In a multiuser system, several signals are transmitted simultaneously within the same frequency band. This can result in significant improvements both in spectral efficiency and system capacity. However, a detrimental effect of the shared transmissions (both in time and bandwidth), is that the signal received at the base station (BS) or access point (AP) suffers from cochannel interference (CCI) and inter-symbol interference (ISI). This situation presents challenges to receiver design. To combat the destructive nature of multipath fading, a receiver often employs multiple antennas to collect the faded superimposed versions of the transmitted signals. The multiple signals are combined and processed in such a way that the effects of CCI and ISI are minimized and the desired information is reliably recovered. The situation is even more challenging when the system is operating under overload, i.e. when there are fewer receive antennas than there are transmitted signals. Multiuser detection (MUD) is used to simultaneously estimate the information sent by the transmitters. To do this, the receiver exploits differences among the cochannel signals (through unique spatial signatures in this case). We consider a cochannel communication system where multiple transmitted signals arrive at a receiver (equipped with multiple receive antennas) after propagating through a Rayleigh fading channel. It is assumed that the receiver is operating in an overloaded scenario. For such systems, an optimum maximum a posterior probability (MAP) detector estimates the transmitted signal by maximizing the probability of correct decision. The MAP detector reduces to the maximum likelihood (ML) detector when all the transmitted signals are equiprobable. The computational complexity of both MAP and ML detectors increases exponentially with the number of transmitted signals and the channel memory. For large systems suffering severe CCI and ISI, this is clearly not a good choice for real-time implementation due to the associated computational expenses. The main factors that influence the complexity of MAP / ML detection are: (i) the number of transmitted signals (or equivalently the number of users sharing the system resources), (ii) modulation alphabet size, and (iii) length of the channel memory. On the other hand, linear detection approaches fail to offer acceptable performance while other nonlinear sub-optimum approaches incur high computational costs for reasonably improved system performance and exhibit an irreducible error-floor at medium to high signal to noise ratio (SNR) values. We develop receiver signal processing techniques for the frequency-flat fading channel (where all the multipaths of the transmitted signal arrive at the receiver within a symbol period). We develop an ant colony optimization (ACO) assisted soft iterative detection approach for binary phase-shift keying (BPSK) modulated signals which employs a simplified MAP criteria to extract the most probable signals from the search space. The structure of the receiver is such that it can continue operating under overloaded conditions. The technique achieves near maximum likelihood (ML) performance in critically loaded cases using much lower complexity. For the challenging case of overload it still offers performance close to ML at low to moderate SNR values. Second, an integrated framework comprising of ACO metaheuristic and a recursively defined ML search criteria is developed to handle multilevel modulations. The proposed receiver is capable of achieving near-ML performance for the considered system with significant savings in computational complexity. The receiver framework is independent of the system loading condition, and therefore it remains suitable for overloaded scenarios. Due to the branch and bound nature of the algorithm, an exact expression for the complexity cannot be determined. Instead, an upper bound on computational complexity is developed.

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With the rapid development of wireless networks, mesh networks are evolving as a new important technology, presenting a high research and commercial interest. Additionally, wireless mesh networks have a wide variety of applications, offering the ability to provide network access in both rural and urban areas with low cost of maintenance. One of the main functionalities of a wireless mesh network is load balancing routing, which is the procedure of finding the best, according to some criteria, routes that data need to follow to transfer from one node to another. Routing is one of the state-of-the-art areas of research because the current algorithms and protocols are not efficient and effective due to the diversity of the characteristics of these networks. In this thesis, two new routing algorithms have been developed for No Intra-Cell Interference (NICI) and Limited Intra-Cell Interference (LICI) networks based on WiMAX, the most advanced wireless technology ready for deployment. The algorithms created are based on the classical Dijkstra and Ford-Fulkerson algorithms and can be implemented in the cases of unicast and multicast transmission respectively.

Shingled Magnetic Recording (SMR) has been recognised as one of the alternative technologies to achieve an areal density beyond the limit of the perpendicular recording technique, 1 Tb/in2, which has an advantage of extending the use of the conventional method media and read/write head. This work presents SMR system subject to both Inter Symbol Interference (ISI) and Inter Track Interference (ITI) and investigates different equalisation/detection techniques in order to reduce the complexity of this system. To investigate the ITI in shingled systems, one-track one-head system model has been extended into two-track one-head system model to have two interfering tracks. Consequently, six novel decoding techniques have been applied to the new system in order to find the Maximum Likelihood (ML) sequence. The decoding complexity of the six techniques has been investigated and then measured. The results show that the complexity is reduced by more than three times with 0.5 dB loss in performance. To measure this complexity practically, perpendicular recording system has been implemented in hardware. Hardware architectures are designed for that system with successful Quartus II fitter which are: Perpendicular Magnetic Recording (PMR) channel, digital filter equaliser with and without Additive White Gaussian Noise (AWGN) and ideal channel architectures. Two different hardware designs are implemented for Viterbi Algorithm (VA), however, Quartus II fitter for both of them was unsuccessful. It is found that, Simulink/Digital Signal Processing (DSP) Builder based designs are not efficient for complex algorithms and the eligible solution for such designs is writing Hardware Description Language (HDL) codes for those algorithms.

