Efficient Heuristic for Resource Allocation in Zero-forcing OFDMA-SDMA Systems with Minimum Rate Constraints

4G wireless access systems require high spectral efficiency to support the ever increasing number of users and data rates for real time applications. Multi-antenna OFDM-SDMA systems can provide the required high spectral efficiency and dynamic usage of the channel, but the resource allocation process becomes extremely complex because of the augmented degrees of freedom. In this paper, we propose two heuristics to solve the resource allocation problem that have very low computational complexity and give performances not far from the optimal. The proposed heuristics select a set of users for each subchannel, but contrary to the reported methods that solve the throughput maximization problem, our heuristics consider the set of real-time (RT) users to ensure that their minimum rate requirements are met. We compare the heuristics' performance against an upper bound and other methods proposed in the literature and find that they give a somewhat lower performance, but support a wider range of minimum rates while reducing the computational complexity. The gap between the objective achieved by the heuristics and the upper bound is not large. In our experiments this gap is 10.7% averaging over all performed numerical evaluations for all system configurations. The increase in the range of the supported minimum rates when compared with a method reported in the literature is 14.6% on average.Comment: 8 figure

Dual-based bounds for resource allocation in zero-forcing beamforming OFDMA-SDMA systems

We consider multi-antenna base stations using orthogonal frequency-division multiple access and space division multiple access techniques to serve single-antenna users. Some users, called real-time users, have minimum rate requirements and must be served in the current time slot while others, called non real-time users, do not have strict timing constraints and are served on a best-effort basis. The resource allocation (RA) problem is to find the assignment of users to subcarriers and the transmit beamforming vectors that maximize the total user rates subject to power and minimum rate constraints. In general, this is a nonlinear and non-convex program and the zero-forcing technique used here makes it integer as well, exact optimal solutions cannot be computed in reasonable time for realistic cases. For this reason, we present a technique to compute both upper and lower bounds and show that these are quite close for some realistic cases. First, we formulate the dual problem whose optimum provides an upper bound to all feasible solutions. We then use a simple method to get a primal-feasible point starting from the dual optimal solution, which is a lower bound on the primal optimal solution. Numerical results for several cases show that the two bounds are close so that the dual method can be used to benchmark any heuristic used to solve this problem. As an example, we provide numerical results showing the performance gap of the well-known weight adjustment method and show that there is considerable room for improvement

Efficient Methods for Resource Allocation in Multi-Antenna Orthogonal Frequency-Division Multiple Access (OFDMA) Systems

