Security and trust are two interdependent concepts and are often used interchangeably when defining a secure wireless sensor network (WSN) system. However, security is different from trust in that, it assumes no node is trustworthy and requires ongoing authentication using sophisticated protocols leading to high communication and computation overheads. This makes the traditional cryptographic security tools hard, if not impossible, to be used in wireless sensor networks that are severely resource constrained. Trust on the other hand is the exact opposite of security in that any node can interact with any other and requires no authentication and unwrapping of hidden keys to carry on with their business and hence carries zero overhead. However, this leads to the miss-use and abuse of networks causing loss and damage to the owners of the networks. This thesis focuses on developing novel methods for modelling and managing trust that enable WSN to be secure while significantly reducing computing and communication overheads. Although researchers have been studying the problem of trust modelling and management in wireless sensor networks for over a decade, their focus was on the trust associated with routing messages between nodes (communication trust). However, wireless sensor networks are mainly deployed to sense the world and report data, both continuous and discrete. However, there are no methods in the literature that focus on the trust associated with misreporting data (data trust). In this thesis, we model the trust associated with the integrity of the data, and propose methods to combine the data trust with the communication trust to infer the total trust. Bayesian probabilistic approach is used to model and manage trust. A new risk assessment algorithm for establishing trust in wireless sensor networks based on the quality of services characteristics of sensor nodes, using the traditional weighting approach is introduced. Then a Beta distribution is used to model communication trust (due to its binary nature) and determine the weights in terms of the Beta distribution parameters to probabilistically combine direct and indirect trust. The thesis extends the Bayesian probabilistic approach to model data trust for cases when the sensed data is continuous. It introduces the Gaussian trust and reputation system to that accounts for uncertain characteristics of sensor data. Finally we introduce a Bayesian fusion algorithm to combine the data trust and communication trust to infer the overall trust between nodes. Simulation results are presented to demonstrate how the models accurately classify different nodes as being trustworthy or not based on their reliability in sensor reporting and routing functions.

Due to the enormous capacity and performance gains associated with the use of antenna arrays in wireless multi-input multi-output (MIMO) communication links, it is inevitable that these technologies will become an integral part of future systems. In order to assess the potential of such beam-oriented technologies, direct representation of the dispersion of multipath fading channel in angular and temporal domains is required. This representation can only be achieved with the use of spatial channel models. This thesis thus focuses on the issue of spatial channel modeling for cellular systems and on its use in the characteri- zation of multipath fading channels. The results of this thesis are presented mainly in five parts: a) modeling of scattering mechanisms, b) derivation of the closed-form expressions for the spatio-temporal characteristics, c) generalization of the quantitative measure of angular spread, d) investigation of the effect of mobile motion on the spatio-temporal characteris- tics, and e) characterization of fast fading channel and its use in the signature sequence adaptation for direct sequence code division multiple access (DS-CDMA) system. The thesis begins with an overview of the fundamentals of spatial channel modeling with regards to the specifics of cellular environments. Previous modeling approaches are dis- cussed intensively and a generalized spatial channel model, the 'Eccentro-Scattering Model' is proposed. Using this model, closed-form mathematical expressions for the distributions of angle and time of multipath arrival are derived. These theoretical results for the picocell, microcell and macrocell environments, when compared with previous models and available measurements, are found to be realistic and generic. In macrocell environment, the model incorporates the effect of distant scattering structures in addition to the local ones. Since the angular spread is a key factor of the second order statistics of fading processes in wireless communications, the thesis proposes a novel generalized method of quantifying the angular spread of the multipath power distribution. The proposed method provides almost all parameters about the angular spread, which can be further used for calculating more accurate spatial correlations and other statistics of multipath fading channels. The degree of accuracy in such correlation calculations can lead to the computation of exact separation distances among array elements required for maximizing capacity in MIMO systems or diversity antennas. The proposed method is also helpful in finding the exact standard deviation of the truncated angular distributions and angular data acquired in measurement campaigns. This thesis also indicates the significance of the effects of angular distribution truncation on the angular spread. Due to the importance of angular spread in the fading statistics, it is proposed as the goodness-of-fit measure in measurement campaigns. In this regard, comparisons of some notable azimuthal models with the measurement results are shown. The effect of mobile motion on the spatial and temporal characteristics of the channel is also discussed. Three mobile motion scenarios are presented, which can be considered to be responsible for the variations of the spatio-temporal statistical parameters of the multipath signals. Two different cases are also identified, when the terrain and clutter of the mobile surroundings have an additional effect on the temporal spread of the channel during mobile motion. The effect of increasing mobile-base separation on the angular and temporal spreads is elaborated in detail. The proposed theoretical results in spatial characteristics can be extended to characterizing and tracking transient behavior of Doppler spread in time-varying fast fading channels; likewise the proposed theoretical results in temporal characteristics can be utilized in designing efficient equalizers for combating inter-symbol interference (ISI) in time-varying frequency-selective fading channels. In the last part of the thesis, a linear state-space model is developed for signature sequence adaptation over time-varying fast fading channels in DS-CDMA systems. A decision directed adaptive algorithm, based on the proposed state-space model and Kalman filter, is presented. The algorithm outperforms the gradient-based algorithms in tracking the received distorted signature sequence over time-varying fast fading channels. Simulation results are presented which show that the performance of a linear adaptive receiver can be improved significantly with signature tracking on high Doppler spreads in DS-CDMA systems.

