Wireless Underground Sensor Networks (WUSNs) are the networks of wireless sensors that operate below the ground surface. These sensors are either buried completely in soil medium, or placed within a bounded open underground space, such as underground mines and tunnels. WUSNs enable a wide variety of novel applications, including intelligent irrigation, underground structure monitoring, and border patrol and intruder detection. This thesis is concerned with establishing reliable and efficient communications in the network of wireless sensor nodes that are deployed in either soil medium or underground mines and tunnels. In particular, to realize WUSNs in soil medium, two types of signal propagation techniques including Electromagnetic (EM) waves and Magnetic Induction (MI) are explored. For EM wave-based WUSNs, the heterogeneous network architecture and dynamic connectivity are investigated based on a comprehensive channel model in soil medium. Then a spatio-temporal correlation-based data collection schemes is developed to reduce the sensor density while keeping high monitoring accuracy. For MI-based WUSNs, the MI channel is first analytically characterized. Then based on the MI channel model, the MI waveguide technique is developed in order to enlarge the underground transmission range. Finally, the optimal deployment algorithms for MI waveguides in WUSNs are analyzed to construct the WUSNs with high reliability and low costs. To realize WUSNs in underground mines and tunnels, a mode-based analytical channel model is first proposed to accurately characterize the signal propagation in both empty and obstructed mines and tunnels. Then the Multiple-Input and Multiple-Output (MIMO) system and cooperative communication system are optimized to establish reliable and efficient communications in underground mines and tunnels.

With the increasing advancements in the digital technology, future wireless systems are promising to support higher data rates, higher mobile speeds, and wider coverage areas, among other features. While further technological developments allow systems to support higher computational complexity, lower power consumption, and employ larger memory units, other resources remain limited. One such resource, which is of great importance to wireless systems, is the available spectrum for radio communications. To be able to support high data rate wireless applications, there is a need for larger bandwidths in the spectrum. Since the spectrum cannot be expanded, studies have been concerned with fully utilizing the available spectrum. One approach to achieve this goal is to reuse the available spectrum through space, time, frequency, and code multiplexing techniques. Another approach is to optimize the transceiver design as to achieve the highest throughput over the used spectrum. From the physical layer perspective, there is a need for a highly flexible and efficient modulation technique to carry the communication signal. A multicarrier modulation technique known as orthogonal frequency division multiplexing (OFDM) is one example of such a technique. OFDM has been used in a number of current wireless standards such as wireless fidelity (WiFi) and worldwide interoperability for microwave access (WiMAX) standards by the Institute of Electrical and Electronics Engineers (IEEE), and has been proposed for future 4G technologies such as the long term evolution (LTE) and LTE-advanced standards by the 3rd Generation Partnership Project (3GPP), and the wireless world initiative new radio (WINNER) standard by the Information society technologies (IST). This is due to OFDM’s high spectral efficiency, resistance to narrow band interference, support for high data rates, adaptivity, and scalability. In this dissertation, OFDM and multiuser OFDM , also known as orthogonal frequency division multiple access (OFDMA), techniques are investigated as a candidate for advanced wireless systems. Features and requirements of future applications are discussed in detail, and OFDM’s ability to satisfy these requirements is investigated. We identify a number of challenges that when addressed can improve the performance and throughput of OFDM-based systems. The challenges are investigated over three stages. In the first stage, minimizing, or avoiding, the interference between multiple OFDMA users as well as adjacent systems is addressed. An efficient algorithm for OFDMA uplink synchronization that maintains the orthogonality between multiple users is proposed. For adjacent channel interference, a new spectrum shaping method is proposed that can reduce the out-of-band radiation of OFDM signals. Both methods increase the utilization of available spectrum and reduce interference between different users. In the second stage, the goal is to maximize the system throughput for a given available bandwidth. The OFDM system performance is considered under practical channel conditions, and the corresponding bit error rate (BER) expressions are derived. Based on these results, the optimum pilot insertion rate is investigated. In addition, a new pilot pattern that improves the system ability to estimate and equalize various radio frequency (RF) impairments is proposed. In the last stage, acquiring reliable measurements regarding the received signal is addressed. Error vector magnitude (EVM) is a common performance metric that is being used in many of today’s standards and measurement devices. Inferring the signal-to-noise ratio (SNR) from EVM measurements has been investigated for either high SNR values or data-aided systems. We show that using current methods does not yield reliable estimates of the SNR under other conditions. Thus, we consider the relation between EVM and SNR for nondata-aided systems. We provide expressions that allow for accurate SNR estimation under various practical channel conditions.

