This thesis presents packet-level channel modeling, spectrum efficiency optimization and channel estimation for wireless cooperative communication systems with diversity combining. Cooperative transmission in a wireless network allows neighboring nodes to share their communication resources to create a virtual antenna array by distributed transmission and signal processing, which is useful to exploit spatial diversity, increase channel capacity, and attain wider service coverage with single-antenna terminals. How to exploit spatial diversity and leverage the multi-hop channel structure is an important research issue for the cooperative network. In this thesis, two cooperative schemes are considered, amplify and forward (AF) and demodulation and forward (DMF). For AF cooperative systems, finite state Markov chain (FSMC) models are designed in analyzing the system performance considering time-varying channel behaviors and facilitating fast channel simulation. For DMF cooperative systems, first we formulate the optimization problem that jointly chooses the modulation schemes at the source and relay nodes, to maximize the throughput of cooperative systems under the BER constraint. Second, we propose to use the soft values of each bit to devise a simple and effective combining scheme, which can be applied for both AF and DMF cooperative systems. Third, as the soft values from demodulation process can also be used for measuring the channel estimation accuracy, a soft value-assisted channel estimation has been proposed by iteratively utilizing soft values to refine the accurate channel estimation. In addition, we also implement the soft value module in OFDM-based transceiver system based on a GNU Radio/USRP2 platform, and verify the effectiveness and performance improvement for the proposed SVC systems. As considering wireless cooperative systems has attracted increasing attentions from both academic and industry to meet the demanding of the high data rate transmission, the packet-level channel modeling, adaptive modulation, spectrum efficiency improvement frameworks based on soft value combining and accurate channel estimation algorithms proposed in this thesis are essential for future proliferation of high data rate, reliable and efficient wireless communication networks. / Graduate / 0537 / 0544 / 0984

To broaden the application scenario and reduce energy consumption, we propose an energy-efficient fixed-gain (FG) amplify-and-forward (AF) relay assisted orthog- onal frequency-division multiplexing with index modulation (OFDM-IM) scheme in this thesis. The proposed system needs neither instantaneous channel state informa- tion (CSI) nor performing complicated processing at the relay node. It operates based on a new design of power allocation that minimizes the sum of transmit power at both source and relay node, given an outage probability constraint. Considering the actual situation and combining with the characteristics of normalization research, the pro- posed scheme can be discussed in two scenarios regarding to whether the subcarriers are interfered with by fading and noise independently. Based on the consistency of statistical CSI for each subcarrier, through a series of problem transformation and simplification, this thesis converts the original power allocation problem to a relaxed version and solve the relaxed problem using the convex optimization techniques. To reveal the computing efficiency of the proposed power allocation scheme, we analyze its computational complexity. Numerical simulations substantiate that the proposed optimization scheme has a neglectable loss compared with the brute force search, while the computational complexity could be considerably reduced. As for the sce- nario about the independence of statistical CSI for each subcarrier, an approach of artificial neural network (ANN) based on deep learning is incorporated into the sys- tem, enabling the proposed scheme to achieve a high accuracy comparing perfect optimization scheme. In the processing of power minimization, this study utilizes the adaptive moment estimation (Adam) method to implement back-propagation learn- ing and achieve the power allocation needed.

The concept of multihop communications (where the source communicates with the destination via many intermediate nodes) has been revisited and adapted to mitigate wireless channel impairments and ensure broader coverage. It has been shown in the literature that, in addition to extending coverage, overcoming shadowing and reducing the transmit power, multihop communications can increase the capacity of the network at a low additional cost. On the other hand, the problem of energy efficiency is one of the current biggest challenges towards green radio communications. Morevover, electromagnetic radiation is at its limit in many contexts, while for battery-powered devices, transmit and circuit energy consumption has to be minimized for better battery lifetime and performance. In this work, the performance of multihop communication over Nakagami-m fading is investigated for both cases without and with diversity combining. Closed form expressions of the average ergodic capacity are derived for each of these cases. Then, an expression of the outage probability is obtained using the inverse of Laplace transform and the average bit error rate is bounded using the Moment-Generating-Function approach. The energy efficiency is analyzed using the "consumption factor" as a metric, and it is derived in closed-form. And based on the obtained expressions, we propose a power allocation strategy maximizing this consumption factor.

