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Emerging 4G standards, such as WiMAX and LTE have adopted the proven technique of Adaptive Modulation and Coding (AMC) to dynamically react to channel fluctuations while maintaining bit-error rate targets of the transmission. This scheme makes use of the estimated channel state indication (CSI) to efficiently utilize channel capacity for next transmission, but it brings with it the stale CSI problem due to the frequently channel fluctuations. As its objective, this thesis focuses on mitigating the vicious effect of stale CSI by proposing a novel framework that incorporate AMC with layered transmission through Superposition Coding (SPC) is introduced. A layered multi-step finite-state Markov chain model (FSMC) is developed under this framework, to effectively assist the system in selecting the optimal modulation and coding scheme as well as the power allocated for each layer in every multi-resolution unicast transmission. Extensive simulations are conducted to verify the proposed framework and compare its performance with other counterparts. The effects of changing key parameters, such as the complexity factor and step size, are also investigated to get close to real world performance. Results demonstrate that the proposed framework can achieve better spectrum efficiency than similar counterparts, due to its improved robustness to the stale CSI problem for each multi-resolution modulated transmission, also these show that the performance of two-layer scheme is good enough for layer allocation, without need of more layers.

L’OFDM est une technique de modulation multiporteuses largement utilisée dans des applications de communications filaires et sans-fils comme le DVB-T/T2, le Wifi, et la 4G, grâce à sa robustesse contre les canaux sélectifs en fréquence en comparaison avec la modulation monoporteuse. Cependant, le signal OFDM souffre de grandes variations d’amplitude. Les fluctuations de l’enveloppe du signal OFDM génèrent des distorsions non-linéaires quand on introduit le signal dans un équipement non-linéaire comme l’amplificateur de puissance. Réduire les variations du signal améliore le rendement de l’amplificateur, réduit la consommation énergétique et diminue les émissions de CO2 des transmissions numériques.Le PAPR (rapport de la puissance crête sur la puissance moyenne) est une variable aléatoire qui a été introduite pour mesurer les variations du signal. Il existe plusieurs systèmes multiporteuses basés sur différentes bases de modulation et filtres de mise en forme. Nous prouvons d’abord dans ces travaux que le PAPR dépend de cette structure de modulation. Ensuite, nous étudions le comportement du PAPR vis-à-vis des formes d’ondes utilisées dans la modulation. Le problème de réduction du PAPR est ainsi formulé en un problème d’optimisation. Par ailleurs, une condition nécessaire pour construire des formes d’ondes avec un meilleur PAPR que l’OFDM est développée. Cette condition est notamment satisfaite par des bases en ondelettes. Enfin, une nouvelle forme d’onde en paquets d’ondelettes adaptative est proposée, permettant des gains significatifs en PAPR, tout en maintenant les avantages des modulations multiporteuses. / OFDM is a multicarrier modulation system widely used in wireline and wireless applications such as DVB-T/T2, Wifi, and 4G, due to its resilience against frequency selective channels compared with the single carrier modulation systems. However, the OFDM signal suffers from large amplitude variations. The fluctuations of the OFDM envelope generate non-linear distortions when we introduce the signal into a non-linear device like the power amplifier. Reducing the variations of the signal improves the power amplifier efficiency, reduces the energy consumption and decreases CO2 emissions.The peak-to-average power ratio (PAPR) has been introduced as a random variable that measures the power variations of the signal. There exist several multicarrier modulation systems based on different modulation basis and shaping filters. We first prove in this work that the PAPR depends on this modulation structure. Moreover, the behaviour of the PAPR regarding to the modulation waveforms is analysed and the PAPR reduction problem is formulated as an optimization problem. Furthermore, a necessary condition for designing waveforms with better PAPR than OFDM is developed. This necessary condition is particularly satisfied by wavelet basis. Finally, a new adaptive wavelet packet waveform is proposed, allowing significant gain in terms of PAPR, while keeping the advantages of multicarrier modulations.

