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Communication systems have remained almost unchanged since the invention of the superheterodyne receiver in 1918 by the US engineer Edwin Armstrong. With the introduction of multiple-input-multiple-output (MIMO) technologies, Index Modulation appears to be the promising technology to revolutionize the traditional radio-frequency (RF) chain. Index modulation is a high-spectrum, energy-efficient, simple digital communication technique that uses the states of the building blocks of a communication system. In this study, we have focused on the use of radiation patterns scattered by antenna arrays or a metasurface as indices that are encoded as data bits. Initially, we explore sets of 𝑁tx transmitting point source antennas located on the XY plane; we assume that every antenna has phase tunability capability. The phase, the position in space, and the size of the array determine the shape of the far-field radiation pattern. Following the antenna excitation, a set of 𝑁rx receiver antennas spread at specific locations of the spherical space measures the incoming power signal, allowing the sampling of the radiation pattern that is demodulated into information bits.This work is focused on the characterization of the measured radiation patterns under different system and channel variables and their direct effect on the Bit Error Rate.

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In today’s modern society, we are surrounded by a multitude of digital devices.The number of available digital devices is set to grow even more. As the trendcontinues, product life-cycle is a major issue in mass production of these devices.Testing and verification is responsible for a significant percentage of the productioncost of digital devices. Time efficient procedures for testing and characterization aretherefore sought for. Moreover, the need for flexible and low-cost solutions in thedesign architecture of radio frequency devices coupled with the demand for highdata rate has presented a challenge caused by interferences from the analog circuitparts. Study of digital signal processing based techniques which would alleviate theeffects of the analog impairments is therefore a pertinent subject. In the first part of this thesis, we address parameter estimation based on wave-form fitting. We look at the sinewave model for parameter estimation which iseventually used to characterize the performance of a device. The underlying goal isto formulate and analyze a set of new parameter estimators which provide a moreaccurate estimate than well known estimators. Specifically, we study the maximum-likelihood (ML) SNR estimator employing the three-parameter sine fit and derivealternative estimator based on its statistical distribution. We show that the meansquare error (MSE) of the alternative estimators is lower than the MSE of the MLestimator for a small sample size and a few of the new estimators are very close tothe Cramér-Rao lower bound (CRB). Simply put, the number of acquired measure-ment samples translate to measurement time, implying that the fewer the numberof samples required for a given accuracy, the faster the test would be. We alsostudy a sub-sampling approach for frequency estimation problem in a dual channelsinewave model with common frequency. Coprime subsampling technique is usedwhere the signals from both channels are uniformly subsampled with coprime pairof sparse samplers. Such subsampling technique is especially beneficial to lower thesampling frequency required in applications with high bandwidth requirement. TheCRB based on the co-prime subsampled data set is derived and numerical illus-trations are given showing the relation between the cost in performance based onthe mean squared error and the employed coprime factors for a given measurementtime. In the second part of the thesis, we deal with the problem of phase-noise (PHN).First, we look at a scheme in orthogonal frequency-division multiplexing (OFDM)system where pilot subcarriers are employed for joint PHN compensation, channelestimation and symbol detection. We investigate a method where the PHN statis-tics is approximated by a finite number of vectors and design a PHN codebook. Amethod of selecting the element in the codebook that is closest to the current PHNrealization with the corresponding channel estimate is discussed. We present simula-tion results showing improved performance compared to state-of-the art techniques.We also look at a sequential Monte-Carlo based method for combined channel im-pulse response and PHN tracking employing known OFDM symbols. Such techniqueallows time domain compensation of PHN such that simultaneous cancellation ofthe common phase error and reduction of the inter-carrier interference occurs. / <p>QC 20150529</p>