L’estimation de canal est une tâche cruciale du récepteur radio dans les systèmes de communication sans fil, en particulier en cas de mobilité où les paramètres du canal varient avec le temps en raison de l’effet Doppler. Dans cette thèse, nous considérons des variations de canal lentes à modérées, typiques des applications véhiculaires, et en particulier les deux types de canaux suivant : canaux Fixe-Mobiles (F-M) et canaux Mobiles-Mobiles (M-M), avec dans ce dernier cas la présence éventuelle de relais mobiles permettant d’amplifier et re-émettre le signal (Amplify and Forward). Nous avons démarré notre étude avec le canal F-M, qui servira de base pour traiter le canal M-M.Pour le cas d’un canal F-M, modélisé par le modèle de Rayleigh à spectre de Jakes, une approche courante pour estimer le canal consiste à utiliser un filtre de Kalman (KF) basé sur un modèle autorégressif d'ordre p (AR(p)). La méthode conventionnelle pour régler les paramètres du modèle AR(p) est basée sur le critère de corrélation (CM). Cependant, l’inconvénient majeur de cette méthode est que des ordres très élevés (p > 15) sont nécessaires pour approcher la borne de Cramer-Rao Bayésienne. Le choix de p ainsi que le réglage des paramètres du modèle sont donc critiques et un compromis doit être trouvé entre la complexité numérique et la performance. Le compromis raisonnable qui a suscité beaucoup d’attention est de prendre p = 2. Le CM n’étant pas performant pour p = 2, d’autres méthodes de réglage ont été proposées dans la littérature, mais celle-ci reposent principalement sur des résultats expérimentaux ou des recherches exhaustives, ce qui limite leur application. Pour régler le modèle, nous proposons d'utiliser un critère de minimisation de la variance asymptotique (MAV) de l’erreur d’estimation en sortie du filtre de Kalman. Une formule générale de réglage a été dérivée en fonction de l’état du canal (fréquence Doppler et rapport signal sur bruit), qui peut s’avérer très utile en pratique. De plus, nous avons également dérivé une formule analytique pour l'erreur quadratique moyenne, ce qui permet de mieux comprendre le comportement du KF. Ensuite, nous avons traité le canal M-M avec présence éventuelle de relais, en suivant la même approche. Les expressions analytiques pour le réglage optimal des paramètres du modèle AR(2) et les performances en erreur quadratique moyenne ont d'abord été établies en fonction des deuxièmes et quatrièmes moments du spectre Doppler du canal global. Les formules analytiques de ces moments ont été dérivées en exploitant la propriété de convolution des fonctions de densité, après décomposition du canal global en cascade de canaux élémentaires à spectre de Jakes. Avec ces approches, les résultats de simulations pour les différents canaux montrent un gain considérable en terme d’erreur quadratique moyenne d’estimation, comparé à la littérature. / Channel estimation is a crucial task of the radio receiver in wireless communication systems, especially in the case of mobility where the channel parameters vary over time due to the Doppler effect. In this thesis, we consider slow to moderate channel variations, typical of vehicular applications, and in particular the following two types of channels: fixed-mobile (F-M) channels and mobile-mobile (M-M) channels, with in the latter case the possible presence of mobile relays (Amplify and Forward). We started our study with the F-M channel, which will serve as a basis for investigating the M-M channel.For the case of an F-M channel, modeled by Rayleigh model described by the Jakes spectrum, a common approach to estimating the channel is to use a Kalman filter (KF) based on an autoregressive model of order p (AR(p)). The conventional method for setting AR(p) model parameters is based on the correlation matching criterion (CM). However, the major disadvantage of this method is that very high orders p>15) are needed to approach the Bayesian Cramer-Rao Bound. The choice of p as well as the adjustment of the parameters of the model are therefore critical and a compromise must be found between the numerical complexity and the performance. The reasonable compromise that has attracted a lot of attention is to take p = 2. Since the CM is not efficient for p = 2, other methods of tuning have been proposed in the literature, but these are mainly based on experimental results or exhaustive searches, which limits their application.To adjust the model, we propose to use a criterion of minimization of the asymptotic variance (MAV) of the estimation error at the output of the Kalman filter. A general tuning formula has been derived based on the state of the channel (Doppler frequency and signal-to-noise ratio), which can be very useful in practice. In addition, we also derived an analytic formula for the mean squared error, which allows a better understanding of KF behavior.Then we treated the M-M channel with the possible presence of mobile relays, following the same approach. The analytical expressions for the optimal adjustment of the AR(2) model parameters and the mean squared error performance were first set according to the second and fourth moments of the Doppler spectrum of the global channel. The analytical formulas of these moments were derived by exploiting the convolution property of the density functions, after decomposing the cascading global channel channel of Jakes spectrum elementary channels. With these approaches, the results of simulations for the different channels show a considerable gain in terms of mean squared error performance estimation, compared to the literature.