Telecommunication has experienced significant changes over the past few years and its paradigm has moved from wired to wireless communications. The wireless channel constitutes the basic physical link between the transmitter and the receiver antennas. Therefore, complete knowledge of the wireless channel and radio propagation environment is necessary in order to design efficient wireless communication systems. This PhD thesis is devoted to studying the spatial and temporal statistics of the wireless channel in cellular environments based on a geometry-based stochastic physical channel modeling approach. Contributions in this thesis report include the following: ??? A new physical channel model called the eccentro-scattering model is proposed to study the spatial and temporal statistics of the multipath signals in cellular environments. ??? Generic closed-form formulas for the probability density function (pdf) of angle of arrival (AoA) and time of arrival (ToA) of the multipath signals in each cellular environment are derived. These formulas can be helpful for the design and evaluation of modern communication systems. ??? A new Gaussian scattering model is proposed, which consists of two Gaussian functions for the distribution of scatterers around base station (BS) and mobile station (MS) and confines these scatterers within a scattering disc. ??? The effect of mobile motion on the spatial and temporal statistics of the multipath signals in cellular environments is discussed. Three motion scenarios are considered for the possible trajectory of the mobile unit. Furthermore, two different cases are identified when the terrain and clutter of mobile surrounding have additional effect on the temporal spread of the multipath signals during motion. ??? The physical channel model is employed to assess the performance of a RAKE receiver in cellular environments. ??? Comparisons between uniform scattering and Gaussian scattering, which are the two assumptions for the distribution of scatterers usually used in the derivation of the pdf of AoA, are also presented. ??? An overview of earlier physical channel models and comparisons between these models and with the proposed model are presented.

Cooperative communication has been considered a promising technique used in wireless network to introduce diversity. Based on distributed architecture, cooperative network enables single-antenna users to share their information as a virtual multiple antenna array, which makes it possible to enhance the user data rates and obtain the diversity gain. Depending on the ways users share and process the information, practical user cooperation is mainly grouped in three modes: Amplify and Forward (AF), Decode and Forward (DF) and Compress and Forward (CF). Generally, DF outperforms AF in most practical implementation and is alternately the best by theoretical analysis. In particular, it is shown in theory that DF outperforms CF when the inter-user link is in good condition and vice versa. Considered as a capacity achieving approach, superposition encoding technique produces approximate Gaussian output signals. It is the power and spectral efficiency of the encoding scheme that make it useful for several wireless communication systems such as MIMO system, relay channels, and so on. The main goal of the thesis is to study how much superposition coding can help when applied to DF user cooperation. In particular, a new DF scheme with soft information relaying technique is proposed to overcome the performance degradation happening when the quality of the inter-user channel is bad. Based on the scheme, soft log-likelihood ratio (LLR) of the relay decoder is quantized, encoded, modulated by superimposition and then forwarded to the destination. The destination receiver employs an iterative superposition decoder and modified maximum a posteriori probability (MAP) decoder to recover the transmitted signal from the source. The performance of the scheme is evaluated by simulation. We show that the new scheme can significantly outperform the conventional DF scheme even in a poor inter-user channel. Furthermore, a new cooperative transmission strategy based on superposition and multiuser detection techniques is also investigated in the thesis. The new scheme is an improved DF scheme in which the two users take turns in being the relay for each other and the signal forwarded by each user is the superimposed data of both users. Here, interleavers are introduced in the superposition process as an efficient user separation tool, providing a large improvement in error performance and also facilitating the decoding process at the destination. Different types of iterative receivers are examined. The performance of the scheme is evaluated by simulation. It is shown that the new transmission scheme outperforms the conventional one in terms of both spectral and power efficiency.

