Multicast service is one of the methods used to efficiently manage bandwidth when sending multimedia content. To improve bandwidth utilisation, virtualization is often invoked because of its additional features such as bandwidth sharing and support of services that require high volumes of transactional data. Currently, network providers are concerned with the bandwidth amount for efficient use of the limited wireless network capabilities and the provision of a better quality of service. The virtualization design of a multicast service framework should satisfy several objectives. For example, it should enable the interchange of service delivery between multiple networks with one shareable network infrastructure. Also, it should ensure efficient use of network resources and guarantee users' demands of Quality of Service (QoS). Thus, the design of virtualization of multicast service framework is a complex research study. Due to the bandwidth-related arguments, a strong focus has been put on technical issues that facilitate virtualization in wireless networks. A well-designed virtualized network guarantees users with the required quality service. Similarly, virtualization of multicast service is invoked to improve efficient utilisation of bandwidth in wireless networks. As wireless links prove to be unstable, packet loss is unavoidable when multicast service-oriented virtual artefacts are incorporated in wireless networks. In this thesis, a virtualized multicast framework was modelled by using Generalized Assignment Problem (GAP) methodology. Mixed Integer Linear Programing (MILP) was implemented in MATLAB to solve the GAP model. This was to optimise the allocation of multicast traffic to the appropriate virtual networks. Thus, the developed model allows users to have interchangeable services offered by multiple networks. Furthermore, Network Simulator version 3 (NS-3) was used to evaluate the performance of the virtualized multicast framework. Three applications, namely, voice over IP (VoIP), video streaming, and file download have been used to evaluate the performance of a multicast service virtualization framework in Worldwide Interoperability for Microwave Access (WiMAX) networks using NS-3. The performance evaluation was based on whether MILP is used or not used. The results of experimentation have revealed that there is good performance of virtual networks when multicast traffic is sent over one single virtual network instead of sending it over multiple virtual networks. Similarly, the results show that the bandwidth is efficiently used because the multicast traffic is not delivered through multiple virtual networks. Overall, the concepts, the investigations and the model presented in this thesis can enable mobile network providers to achieve efficient use of bandwidth and provide the necessary means to support services for QoS differentiations and guarantees. Also, the multicast service virtualization framework provides an excellent tool that can enable network providers to interchange services. The developed model can serve as a basis for further extension. Specifically, the extension of the model can boost load balancing in the flow allocation problem and activate a virtual network to deliver traffic. This may rely on the QoS policy between network providers. Therefore, the model should consider the number of users in order to guarantee improved QoS.

Hidden terminals are a key reason for performance degradation in wireless networks. When transmitting nodes cannot carrier sense each other, their packets can collide at receiving nodes, causing packet loss. In the IEEE 802.11 protocol, the RTS/CTS mechanism was introduced to combat the hidden terminal problem. While RTS/CTS can help improve network performance when hidden terminals exist, it can decrease the performance in the absence of hidden terminals due to the overhead of sending additional control traffic. For this reason, RTS/CTS is usually disabled in default driver settings. In this thesis, we present an algorithm for dynamically adjusting the use of RTS/CTS. The algorithm, called SmartRTS, continuously monitors traffic feedback in order to decide whether RTS/CTS should be used. The goal is to enable RTS/CTS in the face of hidden terminals and disable RTS/CTS when hidden terminals do not exist. We find SmartRTS to be effective and easily employed. With extensive simulations using both simple and random topologies, we demonstrate the effectiveness of SmartRTS, especially over static RTS/CTS configurations (ie- RTS/CTS enabled or RTS/CTS disabled). SmartRTS can adapt to the appearance and disappearance of hidden terminals and substantially improve overall network throughput by as much as 11-35%. / text

The Global Positioning System (GPS) is the most popular positioning system among some operational Global Navigation Satellite Systems (GNSS). However, GNSS suffer from accuracy deterioration and interruption of services in dense urban areas and are almost unavailable indoors. Although high-sensitivity receivers improve signal acquisition indoors, multipath is still be a challenging problem that affects accuracy especially indoors where a direct line of sight between transmitter and receiver almost never exist. Moreover, the wireless signal features are significantly jeopardized by obstacles and constructions indoors. To address these challenges, this research came in the context of proposing an alternative positioning system that is designed for GPS-denied environment and especially for indoors. Cramer-Rao Lower-Bound (CRLB) analysis was used to estimate the lower bound accuracy of different positioning methods indoors. Based on CRLB analysis, this research approached the wireless positioning problem indoors utilizing received signal strength (RSS) to achieve the following: 1) Developing new estimation methods to model the wireless RSS patterns in indoors. 2) Designing adaptive RSS-based wireless positioning methods for indoors. 3) Establishing a consistent framework for indoor wireless positioning systems. 4) Developing new methods to integrate inertial/odometer-based navigation systems with the developed wireless positioning methods for further improvements. The theoretical basis of the work was built on nonlinear stochastic estimation techniques including Particle Filtering, Gaussian Process Regression, Fast Orthogonal Search, Least-Squares, and Radial Basis Functions Neural Networks. All the proposed wireless positioning methods were developed and physically realized on Android-based smart-phones using the IEEE 802.11 WLANs (WiFi). In addition, successful integration with inertial/odometer sensors of mobile robots has been performed on embedded systems. Both theoretical analysis and experimental results showed significant improvements in modeling RSS indoors dynamically without offline training achieving a positioning accuracy of 1-3 meters. Sub-meter accuracy was achieved via integration with inertial/odometer sensors. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2013-03-25 16:11:59.518