Cooperative wireless communication uses relays to enhance the capacity and reliability of data transmission. Adaptive transmission is typically used in conventional non-cooperative communications to exploit the time-varying nature of the wireless channel. In this thesis, we combine these two techniques. We consider decode-and-forward (DF) and amplify-and-forward (AF) relays. The wireless environment is modeled by using the Nakagami-m distribution. The achievable channel capacity with rate adaptive transmission is analytically derived for DF and AF cooperative networks. The performance of a DF cooperative network is analyzed with a constant power rate adaptive scheme consisting of a discrete set of transmission modes. The effect of decoding errors on DF cooperative networks is also analyzed. To this end, a new heuristic approximation of the total received signal-to-noise ratio at the destination is developed. This approximation enables simple yet accurate performance analysis. / Communications

In wireless communications, channel estimation is necessary for coherent symbol detection. This thesis considers a network which consists of two transceivers communicating with the help of a relay applying the amplify-and-forward (AF) relaying scheme. The training based channel estimation technique is applied to the proposed network where the numbers of the training sequence transmitted by the two transceivers, are different. All three terminals are equipped with a single antenna for signal transmission and reception. Communication between the transceivers is carried out in two phases. In the first phase, each transceiver sends a transmission block of data embedded with known training symbols to the relay. In the second phase, the relay retransmits an amplified version of the received signal to both transceivers. Estimates of the channel coefficients are obtained using the Maximum Likelihood (ML) estimator. The performance analysis of the derived estimates are carried out in terms of the mean squared error (MSE) and we determine conditions required to increase the estimation accuracy. / UOIT

Cooperative communications have received much attention recently, due to its ability to attain cooperation diversity. But when two nodes communicate via relays, it is difficult to get the perfect channel information, so relays must estimate their forward channel and backward channel in order to amplify the data to the destination. We investigate the effect of channel estimation error, and design the LMMSE estimator to estimate the channels, and also we consider the multi-relays to assist the whole system for training and data transmission. We propose the SNR gap ratio, outage probability, and the BER simulations for the analysis. Simulation shows that when using multi-relays, it can mitigate the effect of channel estimation errors in all of the amplify-and-forward (AF) scenarios.

In the wireless sensor network environment (WSN), the system transmits signals often need to rely on the stability and reliability of the relay node of each path of cooperation with each other to achieve balance between leisure and stability. In general, relay adopted Amplify-and-Forward (AF) and Decode-and-Forward (DF) to relaying the signal to destination. Unfortunately, in reality, the relay node itself had a problem of limited energy supplies, would make the overall performance degrade before reaching the optimal performance. Therefore, we propose two novel relay selection schemes and through the multi-hop transmission with cooperation. We also derived the optimal power allocation algorithms for all relay nodes. Finally, simulation results show that our proposed scheme obtained the better lifetime and performance where compared with the traditional schemes in a fair environment.

In this thesis, we address the statistics of mutual information of amplify-and-forward (AF) multiple-input multiple-output (MIMO) two-hop relay channels, where the source terminal (ST), relay terminal (RT) and destination terminal (DT) are equipped with a number of correlated antennas and there is a line-of-sight (LOS) component (Rician fading) of each link. To the best of our knowledge, deriving analytical expressions for the statistics of mutual information of the relay channel is difficult and still unsolvable. To circumvent the mathematical difficulties, we consider this problem under the large-system regimen in which the numbers of antennas at the transmitter and receiver go to infinity with a fixed ratio. In the large-system regimen, this thesis has made the following contributions: 1) We get the mean and the variance of the mutual information of the concerned relay channel. 2) We show that the mutual information distribution converges to the Gaussian distribution. The analytical results are derived by mean of two powerful tools developed in the context of theoretical physics: emph{saddle-point approximation} and emph{superanalysis}. The derived analytical results are very general and can degenerate to several previously results as special cases. From a degenerated case, we realize that the previous result by Wagner {em et al.} cite{Wag-08} is wrong and thus we provide the corrected result. Finally, Simulation results demonstrate that even for a moderate number of antennas at each end, the proposed analytical results provide undistinguishable results as those obtained by Monte-Carlo results.

Dual-hop transmission system can increase the transmission diversity via the cooperation of transmission nodes and can also overcome the channel fading effectively. This thesis proposes an outage probability analysis method for the AF relaying system where multiple antennas are equipped at source node and both the relay node and destination node just carry single antenna. Compare with previous work, the average signal to noise ratio of source to relay and relay to destination links are assumed to be two different variables, therefore we can get a more general performance analysis. We also extend our theoretical analysis to the system where multiple antennas are utilized at destination node. Simulation results are shown to verify the analysis of the proposed schemes in some representative scenarios.