Résumé Dans cette thèse, nous proposons une solution au problème d’allocation de ressources d’un système MISO (Multiple Input Multiple Output) – OFDMA (Orthogonal Frequency Division Multiplexing Access) supportant des usagers requérant un débit de transmission minimal. Ce problème peut être modélisé comme une optimisation non-linéaire mixte avec variables entières. Nous nous sommes intéressés dans cette thèse à diverses méthodes permettant la résolution d’un tel problème. La première approche étudiée utilise une méthode hors-ligne et permet d’obtenir une solution quasi-optimale qui peut être utilisée comme références pour évaluer la performance d’algorithmes heuristiques pouvant être réalises en temps réel. Pour ce faire, nous cherchons une allocation réalisable en se basant sur la solution optimale du problème dual. Nous obtenons la fonction duale et trouvons la solution à l’aide d’un algorithme itératif à sous-gradient. Cette solution permet d’obtenir une borne supérieure à la solution optimale. D’autre part, nous développons une heuristique basée sur la solution du problème dual pour obtenir une solution réalisable du problème primaire qui constitue une borne inferieure à la solution optimale. Ces bornes nous permettent d’établir que l’écart de dualité est petit pour les configurations étudiées et elles peuvent servir de référence pour l’évaluation de performances des algorithmes heuristiques. La formulation duale nous fournit aussi une meilleure compréhension du sujet en établissant un lien entre la réalisabilité de l’allocation de ressources et les débits minimaux requis par les usagers. Afin d’obtenir des méthodes de résolution plus pratiques pouvant être réalisées en temps réel, nous proposons deux heuristiques ayant une faible complexité et permettant d’atteindre des performances assez prés des performances optimales. Les performances ainsi obtenues sont légèrement moins bonnes que celles d’autres algorithmes qu’on retrouve dans la littérature, mais supportent une plus grande plage de valeurs de débit minimal tout en réduisant la complexité de l’algorithme d’allocation de ressources de plusieurs ordres de grandeur. L’écart entre la solution trouvée par ces algorithmes heuristiques et la borne supérieure duale est relativement faible. Par exemple, l’écart est de 10.7% en moyenne pour toutes les configurations étudiées. L’augmentation dans la plage de débits minimaux supportes compares avec les méthodes disponibles dans la littérature est de 14.6% en moyenne. Cette amélioration est obtenue en considérant les variables duals de contrainte de débits minimaux dans l’allocation de puissance aux usagers. L’algorithme heuristique proposé sélectionne un ensemble d’usagers pour chaque sous-porteuse, mais contrairement aux autres méthodes proposées précédemment, l’algorithme considère l’ensemble des usagers avec des contraintes de débits minimaux dans la réassignation des sous-porteuses pour s’assurer que le niveau de service requis est rencontre. Suite à la sélection des ensembles d’usagers, un problème d’allocation de puissance convexe est résolu. Des algorithmes permettant de résoudre efficacement et en un temps moindre les problèmes d’assignation des sous-porteuses aux usagers et d’allocation de puissance sont proposées dans cette thèse. Finalement, nous étudions aussi de quelle façon ces algorithmes peuvent être utilises pour résoudre le problème d’allocation de ressources dans une cellule utilisant la technologie LTE (Long Term Evolution)-Advanced. Les méthodes étudiées dans cette thèse font partie d’un nouvel ensemble d’algorithmes nécessaires pour supporter des applications temps réel à haut débit et a l’efficacité spectrale requise dans les prochains réseaux d’accès sans-fil de quatrième génération.----------Abstract In this dissertation, we solve the Resource Allocation (RA) problem of a Multiple Input Single Output (MISO) – Orthogonal Frequency Division Multiplexing Access (OFDMA) sys¬tem supporting minimum rates. This problem can be modelled as a non-linear Mixed Integer Program (NLMIP). We are interested in various kinds of methods to solve this problem. First, our focus is on an off-line method that gives near-optimal solutions that serve as benchmark for more practical methods. For this purpose, we propose a method based on the optimal solution of the dual problem. We obtain a dual function and solve the dual problem through subgradient iterations. Then, we find upper and lower bounds for the optimal solution and verify that the duality gap is small for the system configurations studied. Therefore, the dual optimal serves as a reference for any feasible solution produced by the heuristic methods. The dual formulation also gives a better insight into the problem, as it shows us the relation between the problem’s feasibility and the minimum rate requirements. To obtain more practical methods, we propose two heuristics that have very low com-putational complexity and give performances not far from the optimal. We compare their performance against other methods proposed in the literature and find that they give a somewhat lower performance, but support a wider range of minimum rates while reducing the computational complexity of the algorithm by several orders of magnitude. The gap be¬tween the objective achieved by the heuristics and the upper bound given by the dual optimal is not large. For example, in our experiments this gap is 10.7% averaging over all performed numerical evaluations for all system configurations. The increase in the range of the sup¬ported minimum rates when compared with the method reported in the literature is 14.6% on average. This increase is achieved by considering the rate constraint dual variables in the user power allocation stage. The proposed heuristics select a set of users for each subcarrier, but contrary to other reported methods used to solve the throughput maximization problem, they consider the set of real-time (RT) users to ensure that their minimum rate requirements are met. Then, they solve a power allocation problem for fix subcarrier assignment, which is a convex problem that is simpler to solve. We use efficient algorithms for the subcarrier assignment and power allocation stages to solve the problem much quicker. Finally, we adapt the algorithms to solve the RA problem in a single cell using LTE (Long Term Evolution)–Advanced technology. The methods examined in this dissertation are part of the new set of algorithms needed to support the high rate applications and spectral efficiency required in the wireless access of upcoming 4G networks