D. Tech. Electrical Engineering. / Objectives of the study is to propose a suitable feature extraction and classication approach that is capable of adapting to the non-linear nature and the noise contained in the time series data. The end goal of subscriber classication in this study is to utilise the subscriber information extracted for a new radio resource optimisation model that focuses on the Channel Allocation Problem CAP. Although there they have been various models proposed in literature for solving of the CAP problem, the utilisation of subscriber related information in the CAP has not been directly considered.

Interference is a defining feature of a wireless network. How to optimally deal with it is one of the most critical and least understood aspects of decentralized multiuser communication. This dissertation focuses on distributed transmission strategies that a transmitter can follow to achieve reliability while reducing the impact of interference. The problem is investigated from three directions : distributed opportunistic scheduling, multicast outage and transmission capacity, and ergodic transmission capacity, which study distributed transmission in different scenarios from a transmission-capacity perspective. Transmission capacity is spatial throughput metric in a large-scale wireless network with outage constraints. To understand the fundamental limits of distributed transmission, these three directions are investigated from the underlying tradeoffs in different transmission scenarios. All analytic results regarding the three directions are rigorously derived and proved under the framework of transmission capacity. For the first direction, three distributed opportunistic scheduling schemes -- distributed channel-aware, interferer-aware and interferer-channel-aware scheduling are proposed. The main idea of the three schemes is to avoid transmitting in a deep fading and/or sever interfering context. Theoretical analysis and simulations show that the three schemes are able to achieve high transmission capacity and reliability. The second direction focuses on the study of the transmission capacity problem in a distributed multicast transmission scenario. Multicast transmission, wherein the same packet must be delivered to multiple receivers, has several distinctive traits as opposed to more commonly studied unicast transmission. The general expression for the scaling law of multicast transmission capacity is found and it can provide some insight on how to do distributed single-hop and multi-hop retransmissions. In the third direction, the transmission capacity problem is investigated for Markovain fading channels with temporal and spatial ergodicity. The scaling law of the ergodic transmission capacity is derived and it can indicate a long-term distributed transmission and interference management policy for enhancing transmission capacity. / text

In a multihop cellular network, mobile terminals have the capability to transmit directly to other mobile terminals enabling them to use other terminals as relays to forward traffic towards the base station. Previous studies of networks consisting of a single cell found that the SINR in a multihop cellular network is slightly lower than in a traditional cellular network. However, multihop cellular networks may have a higher capacity than traditional cellular networks due to their potential for lower intercell interference. For this reason, the effects of intercell interference are investigated in this thesis. Our simulations of a network with many cells show that multihop cellular networks have a higher SINR than traditional cellular networks due to the near elimination of intercell interference. However, multihop cellular networks still suffer from large amounts of interference surrounding the base station because all traffic either emanates or is destined to the base station making it the capacity bottleneck. To resolve this problem, we propose a novel architecture called the autonomous infrastructure multihop cellular network where users can connect their mobile terminals to the backbone network giving them the functionality of an access point. Access points receive traffic from other terminals and send it directly onto the backbone, as would a base station. This reduces the traffic handled by the base station and increases network capacity. Our analysis and simulations show that in autonomous infrastructure multihop cellular networks, the SINR at the base station is higher, the power consumption is lower and the coverage is better than in normal multihop cellular networks. Access points require parameters like their transmission range to be adjusted autonomously to optimal levels. In this thesis, we propose an autonomous pilot power protocol. Our results show that by adjusting a parameter within the protocol, a required coverage level of terminals can be specified and achieved without knowledge of the location or density of mobile terminals. Furthermore, we show that the protocol determines the transmission range that is optimal in terms of SINR and power consumption that achieves the required coverage while effectively eliminating the bottleneck that existed at the base station.

In a multihop cellular network, mobile terminals have the capability to transmit directly to other mobile terminals enabling them to use other terminals as relays to forward traffic towards the base station. Previous studies of networks consisting of a single cell found that the SINR in a multihop cellular network is slightly lower than in a traditional cellular network. However, multihop cellular networks may have a higher capacity than traditional cellular networks due to their potential for lower intercell interference. For this reason, the effects of intercell interference are investigated in this thesis. Our simulations of a network with many cells show that multihop cellular networks have a higher SINR than traditional cellular networks due to the near elimination of intercell interference. However, multihop cellular networks still suffer from large amounts of interference surrounding the base station because all traffic either emanates or is destined to the base station making it the capacity bottleneck. To resolve this problem, we propose a novel architecture called the autonomous infrastructure multihop cellular network where users can connect their mobile terminals to the backbone network giving them the functionality of an access point. Access points receive traffic from other terminals and send it directly onto the backbone, as would a base station. This reduces the traffic handled by the base station and increases network capacity. Our analysis and simulations show that in autonomous infrastructure multihop cellular networks, the SINR at the base station is higher, the power consumption is lower and the coverage is better than in normal multihop cellular networks. Access points require parameters like their transmission range to be adjusted autonomously to optimal levels. In this thesis, we propose an autonomous pilot power protocol. Our results show that by adjusting a parameter within the protocol, a required coverage level of terminals can be specified and achieved without knowledge of the location or density of mobile terminals. Furthermore, we show that the protocol determines the transmission range that is optimal in terms of SINR and power consumption that achieves the required coverage while effectively eliminating the bottleneck that existed at the base station.

