension to this algorithm, known as Coverage Map Search (CMS) that allows it to be used in suboptimal coverage conditions (which we refer to as partial coverage conditions) that may prevent other TOA-based geolocation techniques from being used. We treat the partial coverage case by defining coverage probabilities and relating them to the average radius of coverage and dimensions of the indoor area. Next, we characterize the effects of node density on the performance of the CN-TOAG algorithm using a DME model based on UWB measurements, and show that node density and partial coverage are intimately linked together. Since this second DME model also allows for the effects of UDP conditions (which affect the quality of the link or QoL), we also characterize the effects of varying UDP conditions on the performance. Finally, we conclude the dissertation by presenting an analysis of fundamental performance bounds for infrastructure-based indoor geolocation, specifically focusing on the Cramer-Rao Lower Bound (CRLB).

"As streaming techniques and wireless access networks become more widely deployed, a streaming multimedia connection with the "last mile" being a wireless network is becoming increasingly common. However, since current streaming techniques are primarily designed for wired networks, streaming multimedia applications can perform poorly in wireless networks. Recent research has shown that the wireless network conditions, such as the wireless link layer rate adaptation, contending traffic, and interference can significantly degrade the performance of streaming media applications. This performance degradation includes increased multimedia frame losses and lower image quality caused by packet loss, and multiple rebuffering events that stop the media playout. This dissertation presents the model, design, implementation and evaluation of an application layer solution for improving streaming multimedia application performance in IEEE 802.11 wireless networks by using enhanced bandwidth estimation techniques. The solution includes two parts: 1) a new Wireless Bandwidth estimation tool (WBest) designed for fast, non-intrusive, accurate estimation of available bandwidth in IEEE 802.11 networks, which can be used by streaming multimedia applications to improve the performance in wireless networks; 2) a Buffer and Rate Optimization for Streaming (BROS) algorithm using WBest to guide the streaming rate selection and initial buffer optimization. WBest and BROS are implemented and incorporated into an emulated streaming client-server system, Emulated Streaming (EmuS), in Linux and evaluated under a variety of wireless conditions. The evaluations show that with WBest and BROS, the performance of streaming multimedia applications in wireless networks can be significantly improved in terms of multimedia frame loss, rebuffer events and buffer delay."

As the popularity of wireless networks increases, so does the need to protect them. In recent years, many researchers have studied the limitations of the security mechanisms that protect wireless networks. There has also been much research in the power consumption introduced by the network card. Technologies such as CPU and memory are increasing and so is their need for power, but battery technology is increasing at a much slower rate, forming a“battery gap". Because of this, battery capacity plays a major role in the usability of the devices. Although the effect of the network communication on a mobile device's battery has been widely researched, there has been less research on the effect of the security profile on energy usage. In this thesis, we examine a method for analyzing trade-offs between energy and security proposed by Colon Osorio et al. This research describes a method to identify the most appropriate security profile for a given application, given battery constraints. The same method can also be used to discover the minimum battery capacity to maintain a minimum security profile for a predefined amount of time. Trade-offs and optimality are analyzed using a cost-energy function, CE, and security measure, SM. CE encompasses the energy required to use countermeasure M against a specific vulnerability, Vi, as well as the energy consumed in bulk transfer. SM is a numerical representation of the effectiveness of a set of security mechanisms which utilize the set of countermeasures to defend against a set of vulnerabilities. Using CE and SM, we can compare different security profiles using a trade-off model. Having defined such a framework, we investigate different instances and examples where the use of the model is helpful in accessing trade-offs between security obtained and energy consumed to achieve such security. This was first examined through an analytical study, followed by experimentation. The major contributions of this work are an energy-security trade-off model and its empirical validation. This work extends the empirical experimentation done by other researchers such as Potlapally et al., Karri et al., and Stemm and Katz on the relationship between energy and the security of wireless communications in battery-constrained devices.

"In this thesis, a transmission frequency rendezvous approach for secondary users deployed in decentralized dynamic spectrum access networks is proposed. Frequency rendezvous is a critical step in bootstrapping a wireless network that does not possess centralized control. Current techniques for enabling frequency rendezvous in decentralized dynamic spectrum access networks either require pre-existing infrastructure or use one of several simplifying assumptions regarding the architecture, such as the use of regularly spaced frequency channels for communications. Our proposed approach is designed to be operated in a strictly decentralized wireless networking environment, where no centralized control is present and the spectrum does not possess pre-defined channels. In our proposed rendezvous algorithm, the most important step is pilot tone detection and receiver query. In order to realize a shortest search time for the target receiver, an efficient scanning rule should be employed. In this thesis, three scanning rules are proposed and evaluated, namely: frequency sequence scanning, pilot tone strength scanning, and cluster scanning. To validate our result, we test our scanning rules with actual paging band spectrum measurements. Previous research on security of network coding focuses on the protection of data dissemination procedures and the detection of malicious activities such as pollusion attacks. The capabilities of network coding to detect other attacks has not been fully explored. In this thesis, a new mechanism based on physical layer network coding to detect wormhole attacks is proposed. When two signal sequences collide at the receiver, the difference between the two received sequences is determined by its distances to the senders. Therefore, by comparing the differences between the received sequences at two nodes, we can estimate the distance between them and detect those fake neighbor connections through wormholes. While the basic idea is clear, we design many schemes at both physical and network layers to turn the idea into a practical approach. Simulations using BPSK modulation at the physical layer show that the wireless nodes can effectively detect fake neighbor connections without the adoption of any special hardware on them."

