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Regarding the problems of resource allocation in OFDMA-based wireless communication systems, much of the research effort mainly focuses on finding efficient power control and subcarrier assignment policies. With systems employing multicast transmission, the available schemes in literature are not always applicable. Moreover, the existing approaches are particularly inaccessible in practical systems in which there are a large number of OFDM subcarriers being utilized, as the required computational burden is prohibitively high. The ultimate goal of this research is therefore to propose affordable mechanisms to flexibly and effectively share out the available resources in multicast wireless systems deploying OFDMA technology. Specifically, we study the resource distribution problems in both conventional and cognitive radio network settings, formulating the design problems as mathematical optimization programs, and then offering the solution methods. Suboptimal and optimal schemes with high performance and yet of acceptable complexity are devised through the application of various mathematical optimization tools such as genetic algorithm and Lagrangian dual optimization. The novelties of the proposed approaches are confirmed, and their performances are verified by computer simulation with the presentation of numerical examples to support the findings. / Communications

This thesis documents the design of logical superposition coded (SPC) modulation for implementation in wireless video multicast systems, to tackle the issues caused by multi-user channel diversity, one of the legacy problems due to the nature of wireless video multicasting. The framework generates a logical SPC modulated signal by mapping successively refinable information bits into a single signal constellation with modifications in the MAC-layer software. The transmitted logical SPC signals not only manipulatively mimic SPC signals generated by the superposition of multiple modulated signals in the conventional hardware-based SPC modulation, but also yield comparable performance gains when provided with the knowledge of information bits dependencies and receiver channel distributions. At the receiving end, the proposed approach only requires simple modifications in the MAC layer software, which demonstrates full decoding compatibility with the conventional multi-stage signal-interference cancellation (SIC) approach involving additional hardware devices. Generalized formulations for symbol error rate (SER) are derived for performance evaluations and comparisons with the conventional hardware-based approach.

This thesis documents the design of logical superposition coded (SPC) modulation for implementation in wireless video multicast systems, to tackle the issues caused by multi-user channel diversity, one of the legacy problems due to the nature of wireless video multicasting. The framework generates a logical SPC modulated signal by mapping successively refinable information bits into a single signal constellation with modifications in the MAC-layer software. The transmitted logical SPC signals not only manipulatively mimic SPC signals generated by the superposition of multiple modulated signals in the conventional hardware-based SPC modulation, but also yield comparable performance gains when provided with the knowledge of information bits dependencies and receiver channel distributions. At the receiving end, the proposed approach only requires simple modifications in the MAC layer software, which demonstrates full decoding compatibility with the conventional multi-stage signal-interference cancellation (SIC) approach involving additional hardware devices. Generalized formulations for symbol error rate (SER) are derived for performance evaluations and comparisons with the conventional hardware-based approach.