The detrimental effects rapid power fluctuation has on wireless narrowband communication channels has long been a concern of the mobile radio community as appropriate channel models seek to gauge link quality. Furthermore, advances in signal processing capabilities and the desire for spectrally efficient and low power radio systems have rekindled the interest for adaptive transmission schemes, hence some method of quickly probing the link quality and/or predicting channel conditions is required. Mathematical distributions for modeling the channel profile seek to estimate fading parameters from a finite number of discrete time samples of signal amplitude. While the statistical inference of such estimators has proven to be robust to rapidly shifting channel conditions, the benefits are quickly realized at the expense of processing complexity. Furthermore, computations of the best-known estimation techniques are often iterative, tedious, and complex. This thesis takes a renewed look at estimating fading parameters for the Nakagami-m, Rice-K, and Weibull distributions, specifically by showing that the need to solve transcendental equations in the estimators can be circumvented through use of polynomial approximation in the least-squared error sense or via asymptotic series expansion which often lead to closed-form and simplified expressions. These new estimators are compared to existing ones, the performances of which are comparable while preserving a lower computational complexity. In addition, the thesis also investigates the impact knowledge of the fading profile has on systems employing adaptive switching modulation schemes by characterizing performance in terms of average bit error rates (BER) and spectral efficiency. A channel undergoing Rice-$K$ fading on top of log-normal shadowing is simulated by correlating samples of received signal amplitude according to the user's doppler speed, carrier frequency, etc. The channel's throughput and BER performances are analyzed using the above estimation techniques and compared to non-estimation assumptions. Further discussion on narrowband fading parameter estimation and its applicability to wireless communication channels is provided. / Master of Science

Wireless technologies, such as satellite, cellular, and wireless internet are now commercially driven by ever more demanding consumers, who are ready for seamless integration of communication networks from the home to the car, and into the office. There is a growing need to quickly transmit information wirelessly and accurately. Engineers have already combine techniques such as orthogonal frequency division multiplexing (OFDM) suitable for high data rate transmission with forward error correction (FEC) methods over wireless channels. In this thesis, we enhance the system throughput of a working OFDM system by adding turbo coding and adaptive modulation (AD). Simulation is done over a time varying, frequency selective Rayleigh fading channel. The temporal variations in the simulated wireless channel are due to the presence of Doppler, a sign of relative motion between transmitter and receiver. The wideband system has 48 data sub-channels, each is individually modulated according to channel state information acquired during the previous burst. The end goal is to increase the system throughput while maintaining system performance under a bit error rate (BER) of 10-2. The results we obtained are preliminary. The lack of resources prevented us from producing detailed graphs of our findings. / Master of Science

Due to the rapid development of wireless communications together with the inflexibility of the current spectrum allocation policy, radio spectrum becomes more and more exhausted. One of the critical challenges of wireless communication systems is to efficiently utilize the limited frequency resources to be able to support the growing demand of high data rate wireless services. As a promising solution, cognitive radios have been suggested to deal with the scarcity and under-utilization of radio spectrum. The basic idea behind cognitive radios is to allow unlicensed users, also called secondary users (SUs), to access the licensed spectrum of primary users (PUs) which improves spectrum utilization. In order to not degrade the performance of the primary networks, SUs have to deploy interference control, interference mitigating, or interference avoidance techniques to minimize the interference incurred at the PUs. Cognitive radio networks (CRNs) have stimulated a variety of studies on improving spectrum utilization. In this context, this thesis has two main objectives. Firstly, it investigates the performance of single hop CRNs with spectrum sharing and opportunistic spectrum access. Secondly, the thesis analyzes the performance improvements of two hop cognitive radio networks when incorporating advanced radio transmission techniques. The thesis is divided into three parts consisting of an introduction part and two research parts based on peer-reviewed publications. Fundamental background on radio propagation channels, cognitive radios, and advanced radio transmission techniques are discussed in the introduction. In the first research part, the performance of single hop CRNs is analyzed. Specifically, underlay spectrum access using M/G/1/K queueing approaches is presented in Part I-A while dynamic spectrum access with prioritized traffics is studied in Part I-B. In the second research part, the performance benefits of integrating advanced radio transmission techniques into cognitive cooperative radio networks (CCRNs) are investigated. In particular, opportunistic spectrum access for amplify-and-forward CCRNs is presented in Part II-A where collaborative spectrum sensing is deployed among the SUs to enhance the accuracy of spectrum sensing. In Part II-B, the effect of channel estimation error and feedback delay on the outage probability and symbol error rate (SER) of multiple-input multiple-output CCRNs is investigated. In Part II-C, adaptive modulation and coding is employed for decode-and-forward CCRNs to improve the spectrum efficiency and to avoid buffer overflow at the relay. Finally, a hybrid interweave-underlay spectrum access scheme for a CCRN is proposed in Part II-D. In this work, the dynamic spectrum access of the PUs and SUs is modeled as a Markov chain which then is utilized to evaluate the outage probability, SER, and outage capacity of the CCRN.