When data streams transmitted on the networks include wire and wireless parts, the utilizations of bandwidth are usually not good on existing TCP protocol, that is because TCP is not designed for the wireless transferring at first. The SNOOP protocol suggests to cache the data streams from fixed stations to mobile hosts. And do local retransmissions when the data lost is still available on base stations. Our thesis supposes to modify the existing SNOOP protocol, then proving that it reduces many unnecessary timeout on the simulation result. Generating a loss notification back to the TCP sender when there is a packet loss on the wireless link. This notification makes TCP wait a short period of time while base stations is doing local retransmission. These series of mechanisms also avoid low transmit rate which occur when unnecessary timeouts. Besides we preserve the original advantages of SNOOP.

Interference creates a fundamental barrier in attempting to improve throughput in wireless networks, especially when multiple concurrent transmissions share the wireless medium. In recent years, significant progress has been made on characterizing the capacity limits of wireless networks under the premise of global and instantaneous channel state information at transmitter (CSIT). In practice, however, the acquisition of such instantaneous and global CSIT as a means toward cooperation is highly challenging due to the distributed nature of transmitters and dynamic wireless propagation environments. In many limited CSIT scenarios, the promising gains from interference management strategies using instantaneous and global CSIT disappear, often providing the same result as cases where there is no CSIT. Is it possible to obtain substantial performance gains with limited CSIT in wireless networks, given previous evidence that there is marginal or no gain over the case with no CSIT? To shed light on the answer to this question, in this dissertation, I present several achievable sum of degrees of freedom (sum-DoF) characterizations of wireless networks. The sum-DoF is a coarse sum-capacity approximation of the networks, deemphasizing noise effects. These characterizations rely on a set of proposed and existing interference management strategies that exploit limited CSIT. I begin with the classical multi-user multiple-input-single-output (MISO) broadcast channel with delayed CSIT and show how CSI feedback delays change sum-capacity scaling law by proposing an innovative interference alignment technique called space-time interference alignment. Next, I consider interference networks with distributed and delayed CSIT and show how to optimally use distributed and moderately-delayed CSIT to yield the same sum-DoF as instantaneous and global CSIT using the idea of distributed space-time interference alignment. I also consider a two-hop layered multiple-input-multiple-output (MIMO) interference channel, where I show that two cascaded interfering links can be decomposed into two independent parallel relay channels without using CSIT at source nodes through the proposed interference-free relaying technique. Then I go beyond one-way and layered to multi-way and fully-connected wireless networks where I characterize the achievable sum-DoF of networks where no CSIT is available at source nodes using the proposed space-time physical-layer network coding. Lastly, I characterize analytical expressions for the sum spectral efficiency in a large-scale single-input-multiple- output (SIMO) interference network where the spatial locations of nodes are modeled by means of stochastic geometry. I derive analytical expressions for the ergodic sum spectral efficiency and the scaling laws as functions of relevant system parameters depending on different channel knowledge assumptions at receivers. / text

An understanding of network traffic behavior is essential in the evolution of today's wireless networks, and thus leads to a more efficient planning and management of the network's scarce bandwidth resources. Prior reservation of radio resources at the future locations of a user's mobile travel path can assist with optimizing the allocation of the network's limited resources. Such actions are intended to support the network with sustaining a desirable Quality-of-Service (QoS) level. To help ensure the availability of the network services to its users at anywhere and anytime, there is the need to predict when and where a user will demand any network usage. In this thesis, the mobility behavior of the wireless users are modeled as a Markov renewal process for predicting the likelihoods of the next-cell transition. The model also includes anticipating the duration between the transitions for an arbitrary user in a wireless network. The proposed prediction technique is further extended to compute the likelihoods of a user being in a particular state after $N$ transitions. This technique can also be applied for estimating the future spatial-temporal traffic load and activity at each location in a network's coverage area. The proposed prediction method is evaluated using some real traffic data to illustrate how it can lead to a significant improvement over some of the conventional methods. The work considers both the cases of mobile users with homogeneous applications (e.g. voice calls) and data connectivity with varying data loads being transferred between the different locations.