Le système OFDM (Orthogonal Frequency Division Multiplexing) utilise plusieurs sous-porteuses pour transmettre de l’information. Comparé à un schéma mono-porteuse, la modulation multi-porteuses OFDM permet d’obtenir facilement des réglages optimaux (au sens de la capacité de Shannon) pour une transmission à haut débit sur un canal sélectif en fréquence. En ce sens, on peut alors garantir une transmission fiable et une meilleure gestion de l'énergie utilisée. Lors de la transmission avec une modulation OFDM, les sous-porteuses utilisent des canaux différents qui n’ont pas forcement la même atténuation. Allouer le même niveau de puissance à chaque sous-porteuse ne garantit pas une capacité optimale dans une liaison point à point. Une allocation dynamique de la puissance (c’est-à-dire attribuer différents niveaux de puissance aux sous-porteuses en fonction du canal) donne de meilleures performances. Par contre, dans une situation de diffusion (broadcast), l’émetteur ne connaît pas les canaux vers tous les utilisateurs, et la meilleure stratégie consiste à émettre avec la même puissance sur toutes les sous-porteuses. Cette thèse a pour objectif d’explorer les situations intermédiaires, et de proposer les outils d’allocation de puissance appropriés. Cette situation intermédiaire est appelée « multicast », ou « multidiffusion » : l’émetteur envoie les signaux vers un nombre fini (pas trop grand) d’utilisateurs, dont il connaît les paramètres de canaux, et il peut adapter son émission à cette connaissance des canaux. On est donc dans une situation intermédiaire entre le « point à point » et la « diffusion ». L’objectif final de ce travail est d’évaluer le gain apporté par la connaissance des canaux en situation de multicast par rapport à la même communication effectuée comme si on était en diffusion. Bien évidemment, quand le nombre de destinataires est très grand, les gains seront négligeables, car le signal rencontre un nombre très élevé de canaux, et une allocation de puissance uniforme sera quasi optimale. Quand le nombre est très faible, on sera proche du point à point et les gains devraient être sensibles. Nous proposons des outils pour quantifier ces améliorations dans les cas de systèmes ayant une antenne à l'émission et une antenne à la réception, dit SISO (Single Input Single Output) et de systèmes avec plusieurs antennes, dits MIMO (Multiple Input Multiple Output). Les étapes nécessaires pour réaliser ce travail sont : 1) En supposant une connaissance préalable de l’état des canaux (entre station de base et terminaux), mettre en œuvre les outils de la théorie de l'information pour effectuer l’allocation de puissance et évaluer les capacités des systèmes étudiés. 2) Pour le système multi-utilisateur SISO-OFDM, nous proposons un algorithme d'allocation de puissance sur chaque sous porteuse dans une situation de multicast. 3) Pour le système multi-utilisateur MIMO-OFDM, nous proposons un algorithme qui exploite les caractéristiques du précodage "zero forcing". L'objectif est alors de partager la puissance disponible entre toutes les sous-porteuses et toutes les antennes. 4) Enfin, dans une dernière étape nous nous intéressons à une conception efficace de la situation de diffusion, afin de déterminer à l’aide d’outils de géométrie stochastique quelle zone peut être couverte afin qu’un pourcentage donné d’utilisateurs reçoivent une quantité d’information déterminée à l’avance. Ceci permet de déterminer la zone de couverture sans mettre en œuvre des simulations intensives. La combinaison de ces outils permet un choix efficace des situations qui relèvent de la « diffusion », du « multicast » et du « point à point ». / The OFDM (Orthogonal Frequency Division Multiplexing) system uses multiple sub-carriers for data transmission. Compared to the single-carrier scheme, the OFDM technique allows optimal settings for high data rate transmission over a frequency selective channel (from the Shannon’s capacity point of view). We can, by this way, ensure reliable communication and efficient energy use. When we use OFDM, the sub-carriers use different channels with different attenuations as well. The equal power allocation on each sub-carrier does not ensure an optimal capacity in a peer to peer link. Dynamic power allocation (i.e., assign different amount of power to subcarriers according to the channel) gives better results, assuming that the channel state information is available at the transmitter. Nevertheless, the transmitter does not know the channels to all users when broadcast transmission are used, and the best strategy is to transmit with the same power on all subcarriers. This thesis aims to explore the intermediate situations, and propose appropriate power allocation tools. This intermediate situation is called "multicast": the transmitter, which knows the channel parameters, sends signals to a finite number of users, and it can adapt the transmission using this knowledge. It is an intermediate position between the "peer to peer" and the "broadcast. The goal of this work is to evaluate the gain brought by the knowledge of the channel state information in multicast situation beside the broadcast situation. Obviously, when the number of receivers is very large, the gain will not be appreciable because the signal found on its path a very large number of channels, and a uniform power allocation is near optimal. When the number of users is very low, we will be close to the peer to peer transmission and gains should be more appreciable. We propose some tools to quantify these improvements in the case where the systems have one antenna at the transmitter and the receiver, this case named SISO (Single Input Single Output). We also propose those tools on systems with multiple antennas, called MIMO (Multiple Input Multiple Output). The steps required to do this work are: 1) Assuming that the channel state information of the users are known at the base station, we implement tools, using information theory, to perform power allocation and evaluate the capacities of the systems under study. 2) For multi-user SISO-OFDM scheme, we propose a power allocation algorithm on each subcarrier on multicast situation. 3) For multi-user MIMO-OFDM, we propose an algorithm that exploits the characteristics of the "zero forcing" precoding. The objective is to share the available power among all subcarriers and all antennas. 4) Finally, in a last step we focus on an efficient design of the broadcast situation. We use tools from stochastic geometry to determine which area can be covered, with the aim that a percentage of users can receive a predetermined amount of information. This determines the coverage area without implementing long period simulations. The combination of these tools allows an effective choice between the situations that fall under the "broadcast", "multicast" and "peer to peer" transmissions.

In this work, a new multicast routing algorithm for wireless networks is presented. The algorithm, called SWIM (Source-initiated WIreless Multicast), is a depth-optimal multicast tree formation algorithm. SWIM is fully distributed and has an average computational complexity of O(N 2 ). SWIM forms a shared tree from the source(s) to destinations / yet, as a by-product, it creates a multicast mesh structure by maintaining alternative paths at every tree node. This makes SWIM suitable for both ad hoc networks and access networks with multiple gateways. An extension to the main algorithm is presented for the use in dynamic networks with mobility and/or dynamic destination group. Performance of SWIM is studied with simulations and is compared to other algorithms in the literature. Due to depth optimality, SWIM achieves a lower average and maximum delay than the compared algorithms. The throughput performance is found to be high. Working capability with rateless codes are also studied.