UWB communication is an attractive technology that has the potential to provide low-power, low-complexity, and high-speed communications in short range links. One of the main challenges of the UWB communications is the highly frequency-selective channel, which induces hundreds of overlapped copies of the transmitted pulse with different delays and amplitudes. To collect the energy of these multipath components, coherent Rake receivers are proposed, but suffer from high implementation and computational costs on channel estimation. To avoid the stringent channel estimation, several noncoherent receivers, including energy detector (ED) and transmitted reference (TR), are proposed at the cost of degraded performance. In addition, when taking into account practical issues of UWB communications, e.g., non-Gaussian impulsive noise, non-ideal antennas, and limited, significant performance degradation may be introduced by noncoherent receivers. In this dissertation, we will present low-complexity, high-performance, noncoherent receiver designs for UWB communications that i) avoid the stringent channel estimation; ii) lower the computational complexity of the existing receivers with the aid of advanced digital signal processing techniques; and iii) improve the error performance of the noncoherent receivers by accommodating practical imperfections. First, we propose three multi-symbol detectors (MSDs) for multi-symbol different detection (MSDD), which has recently caught attention in UWB communications because of its high performance without requiring explicit channel estimation. To alleviate the non-deterministic polynomial hardness (NP-hard) of MSDD, we analyze the statistical model of MSDD and propose an iterative MSD and two MSDs based on relaxation technique with near-optimal performance and low complexity. Moreover, the error performance of MSDs is further enhanced by exploiting joint soft-input soft-output MSDD and forward error correction codes. Next, we consider the non-Gaussian noise in the presence of multi-access interference, which is impulsive when the number of active users is small. To mitigate the impulsive noise effect, in this dissertation, we propose new differential UWB receivers based on the generalized Gaussian distribution and Laplace distribution and achieve better error performance. Another main issue of UWB communications is the limited radio coverage. To extend the coverage and improve the performance of UWB systems, we focus on a novel differentially encoded decode-and-forward (DF) non-cooperative relaying scheme. Putting emphasis on the general case of multi-hop relaying, we illustrate a novel algorithm for the joint power allocation and path selection (JPAPS), minimizing an approximate of the overall bit error rate (BER). A simplified scheme is also presented, which reduces the complexity to O(N²) and achieves a negligible performance loss. Finally, we concentrate on code-multiplexing (CM) systems, which have recently drawn attention mainly because they enable noncoherent detection without requiring either a delay component, as in TR, or an analog carrier, as in frequency-shifted reference. In this dissertation, we propose a generalized code-multiplexing (GCM) system based on the formulation of a constrained mixed-integer optimization problem. The GCM extends the concept of existing CM while retaining their simple receiver structure, even offering better BER performance and a higher data rate in the sense that more data symbols can be embedded in each transmitted block. Moreover, the impacts of non-ideal antennas on the GCM systems are investigated given some practical antenna measurement data and IEEE 802.15.4a channel environments.

Modern speech communication technologies expose users to perceptual quality degradations that were not experienced earlier with conventional telephone systems. Since perceived speech quality is a major contributor to the end user's perception of quality of service, speech quality estimation has become an important research field. In this dissertation, perceptual quality estimators are proposed for several emerging speech communication applications, in particular for i) wireless communications with noise suppression capabilities, ii) wireless-VoIP communications, iii) far-field hands-free speech communications, and iv) text-to-speech systems. First, a general-purpose speech quality estimator is proposed based on statistical models of normative speech behaviour and on innovative techniques to detect multiple signal distortions. The estimators do not depend on a clean reference signal hence are termed ``blind." Quality meters are then distributed along the network chain to allow for both quality degradations and quality enhancements to be handled. In order to improve estimation performance for wireless communications, statistical models of noise-suppressed speech are also incorporated. Next, a hybrid signal-and-link-parametric quality estimation paradigm is proposed for emerging wireless-VoIP communications. The algorithm uses VoIP connection parameters to estimate a base quality representative of the packet switching network. Signal-based distortions are then detected and quantified in order to adjust the base quality accordingly. The proposed hybrid methodology is shown to overcome the limitations of existing pure signal-based and pure link parametric algorithms. Temporal dynamics information is then investigated for quality diagnosis for hands-free speech communications. A spectro-temporal signal representation, where speech and reverberation tail components are shown to be separable, is used for blind characterization of room acoustics. In particular, estimators of reverberation time, direct-to-reverberation energy ratio, and reverberant speech quality are developed. Lastly, perceptual quality estimation for text-to-speech systems is addressed. Text- and speaker-independent hidden Markov models, trained on naturally produced speech, are used to capture normative spectral-temporal information. Deviations from the models, computed by means of a log-likelihood measure, are shown to be reliable indicators of multiple quality attributes including naturalness, fluency, and intelligibility. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2008-12-22 14:54:49.28