Alocação de recursos para sistemas móveis multi-utilizador e multi-antena

Doutoramento em Engenharia ElectrotécnicaThe thesis addresses the sum rate or spectral e ciency maximization problem in cellular systems with two main components, multiple antennas and multiple users. In order to solve such a problem, several resource allocation techniques are studied and developed for di erent cellular scenarios. The antennas at the transmitters are arranged in several con gurations, i.e., co-located or distributed and for such arrangements di erent levels of coordination and cooperation between transmitters are investigated. Accounting for more receiver antennas than transmitter antennas implies that system optimization must select the best transmitter-receiver match (combinatorial problem) which can be solved with di erent degrees of cooperation between transmitters. The system models studied can be classi ed either as interference limited or as power limited systems. In interference limited systems the resource allocation is carried out independently by each transmitter which yield power leakage to unintended receivers. For this kind of systems, the access network using distributed antenna architectures is examined. The properties of distributed antenna in cellular systems as well as the gains they provide in terms of frequency reuse and throughput are assessed. Accounting for multiple user scenarios, several techniques and algorithms for transmitter-receiver assignment, power allocation, and rate allocation are developed in order to maximize the spectral e ciency. In power limited systems the transmitters jointly allocate resources among transmit and receive antennas. The transmitters are equipped with multiple antennas and signal processing is implemented in order to suppress inter-user interference. Single-cell and multi-cell systems are studied and the problem of sum rate maximization is tackled by decoupling the user selection and the resource allocation (power and precoding) processes. The user selection is a function of the type of precoding technique that is implemented and the level of information that can be processed at the transmitter. The developed user selection algorithms exploit information provided by novel channel metrics which establish the spatial compatibility between users. Each metric provides a di erent trade-o between the accuracy to identify compatible users, and the complexity required to compute it. Numerical simulations are used to assess the performance of the proposed user selection techniques (metrics and algorithms) whose performance are compared to state-of-the-art techniques.Esta tese descreve o problema da maximização da taxa de transmissão ou e ciência espectral em sistemas moveis tomando em atenção duas características fundamentais destes, o número de antenas e utilizadores. A fim de resolver este tipo de problema, várias técnicas de alocação de recursos foram estudadas e propostas para diferentes cenários. As antenas nos transmissores estão organizadas em diferentes configurações, podendo ser localizadas ou distribuídas e para estes esquemas, diferentes níveis de cooperação e coordenação entre transmissores foram investigados. Assumindo mais antenas receptoras do que antenas transmissoras, implica que a otimização do sistema seleccione as melhores combinações de transmissor-receptor (problema combinatório), o que pode ser concretizado usando diferentes graus de cooperação entre transmissores. Os modelos de sistemas estudados, podem ser classificados como sistemas limitados por interferência ou sistemas limitados por potência. Em sistemas limitados por interferência a alocação de recursos e feita independentemente para cada transmissor o que resulta em perda de energia para os receptores não tomados em consideração. Para este tipo de sistemas, e considerado o caso em que a rede de acesso e constituída por antenas distribuídas. Os ganhos obtidos devido ao uso de antenas distribuídas, quer em termos do planeamento de frequências quer da maximização da taxa de transmissão são considerados. Assumindo esquemas multi-utilizador, várias técnicas e algoritmos de transmissão-recepção, alocação de potência e de taxa de transmissão foram desenvolvidos para maximizar a e ciência espectral. Para sistemas limitados em potência os transmissores alocam os recursos quer de antenas de transmissão quer de recepção conjuntamente. Os transmissores estão equipados com várias antenas e o processamento de sinal e implementado de modo a eliminar a interferência entre utilizadores. Sistemas de célula única e de múltiplas células foram estudados. Para estes foi considerado o problema da maximização de taxa de transmissão o qual foi resolvido heuristicamente, através do desacoplamento do problema em duas partes, uma onde se efectua a seleção de utilizadores e outra onde se considera a alocação de recursos. A seleção de utilizadores e feita em função do tipo de técnicas de pré-codificação implementadas e do nível de informação que o transmissor possui. Os algoritmos de seleção de utilizadores desenvolvidos verificam a compatibilidade espacial entre utilizadores, usando para tal métricas propostas. Cada uma das métricas oferece um trade-off diferente entre a precisão para identificar um utilizador compatível e a complexidade necessária para a implementar. Foram usadas simulações numéricas para avaliar a performance das técnicas de seleção de utilizadores propostas (métricas e algoritmos), performance que foi comparada com as técnicas mais inovadoras

Traffic Scheduling in Point-to-Multipoint OFDMA-based Systems

The new generation of wireless networks (e.g., WiMAX, LTE-Advanced, Cognitive Radio) support many high resource-consuming services (e.g., VoIP, video conference, multiplayer interactive gaming, multimedia streaming, digital video broadcasting, mobile commerce). The main problem of such networks is that the bandwidth is limited, besides to be subject to fading process, and shared among multiple users. Therefore, a combination of sophisticated transmission techniques (e.g., OFDMA) and proper packet scheduling algorithms is necessary, in order to provide applications with suitable quality of service. This Thesis addresses the problem of traffic scheduling in Point-to-Multipoint OFDMA-based systems. We formally prove that in such systems, even a simple scheduling problem of a Service Class at a time, is NP-complete, therefore, computationally intractable. An optimal solution is unfeasible in term of time, thus, fast and simple scheduling heuristics are needed. First, we address the Best Effort traffic scheduling issue, in a system adopting variable-length Frames, with the objective of producing a legal schedule (i.e., the one meeting all system constraints) of minimum length. Besides, we present fast and simple heuristics, which generate suboptimal solutions, and evaluate their performance in the average case, as in the worst one. Then, we investigate the scheduling of Real Time traffic, with the objective of meeting as many deadlines as possible, or equivalently, minimizing the packet drop ratio. Specifically, we propose two scheduling heuristics, which apply two different resource allocation mechanisms, and evaluate their average-case performance by means of a simulation experiment