An understanding of network traffic behavior is essential in the evolution of today's wireless networks, and thus leads to a more efficient planning and management of the network's scarce bandwidth resources. Prior reservation of radio resources at the future locations of a user's mobile travel path can assist with optimizing the allocation of the network's limited resources. Such actions are intended to support the network with sustaining a desirable Quality-of-Service (QoS) level. To help ensure the availability of the network services to its users at anywhere and anytime, there is the need to predict when and where a user will demand any network usage. In this thesis, the mobility behavior of the wireless users are modeled as a Markov renewal process for predicting the likelihoods of the next-cell transition. The model also includes anticipating the duration between the transitions for an arbitrary user in a wireless network. The proposed prediction technique is further extended to compute the likelihoods of a user being in a particular state after $N$ transitions. This technique can also be applied for estimating the future spatial-temporal traffic load and activity at each location in a network's coverage area. The proposed prediction method is evaluated using some real traffic data to illustrate how it can lead to a significant improvement over some of the conventional methods. The work considers both the cases of mobile users with homogeneous applications (e.g. voice calls) and data connectivity with varying data loads being transferred between the different locations.

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Wireless LANs (WLANs), based on the IEEE 802.11 standard, have become the standard means for indoor wireless connectivity. At the same time, the rising number of smart mobile devices, broadband access speeds, and bandwidth hungry applications (e.g., high definition video streaming) have led to an increase not only of usage but also of demand for higher data-rates. This demand for higher rates is being met with newer IEEE 802.11 standards (e.g., 802.11n/ac) that introduce new features and also increase the different possible settings for each feature. Inherent channel variations and the possible interference conditions when operating in unlicensed spectrum necessitate adaptation of the various medium access control (MAC) and physical (PHY) layer features to ensure high performance. Selecting the values of those features to optimise a criterion such as throughput is the link adaptation problem. Link adaptation, the focus of this thesis, can play a key role in improving the performance of 802.11 WLANs. Increasing number of features and feature setting combinations with newer 802.11 standards is not only making link adaptation even more important but also more challenging. The contributions made in this thesis significantly advance the state of the art on link adaptation for 802.11 WLANs along three dimensions. First, we show that not knowing the exact cause of loss is not an impediment to effective link adaptation. Nevertheless, actions taken in response to losses are more crucial and they ought to be holistic and not solely dependent on the exact cause of loss. Second, we make significant methodological contributions for analysing the impact of multiple parameters on a given criterion, based on comprehensive experimental measurements. The application of this methodology on 802.11n measurements, examining the interaction of the protocols various parameters on performance under varying conditions, has lead to several valuable findings on how to perform efficient link adaptation in a complex WLAN scenario like 802.11n and future 802.11 standards. Adaptation should be holistic, based on the channel quality instead of the interference scenario, and independent of loss differentiation. Based on these insights, lastly and most importantly, we propose two novel holistic link adaptation schemes for legacy 802.11a/b/g and 802.11n WLANs, termed Themis and SampleLite, respectively. Both Themis and SampleLite take a hybrid approach relying on easily accessed channel quality information at the sender side to perform holistic adaptation. The hypothesis that adaptation should be holistic is validated by our results, with both Themis and SampleLite outperforming the current state of the art.

Wireless networks enter a new era in which various objects, such as mobile phones, computers, vehicles, watches, are automatically and intelligently connected to provide ubiquitous services. Green communication protocols are required to save energy consumption and improve transmission performance. MAC protocols can detect the signal status and energy consumptions of physical channels to adapt to the dynamic wireless conditions. They can also provide node-to-node transmissions for network layer protocols under green wireless networks. The thesis presents three energy efficient communication solutions under different delay-tolerant networks scenarios to study the efficiency of MAC transmission protocols within wireless networks: CPMAC, AFLAS and TREE. CPMAC applies three energy-aware algorithms to transmit different quality requirements of data within one contact interval in sparsely connected sensor networks. Simulations and analysis shows CPMAC outperforms two other important MAC protocols in wireless sensor networks and vehicular ad-hoc networks in throughput, delay, energy consumption. AFLAS uses an adaptive frame length aggregation scheme for Vehicular Networks that is designed to improve transmission efficiency and increase data throughput. Suitable aggregation frame lengths are calculated according to the current wireless status, and applied in the MAC layer at the onset of data transmissions to save overhead and energy consumption. The simulations of AFLAS exhibit a significant improvement results in data throughput, retransmissions, overheads and transmission efficiency in comparison to non-adaptive aggregation schemes. TRaffic adaptive Energy Efficient MAC protocol (TREE) adapts its work modes: reservation and contention mode, to traffic density and adjusts its duty cycle to achieve energy efficiency. TREE demonstrates better performance in terms of energy efficiency and traffic adaptability than the schedule-based MAC protocol TDMA, the contention-based protocol CSMA and the traffic adaptive protocol TRAMA under mobile sensor network environments. By studying and designing MAC protocols in wireless environments, the thesis shows the comprehensive knowledge and principles of communication protocol designs with latency relaxed. Future work is discussed for further designs and implementations of green communication protocols.