With the integration of wireless technologies and multimedia services, transmitting high quality images and video has become one of the main objectives for next generations mobile network systems. Shannon's classic separation theorem states that, under ideal conditions, source coding and channel coding can be treated separately without sacrificing any performance for the whole system. However, this theorem holds true only under ideal conditions. Practical communication systems do not meet such requirements. Therefore, joint source and channel coding may reduce distortion, as well as complexity and delay. In this thesis, different schemes of joint source-channel coding and decoding for error resilient image transmission over noisy channels are examined. Unequal error protection (UEP) is one of the techniques used in joint source and channel coding. A JPEG image is partitioned into DC components and AC components according to their respective sensitivity to channel noise. The highly sensitive DC components are better protected with a low coding rate, while the less sensitive AC components use a high coding rate. Simulation results show that the proposed UEP scheme slightly outperforms conventional equal error protection (EEP). A novel turbo diversity scheme (TDS) applied to JPEG coded images is proposed. Turbo codes have a built-in structure that is suitable for diversity techniques used to improve the quality of communications over a multi-path channel. The same image data is encoded by two separate turbo encoders and sent over two independent channels. The received data is then passed to a single turbo decoder. By utilising the built-in structure of the turbo encoder, the transmitted JPEG data encoded by a rate half code is recovered at the receiver using a more powerful rate third code yielded by the TDS. An iterative source-channel decoding scheme applied to JPEG coded images is investigated. Huffman codes used as the variable-length coding scheme in JPEG coding can be represented by an irregular VLC-trellis structure. State transition probabilities can be derived from the irregular trellis and can be used as a priori information to help iterative decoding between source and channel a posteriori probability (APP) decoders. Iterative decoding of JPEG coded images only gives a small coding gain due to the poor distance property of the original JPEG Huffman codes. We propose to replace the Huffman codes used in JPEG coding with error resilient source codes with larger free distance. After accounting for the penalty due to the increased average codeword length, the new scheme achieves a 4 dB coding gain over the conventional system for a range of SNRs. While the focus of this thesis is on joint source-channel coding, two other related topics are also examined, namely, capacity and normalisation of intersymbol interference (ISI) channels and parallel data convolutional codes. Previously published results showed a minimum Eb/N0 of -4.6 dB, 3 dB below the capacity of a flat channel, is obtained using the water-pouring capacity formulas for the 1+D channel. However, these results did not take into account that the channel power gain can be greater than unity when water-pouring is used. We present a new generic power normalization method of ISI channel frequency spectra, namely peak bandwidth normalisation, to facilitate the fair capacity comparison of various ISI channels. A final contribution presented in this thesis regards the proposed parallel data convolutional codes (PDCCs). The encoder inputs consist of the original block of data and its interleaved version. We propose a novel single self-iterative soft-input/soft-output (SISO) decoder structure for the decoding of PDCC. It has the advantage of needing only one APP decoder. Although the performance is not very encouraging, the novelty of the self-iterative idea behind the design is worth exploiting. / thesis (PhDTelecommunications)--University of South Australia, 2003.

This thesis presents the analysis and experimental results for an evaluation of the performance and Quality of Service (QoL) levels of a virtual private network( QoL) levels of a Virtual Private Network (VPN) implementation of an IEEE 802.11b wireless infrastructure. The VPN tunnelling protocol considered for the above study is IP security (IPSec). The main focus of the research is to identify the major performance limitations and their underlying causes for such VPN implementations under study. The experimentation and data collection involved in the study spans over a number of platforms to suit a range of practical VPN implementations over a wireless medium. The collected data includes vital QoS and performance measures such as the application throughput, packet loss, jitter, and round-trip delay. Once the baseline measure is established, a series of experiments are conducted to analyse the behaviour of a single IPSec VPN operating over an IEEE 802.11b infrastructure, after which the experimentation is extended by investigating the trends of the performance metrics of a simultaneously multiple VPN setup. The overall results and analysis of the investigation concludes that the CPU processing power, payload data size, packet generation rate and the geographical distance are critical factors affecting the performance of such VPN tunnel implementations. Furthermore, it is believed that these results may give vital clues for enhancing and achieving optimal performance and QoS levels for VPN applications over WLANs / Master of Science (Hons.)