The new released 4G standard wireless communication reminds us that higher transmission data rate and more reliable service are required urgently. However, to fulfill the demand can face problems in a complex environment like mines. In this thesis, characterization of underground tunnel mines with the idea of combating intersymbol interference effect is presented.            Ray tracing simulation method is applied to characterize channel impulse response in different positions of an underground tunnel. From this channel impulse response, we can obtain how intersymbol interference affects different wireless systems. Intersymbol interference occurs due to multipath propagation of time dispersion channel.           Adaptive Equalization is the most effective way to compensate intersymbol interference. Adaptive filter adapts filter coefficients to compensate the channel so that the combination of the filter and channel offers a flat frequency response and linear phase. The bit error rate performance without using adaptive equalization is compared with using equalizer. Moreover, adaptive equalization approaches using RLS and LMS algorithms are compared with each other. The tradeoff between convergence rate, computation cost instability and ensemble averaged minimum squared errors are analyzed to determine how to select the optimum adaptive equalizer.

The first objective of this thesis is to investigate the effect of several forms of electronic attack (EA) on the radio frequency (RF) sensors used within a boost-phase ballistic missile intercept system. The EA types examined include noise jamming, chaff, radar cross section (RCS) reduction, and expendable decoys. Effects of the EA methods are evaluated by examining the track position error at the sensor fusion output. Sensor fusion architectures investigated include a weighted average sensor fusion; Kalman-filter-based sensor fusion, and joint probabilistic data fusion architecture. A second objective of this thesis is to extend the single-target, single-interceptor analysis and simulation to a multi-target, multi-interceptor scenario to include the formation of an ellipsoidal gating process to correctly correlate the target measurements with the corresponding track file. We show that the most effective EA is the use of noise jamming followed by a RCS reduction of the missile body. We also show that a properly designed sensor fusion process can effectively mitigate the EA techniques that might be used in a boostphase intercept scenario.

Many military communications systems utilize frequency-hopped spread spectrum waveforms to protect against jamming and enemy detection. These waveforms may be subjected not only to intentional jamming but may also be unintentionally jammed by other communications signals. While some systems can overcome inband interference with more signal power, covert systems may be limited to small amounts of transmitted power. The objective of this thesis was to investigate a method for resolving a frequency-hopped signal embedded in interference waveforms. With exponential averaging in the frequency domain, the spectra of the interfering signals can be estimated as long as they are present over a period longer than that of the frequency-hopped signal. Certain FFT sizes and weights are more beneficial to achieving this estimate than others. The interference estimate can be used to extract the desired frequency-hopped signal through spectral division of the received signal with the estimate. This technique is designated as noise-normalization. Simulations in MATLAB demonstrate the use of the technique and show how the desired signal can be resolved.

The dispersion and mixing of passive scalars released from two concentrated sources into open-channel and homogeneous isotropic turbulent flows are studied using direct numerical simulation (DNS). The simulations are conducted using two fully-parallelized in-house codes developed using the FORTRAN 90/95 programming language. A comparative study has been conducted to investigate the effects of the source separation distance, Reynolds number, relative length scales of the plume and turbulent flow, and source elevation on the dispersion and mixing of two plumes. For both flow configurations, four distinct stages in the downwind development of the cross correlation between the fluctuating concentration fields have been identified which feature zero, destructive and constructive interferences and a complete mixing state. Differences between the exceedance probability of concentrations for the single and total plumes are highlighted and analyzed, and the effects of destructive and constructive interference on the exceedance probabilities for the total plume are used to explain these differences. It is found that the relationship between the third- and fourth-order concentration moments and the second-order concentration moment can be well predicted using a clipped-gamma model. This leads to an interesting conclusion that all the higher-order (third-order and above) moments of the total concentration can be inferred from a knowledge of only the first- and second-order concentration moments of each single plume and of the cross correlation coefficient. From a spectral analysis, it is observed that there exists a range of `leading scales' at which the rate of turbulent mixing of the two plumes becomes the most efficient and the coherency spectrum of the plumes approaches the asymptotic value of unity quicker than at any other scales. / October 2016

Given a set P of n points in R^d, we consider the k-connected interference minimization problem, in which the objective is to assign a transmission radius to each node in P such that the resulting network is k-connected and the maximum interference is minimized. We show for any n and any 1 <= k < n, Omega(sqrt(kn)) and Omega(k log n) are lower bounds on the worst-case minimum maximum interference in the symmetric and asymmetric models, respectively. In the symmetric case, we present polynomial-time algorithms that build a k-connected network on any given set of n nodes with interference O(sqrt(kn)) in one dimension and O(min{k sqrt(n), k log lambda}) in two dimensions, where lambda denotes the ratio of the longest to shortest distances between any pair of nodes. In the asymmetric case, we present a polynomial-time algorithm that builds a strongly k-connected network with maximum interference O(k log lambda) in two dimensions. / October 2016

In this thesis, a discrete Markov chain model for analyzing memory interference in multiprocessors, is presented.