We investigate the effects of quantized channel state information (CSI) on the performance of resource allocation algorithms in wireless networks. The thesis starts with a brief overview of a specific type of quantizer, referred to as a conservative quantizer where we propose the optimality and sufficiency conditions as well as practical methods to find such quantizers. We apply this theory to the quantization of transmitter CSI in point-to-point Gaussian channels and transmission under short-term power constraints. Next, we show that in a multiple-node decode-and-forward (DF) cooperative network, the same structure for quantizer is close to op- timal for the sum-rate objective function. Based on a proposed upper bound on the rate loss in such scenarios, we also argue that the quantizer should assign uneven numbers of quantization bits to different links in the network. The simulation results show that given a target rate loss level, through quantization and bit allocation, there is, on average, 0.5−1 bits per link savings in CSI feedback requirements compared to the uniform and equal bit allocation approaches. Given the many benefits in non-uniform allocation of CSI rate in the network, we formulate a generalized bit allocation scheme which is extensible to arbitrary classes of network resource allocation problems. In the last part of this thesis, we focus on power control in an interference network and then, investigate the effects of CSI imperfections on the performance of power control algorithms. First, we propose an iterative power control algorithm based on a fixed-point iteration and prove its local convergence. Then, we show that for a centralized implementation of the power control algorithm, a uniform in dB (geometric) quantizer of channel power is efficient. Based on this choice of channel quantizer, we propose a bound on rate loss in terms of the resolution of the ii deployed quantizer, where a 3 dB in quantization error is shown to contribute to a maximum of 1 bit rate loss at each user. Similarly to the previous scenario, the upper bound suggests that an uneven assignment of numbers of quantization levels leads to smaller distortion. Based on this bound, we develop the corresponding bit allocation laws. We also investigate the effects of CSI errors on the performance of distributed power control algorithms and show that, compared to the centralized case, the distributed algorithm could lead to a further SINR loss of up to 3 dB for one or more transmitters. This error is due to the fact that because of CSI errors, the estimated interference level at each receiver is different from the induced interference wireless transmitters expect.

We investigate the effects of quantized channel state information (CSI) on the performance of resource allocation algorithms in wireless networks. The thesis starts with a brief overview of a specific type of quantizer, referred to as a conservative quantizer where we propose the optimality and sufficiency conditions as well as practical methods to find such quantizers. We apply this theory to the quantization of transmitter CSI in point-to-point Gaussian channels and transmission under short-term power constraints. Next, we show that in a multiple-node decode-and-forward (DF) cooperative network, the same structure for quantizer is close to op- timal for the sum-rate objective function. Based on a proposed upper bound on the rate loss in such scenarios, we also argue that the quantizer should assign uneven numbers of quantization bits to different links in the network. The simulation results show that given a target rate loss level, through quantization and bit allocation, there is, on average, 0.5−1 bits per link savings in CSI feedback requirements compared to the uniform and equal bit allocation approaches. Given the many benefits in non-uniform allocation of CSI rate in the network, we formulate a generalized bit allocation scheme which is extensible to arbitrary classes of network resource allocation problems. In the last part of this thesis, we focus on power control in an interference network and then, investigate the effects of CSI imperfections on the performance of power control algorithms. First, we propose an iterative power control algorithm based on a fixed-point iteration and prove its local convergence. Then, we show that for a centralized implementation of the power control algorithm, a uniform in dB (geometric) quantizer of channel power is efficient. Based on this choice of channel quantizer, we propose a bound on rate loss in terms of the resolution of the ii deployed quantizer, where a 3 dB in quantization error is shown to contribute to a maximum of 1 bit rate loss at each user. Similarly to the previous scenario, the upper bound suggests that an uneven assignment of numbers of quantization levels leads to smaller distortion. Based on this bound, we develop the corresponding bit allocation laws. We also investigate the effects of CSI errors on the performance of distributed power control algorithms and show that, compared to the centralized case, the distributed algorithm could lead to a further SINR loss of up to 3 dB for one or more transmitters. This error is due to the fact that because of CSI errors, the estimated interference level at each receiver is different from the induced interference wireless transmitters expect.