Wireless spectral efficiency is increasingly important due to the rapid growth of demand for high data rate wideband wireless services. The design of a multi-carrier system,such as an orthogonal frequency division multiple access (OFDMA) system, enables high system capacity suited for these wideband wireless services. This system capacity can be further optimised with a resource allocation scheme by exploiting the characteristics of the wireless fading channels. The fundamental idea of a resource allocation scheme is to efficiently distribute the available wireless resources, such as the sub-carriers and transmission power, among all admitted users in the system. In this thesis, we present the findings of the investigation into the impact of several resource allocation schemes in an OFDMA environment. We show that in an OFDMA environment without the consideration of sub-carrier assignment, the sub-optimal power allocation closed-form solution can be derived via a constrained optimisation with the duality theorem. With a perfect feedback of channel condition, the proposed low-complexity algorithm that utilises the closed-form solution can maximise the sum capacity to approach near-optimal capacity. We derive the sub-optimal sub-carrier and power allocation closed-form solution via a similar constrained optimisation process. With an imperfect or outdated feedback of channel condition, the adaptive sub-carrier and power allocation scheme not only fails to improve but also further deteriorates the system throughput. We present and discuss the formation of the finite-state Markov channel. We show that by using the dynamics of the Markov channel, the channel quality can be reliably predicted in advance. We analyse via simulation the spectral efficiency achieved by this channel prediction scheme on an OFDMA system. We address the importance of fairness in resource allocation from a game-theoretic perspective. With different utility and preference functions that best describe the gain in users’ throughput as more sub-carriers are allocated to the individual user, we formulate the resource allocation problem into cooperative and non-cooperative games. We study via simulation the effectiveness and fairness of the cooperative and non-cooperative resource allocation schemes on an OFDMA system. Finally, we draw conclusions on our research work and outline the future research topics in connection with our current studies. / Thesis(PhD) -- School of Electrical and Electronic Engineering, 2007

Security and trust are two interdependent concepts and are often used interchangeably when defining a secure wireless sensor network (WSN) system. However, security is different from trust in that, it assumes no node is trustworthy and requires ongoing authentication using sophisticated protocols leading to high communication and computation overheads. This makes the traditional cryptographic security tools hard, if not impossible, to be used in wireless sensor networks that are severely resource constrained. Trust on the other hand is the exact opposite of security in that any node can interact with any other and requires no authentication and unwrapping of hidden keys to carry on with their business and hence carries zero overhead. However, this leads to the miss-use and abuse of networks causing loss and damage to the owners of the networks. This thesis focuses on developing novel methods for modelling and managing trust that enable WSN to be secure while significantly reducing computing and communication overheads. Although researchers have been studying the problem of trust modelling and management in wireless sensor networks for over a decade, their focus was on the trust associated with routing messages between nodes (communication trust). However, wireless sensor networks are mainly deployed to sense the world and report data, both continuous and discrete. However, there are no methods in the literature that focus on the trust associated with misreporting data (data trust). In this thesis, we model the trust associated with the integrity of the data, and propose methods to combine the data trust with the communication trust to infer the total trust. Bayesian probabilistic approach is used to model and manage trust. A new risk assessment algorithm for establishing trust in wireless sensor networks based on the quality of services characteristics of sensor nodes, using the traditional weighting approach is introduced. Then a Beta distribution is used to model communication trust (due to its binary nature) and determine the weights in terms of the Beta distribution parameters to probabilistically combine direct and indirect trust. The thesis extends the Bayesian probabilistic approach to model data trust for cases when the sensed data is continuous. It introduces the Gaussian trust and reputation system to that accounts for uncertain characteristics of sensor data. Finally we introduce a Bayesian fusion algorithm to combine the data trust and communication trust to infer the overall trust between nodes. Simulation results are presented to demonstrate how the models accurately classify different nodes as being trustworthy or not based on their reliability in sensor reporting and routing functions.

Thesis (M. Phil.)--University of Hong Kong, 2007. / Title proper from title frame. Also available in printed format.

Thesis (Ph. D.)--University of Hong Kong, 2007. / Title proper from title frame. Also available in printed format.