OFDM has been recognized as a powerful multi-carrier modulation technique that provides efficient spectral utilization and resilience to frequency selective fading channels. Adaptive modulation is a concept whereby the modulation modes are dynamically changed based on the perceived instantaneous channel conditions. In conjunction with OFDM systems, adaptive modulation is a very powerful technique to combat the frequency selective nature of mobile channels, while simultaneously attempting to fully maximize the time-varying capacity of the channel. This is based on the fact that frequency selective fading affects the sub-carriers unevenly, causing some of them to fade more severely than others. The modulation modes are adaptively selected on the sub-carriers depending on the amount of fading, to maximize throughput and improve the overall BER. Transmission parameter adaptation is the response of the transmitter to the time-varying channel quality. To efficiently react to the dynamic nature of the channel, adaptive OFDM systems rely on efficient algorithms in three key areas namely, channel quality estimation, transmission parameter selection and signaling or blind detection mechanisms of the modified parameters. These are together termed as the enabling techniques that contribute to the effective performance of adaptive OFDM systems. This thesis deals with higher performance and efficient enabling parameter estimation algorithms that further improve the overall performance of adaptive OFDM systems. Traditional estimation of channel quality indicators, such as noise power and SNR, assume that the noise has a flat power spectral density within the transmission band of the OFDM signal. Hence, a single estimate of the noise power is obtained by averaging the instantaneous noise power values across all the sub-carriers. In reality, the noise within the OFDM bandwidth is a combination of white and correlated noise components, and has an uneven affect across the sub-carriers. It is this fact that has motivated the proposal of a windowing approach for noise power estimation. Windowing provides many local estimates of the dynamic noise statistics and allows better noise tracking across the OFDM transmission band. This method is particularly useful for better resource utilization and improved performance in sub-band adaptive modulation, where adaptation is performed on the sub-carriers on a group-by-group basis based on the observed channel conditions. Blind modulation mode detection is another relatively unexplored issue in regard to adaptation of OFDM systems. The receiver has to be informed of the appropriate modulation modes used at the transmitter for proper demodulation. If this can be done without any explicit signaling information embedded within the OFDM symbol, it has the advantage of improved throughput and data capacity. A model selection approach is taken, a novel statistical blind modulation detection method based on the Kullback-Leibler (K-L) distance is proposed. This algorithm takes into account the distribution of the Euclidian distances from the received noisy samples on the complex plane to the closest legitimate constellation points of all the modulation modes used. If this can be done without any explicit signaling information embedded within the OFDM symbol, it has the advantage of improved throughput and data capacity. A model selection approach is taken, and a novel statistical blind modulation detection method based on the Kullback-Leibler (K-L) distance is proposed. This algorithm takes into account the distribution of the Euclidian distances from the received noisy samples on the complex plane to the closest legitimate constellation points of all the modulation modes used.