This thesis extensively analyses the performance of an energy detector which is widely employed to perform spectrum sensing in cognitive radio over different generalised channel models. In this analysis, both the average probability of detection and the average area under the receiver operating characteristic curve (AUC) are derived using the probability density function of the received instantaneous signal to noise ratio (SNR). The performance of energy detector over an ŋ --- µ fading, which is used to model the Non-line-of-sight (NLoS) communication scenarios is provided. Then, the behaviour of the energy detector over к --- µ shadowed fading channel, which is a composite of generalized multipath/shadowing fading channel to model the lineof- sight (LoS) communication medium is investigated. The analysis of the energy detector over both ŋ --- µ and к --- µ shadowed fading channels are then extended to include maximal ratio combining (MRC), square law combining (SLC) and square law selection (SLS) with independent and non-identically (i:n:d) diversity branches. To overcome the problem of mathematical intractability in analysing the energy detector over i:n:d composite fading channels with MRC and selection combining (SC), two different unified statistical properties models for the sum and the maximum of mixture gamma (MG) variates are derived. The first model is limited by the value of the shadowing severity index, which should be an integer number and has been employed to study the performance of energy detector over composite α --- µ /gamma fading channel. This channel is proposed to represent the non-linear prorogation environment. On the other side, the second model is general and has been utilised to analyse the behaviour of energy detector over composite ŋ --- µ /gamma fading channel. Finally, a special filter-bank transform which is called slantlet packet transform (SPT) is developed and used to estimate the uncertain noise power. Moreover, signal denoising based on hybrid slantlet transform (HST) is employed to reduce the noise impact on the performance of energy detector. The combined SPT-HST approach improves the detection capability of energy detector with 97% and reduces the total computational complexity by nearly 19% in comparison with previously implemented work using filter-bank transforms. The aforementioned percentages are measured at specific SNR, number of selected samples and levels of signal decomposition.

Ray tracing based on geometric optics can be utilized for generating propagation models for arbitrary and complex environments. These methods can be employed to determine important wireless channel characteristics such as path gain and the channel impulse response which in turn can be used to deduce channel capacity. In this thesis, a fully vectorial 3-D ray-tracer is developed. The simulator is applied to study novel wireless systems such as ultra-wideband pulse propagation in complex railway tunnels and MIMO systems employing closely spaced low mutual coupling meta-material antennas. The computational complexity of the ray-tracing algorithm is reduced using optimizations and via the development of a novel hybrid method that combines the efficiency and accuracy of waveguide models with the flexibility of a ray-tracer. The resulting simulator is validated against measured results and demonstrated to show good agreement. Convergence of the solution using the ray-tracing method is also discussed.

Ray tracing based on geometric optics can be utilized for generating propagation models for arbitrary and complex environments. These methods can be employed to determine important wireless channel characteristics such as path gain and the channel impulse response which in turn can be used to deduce channel capacity. In this thesis, a fully vectorial 3-D ray-tracer is developed. The simulator is applied to study novel wireless systems such as ultra-wideband pulse propagation in complex railway tunnels and MIMO systems employing closely spaced low mutual coupling meta-material antennas. The computational complexity of the ray-tracing algorithm is reduced using optimizations and via the development of a novel hybrid method that combines the efficiency and accuracy of waveguide models with the flexibility of a ray-tracer. The resulting simulator is validated against measured results and demonstrated to show good agreement. Convergence of the solution using the ray-tracing method is also discussed.

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This thesis presents a design and implementation of a long-range communication subsystem for a UAV and a ground control station. The subsystem is a low-cost alternative employing a line of sight, local communication network for optimal communications between a low-altitude UAV and a portable ground control station. In this thesis, real world experiments are conducted to model the time-variant wireless channel between a low-altitude micro-UAV and a portable ground control station operating in an urban environment. The large-scale and small-scale fading coefficients are calculated and analyzed for this dynamic channel. The channel properties, along with the fading distribution parameters, are computed and analyzed for two most popular antenna configurations for UAV systems (Yagi to omnidirectional and omnidirectional to omnidirectional). For the Yagi-to-omnidirectional link, the effects of three major impacting factors i.e. propagation distance, antenna gains in specific spherical angles and polarization mismatch factor on the overall fading distribution is investigated. Through regression analysis, a multiple-regression model is derived that estimates the instantaneous fading parameter, given these channel conditions. For this model, a modified particle-swarm optimization algorithm is designed and implemented to estimate the underlying model coefficients, given the instantaneous fading information. The implementation of this algorithm, along with the regression model, demonstrates that a sufficient approximation of the fading parameter can be provided for any given wireless channel when the impacting factors and instantaneous fading information is available. / February 2016