This thesis describes a real-time software-defined-radio implementation of the time-slotted round-trip carrier synchronization protocol in two-source and three-source communication systems. The techniques developed in this thesis can be used to synchronize the carriers of two or three single-antenna wireless transmitters with independent local oscillators so that their band-pass transmissions combine constructively at an intended receiver. Synchronization is achieved via the time-slotted transmission of (i) an unmodulated primary beacon from the destination to the sources and (ii) a series of secondary unmodulated beacons between the sources. Explicit channel state information is not exchanged between the sources and/or the destination. When synchronized, the single-antenna sources are able to cooperatively transmit as a distributed beamformer and achieve increased transmission range, reduced transmission energy, and/or increased security. The experimental results in this thesis confirm the theoretical predictions and also provide explicit guidelines for the real-time implementation of a carrier synchronization technique suitable for distributed transmit beamforming.

Developments such as machine-to-machine communications and multimedia services are placing growing demands on high-speed reliable transmissions and limited wireless spectrum resources. Although multiple-input multiple-output (MIMO) systems have shown the ability to provide reliable transmissions in fading channels, it is not practical for single-antenna devices to support MIMO system due to cost and hardware limitations. Cooperative communication allows single-antenna devices to share their spectrum resources and form a virtual MIMO system where their quality of service (QoS) may be improved via cooperation. Most cooperative communication solutions are based on fixed spectrum access schemes and thus cannot further improve spectrum efficiency. In order to support more users in the existing spectrum, we consider dynamic spectrum access schemes and cognitive radio techniques in this dissertation. Our work includes the modelling, characterization and optimization of QoS-constrained cooperative networks and cognitive radio networks. QoS constraints such as delay and data rate are modelled. To solve power control and channel resource allocation problems, dynamic power control, matching theory and multi-armed bandit algorithms are employed in our investigations. In this dissertation, we first consider a cluster-based cooperative wireless network utilizing a centralized cooperation model. The dynamic power control and optimization problem is analyzed in this scenario. We then consider a cooperative cognitive radio network utilizing an opportunistic spectrum access model. Distributed spectrum access algorithms are proposed to help secondary users utilize vacant channels of primary users in order to optimize the total utility of the network. Finally, a noncooperative cognitive radio network utilizing the opportunistic spectrum access model is analyzed. In this model, primary users do not communicate with secondary users. Therefore, secondary users are required to find vacant channels on which to transmit. Multi-armed bandit algorithms are proposed to help secondary users predict the availability of licensed channels. In summary, in this dissertation we consider both cooperative communication networks and cognitive radio networks with QoS constraints. Efficient power control and channel resource allocation schemes have been proposed for optimization problems in different scenarios.

Future 5G systems and beyond are expected to implement compact and versatile antennas in highly densifi ed millimetre-wave (MMW) wireless networks. This research emphasises on the realisation of 5G antennas provided with wide bandwidth, high gain, adaptable performance, preferably conformal implementation, and feasible bulk fabrication. Ka{band (26.5{40 GHz) is selected based on recent 5G standardisation, and novel antenna geometries are developed in this work on both rigid and flexible substrates by implementing advanced techniques of frequency reconfi guration, multiple-input-multiple- output (MIMO) assembly, as well as wideband and multiband antennas and arrays. Nove lMMW wideband antennas are presented for 5G and spatial diversity at the antenna front-ends is substantially improved by deploying wideband antennas in a MIMO topology for simultaneous multiple-channel communication. However, wideband operation is often associated with efficiency degradation, which demands a more versatile approach that allows the adaptable antenna to select the operating frequency. In this research, high performance recon figurable antennas are designed for frequency selection over Ka- {band. Also, an efficient and conformal antenna front-end solution is developed, which integrates both frequency recon guration and MIMO technology. Gain of the antenna is critically important for 5G systems to mitigate high propagation losses. Antenna design with both high gain and bandwidth is challenging as wideband antennas are traditionally gain-limited, while antenna arrays deliver high gain over a narrow bandwidth. An Enhanced Franklin array model is proposed in this thesis, which aggregates multiband response with high gain performance. Furthermore, novel flexible monopole antenna and array con gurations are realised to attain high gain profi le over the complete Ka{band. These proposed 5G antennas are anticipated as potential contribution in the progress towards the realisation of future wireless networks.