[pt] Este trabalho é um estudo sobre um enlace do sistema HSDPA (High Speed Downlink Packet Access), um subsistema do padrão UMTS/WCDMA, desenvolvido para a transmissão de dados em alta velocidade no enlace de descida. Para atingir altas taxas de transmissão, é prevista a utilização, neste sistema, de diversas técnicas avançadas de processamento de sinais, entre elas a modulação adaptativa. O princípio desta técnica é escolher, para cada quadro de bits transmitido, a modulação mais adequada às condições do canal. Através de simulação, o desempenho da modulação adaptativa em enlaces HSDPA foi avaliado em [4], considerando um canal com desvanecimento plano. Estendendo este trabalho, foram introduzidos novos módulos no simulador, de forma a considerar um canal com multipercursos e a utilização de um receptor Rake. A estimação do canal, utilizada na adaptação, é implementada através da análise do sinal recebido e combinado no receptor Rake. O desempenho do enlace foi avaliado em presença de duplo percurso, para diversas situações, através da taxa de erro de pacote e da vazão obtida na transmissão, procurando-se investigar a influência de parâmetros do sistema e da interferência entre os dois percursos nesse desempenho. / [en] This work is a study about the performance of a HSDPA (High Speed Downlink Packet Access) which is a subsystem of UMTS/WCDMA designed for high-speed data transmission in the downlink. In order to achieve high bit rates, the use of advanced signal processing techniques, including adaptive modulation, is specified. This technique consists of choosing, for each transmitted frame, the most efficient modulation according to the channel condition. The performance of adaptive modulation in HSDPA links in a flat fading channel has been evaluated in [4] through simulation. In the present work, new simulation modules have been developed to consider multipath and a Rake receiver. The channel estimation used in the link adaptation is obtained from the received and combined signal at Rake receiver. The link level performance has been evaluated in a double path channel for different situations through packet error rate and throughput. The influence of system parameters and path interference on the performance has been investigated.

This thesis comprises two parts: the first part presents channel-adaptive techniques to achieve high spectral efficiency in a single user multiple-input multiple-output (MIMO) system; the second part exhibits a programmable and reconfigurable software-defined-radio orkbench(SDR-WB) in the Matlab/Octave environment that accommodates a variety of wireless applications. In an attempt to achieve high spectral efficiency, an adaptive modulation technique is applied at the transmitter to vary the data rate depending on the channel state information (CSI). To further enhance the spectral efficiency, adaptive power allocation schemes are applied in the spatial domain to adjust the power on every transmit antenna. We analyze several power control schemes subject to a peak power constraint to maximize the spectral efficiency given an instantaneous target bit-error-rate (BER). A novel power allocation trategy is proposed to achieve high spectral efficiency with relatively low complexity. In addition, adaptive techniques that switch across different MIMO schemes enables even higher spectral efficiency by choosing the scheme with the highest spectral efficiency. We propose a new method to switch between spatial multiplexing with zero-forcing (ZF) detection and orthogonal space-time block coding (OSTBC). This is done by exploiting closed form expressions of the spectral efficiencies--discrete rate spectral efficiency--and finding the crossing points of the two curves. The proposed adaptation scheme adds limited complexity to the transmitter since it requires only statistical information of the channel, which does not change as time evolves. Software Defined Radio (SDR) has received more and more interest recently as a promising multi-band multi-standard solution for transceiver design. In order to support as many wireless applications as possible, we build up a programmable and reconfigurable workbench, namely SDR-WB, in Matlab/Octave environment. The workbench is functionally modularized into generic blocks to facilitate fast development and verification of new algorithms and architectures. The modulation formats that are currently supported by the SDR-WB are MIMO, Orthogonal frequency-division multiplexing (OFDM), MIMO-OFDM, DS-CDMA and Filtered Multitone (FMT). / QC 20101108

This thesis examines the benefits of using adaptive modulation and coding in terms of spectral efficiency and probability of bit error. Specifically, we examine the performance enhancement made possible by using linear prediction along with channel estimation in conjunction with adaptive modulation. We begin this manuscript with basic fundamentals of our study, followed by a detailed view of simulations, their results, and our conclusions from them. The study includes simulations in slow and moderately fast flat fading Rayleigh channels. We present our findings regarding the advantages of using predictive measures to foresee the state of the channel and make adjustments to transmissions accordingly. In addition to finding the general advantages of channel prediction in adaptive modulation, we explore various ways to adjust the prediction algorithm when we are faced with high Doppler rates and fast fading. By the end of this work, we should have a better understanding of when channel prediction is most valuable to adaptive modulation and when it is weakest, and how we can alleviate the problems that prediction will have in harsh environments. / Master of Science