Outage Probability for Multi-Cell Processing under Rayleigh Fading

Multi-cell processing, also called Coordinated Multiple Point (CoMP), is a very promising distributed multi-antennas technique that uses neighbour cell's antennas. This is expected to be part of next generation cellular networks standards such as LTE-A. Small cell networks in dense urban environment are mainly limited by interferences and CoMP can strongly take advantage of this fact to improve cell-edge users' throughput. This paper provides an analytical derivation of the capacity outage probability for CoMP experiencing fast Rayleigh fading. Only the average received power (slow varying fading) has to be known, and perfect Channel State Information (CSI) is not required. An optimisation of the successfully received data-rate is then derived with respect to the number of cooperating stations and the outage probability, illustrated by numerical examples

Why sports should embrace bilateral asymmetry: a narrative review

(1) Background: Asymmetry is ubiquitous in nature and humans have well-established bilateral asymmetries in their structures and functions. However, there are (mostly unsubstantiated) claims that bilateral asymmetries may impair sports performance or increase injury risk. (2) Objective: To critically review the evidence of the occurrence and effects of asymmetry and sports performance. (3) Development: Asymmetry is prevalent across several sports regardless of age, gender, or competitive level, and can be verified even in apparently symmetric actions (e.g., running and rowing). Assessments of bilateral asymmetries are highly task-, metric-, individual-, and sport-specific; fluctuate significantly in time (in magnitude and, more importantly, in direction); and tend to be poorly correlated among themselves, as well as with general performance measures. Assessments of sports-specific performance is mostly lacking. Most studies assessing bilateral asymmetries do not actually assess the occurrence of injuries. While injuries tend to accentuate bilateral asymmetries, there is no evidence that pre-existing asymmetries increase injury risk. While training programs reduce certain bilateral asymmetries, there is no evidence that such reductions result in increased sport-specific performance or reduced injury risk. (4) Conclusions: Bilateral asymmetries are prevalent in sports, do not seem to impair performance, and there is no evidence that suggests that they increase injury risk

Model Predictive Control for Smooth Distributed Power Adaptation

International audienceThis paper addresses the distributed power adaptation (DPA) problem on the downlink for wireless cellular networks. As a consequence of uncoordinated local scheduling decisions in classical networks, the base stations produce mutual uncontrolled interference on their co-channel users. This interference is of a variable nature, and is hardly predictable, which leads to suboptimal scheduling and power control decisions. While some works propose to introduce cooperation between BS, in this work we propose instead to introduce a model of power variations, called trajectories in the powers space, to help each BS to predict the variations of other BS powers. The trajectories are then updated using a Model Predictive Control (MPC) to adapt transmit powers according to a trade-off between inertia (to being predictable) and adaptation to fit with capacity needs. A Kalman filter (KF) is used for the interference prediction. In addition, the channel gains are also predicted, in order to anticipate channel fading states. This scheme can be seen as a dynamic distributed uncoordinated power control for multichannel transmission that fits the concept of self-optimised and self-organised wireless networks (SON). By using the finite horizon MPC, the transmit powers are smoothly adapted to progressively leave the current trajectory toward the optimal trajectory. We formulate the optimisation problem as the minimisation of the utility function of the difference between the target powers and MPC predicted power values. The presented simulation results show that in dynamic channel conditions, the benefit of our approach is the reduction of the interference fluctuations, and as a consequence a more accurate interference prediction, which can further lead to a more efficient distributed scheduling, as well as the reduction of the overall power consumption

Multi-cell processing for uniform capacity improvement in full spectral reuse system

International audienceIn this paper, we study the potential of Multi-Cell Processing (MCP), via Base Stations (BSs) coordination , to improve the uniform capacity of a wireless network. MCP is particularly efficient for edge-cell users that experience very low SINR when an intensive spectral reuse is employed. We choose a baseline form of MCP to show that a simple Alamouti-like code can enhance the SINR by accounting the strongest interferer as a useful signal at the receiver. After having introduced the formulation for uniform capacity, we numerically derive the optimal conditions to use MCP. We then validate our approach by simulation and show that this optimal MCP can increase the uniform capacity by up to a factor 2 and 6 compared to Fractional Frequency Reuse (FFR) and simple Reuse1 mode by using an urban micro-cell channel model

Capacity-Fairness Trade-off Using Coordinated Multi-Cell Processing

International audienceMulti-cell processing, also called Coordinated Multiple Point (CoMP), is a promising distributed technique that uses neighbour cells' antennas. It is expected to be the part of next generation cellular standards such as LTE-A. Small cell networks in dense urban environments are limited by interferences and CoMP can strongly take advantage of this fact to improve cell-edge users' throughput. The present study introduces a distributed criterion for mobiles to select their optimal set of Base Stations (BS) to perform CoMP, and evaluates the impact of this association on the fairness and the total cell throughput. For that, we use a known theoretical expression for the capacity outage probability of CoMP under Rayleigh fading and evaluate the goodputs of antennas associations. The proposed criterion is used in combination with $\alpha$-fair resource allocation to perform a joint double-objective optimization of fairness and efficiency

Gibbs Sampling Based Distributed OFDMA Resource Allocation

International audienceIn this article, we present a distributed resource and power allocation scheme for multiple-resource wireless cellular networks. The global optimization of multi-cell multi-link resource allocation problem is known to be NP-hard in the general case. We use Gibbs sampling based algorithms to perform a distributed optimization that would lead to the global optimum of the problem. The objective of this article is to show how to use the Gibbs sampling (GS) algorithm and its variant the Metropolis-Hastings (MH) algorithm. We also propose an enhanced method of the MH algorithm, based on a priori known target state distribution, which improves the convergence speed without increasing the complexity. Also, we study different temperature cooling strategies and investigate their impact on the network optimization and convergence speed. Simulation results have also shown the effectiveness of the proposed methods

Self-Optimized Precoding and Power Control in Cellular Networks

International audienceIn this paper, we propose an autonomous radio resource allocation and optimization scheme that chooses the transmit power and precoding vector among codebooks for multiple antennas transmitters to improve spectral and power efficiency and provide user fairness. Network self-optimization is an essential feature for supporting the cell densification in future wireless cellular systems. The proposed self-optimization is inspired by Gibbs sampler. We show that it can be implemented in a distributed manner and nevertheless achieves system-wide optimization which improves network throughput, power utilization efficiency, and overall service fairness. In addition, we extend the work and include power pricing to parametrize and enhance energy efficiency further. Simulation results show that the proposed scheme can outperform today's default modes of operation in network throughput, energy efficiency, and user fairness

Optimisation du partage de ressources pour les réseaux cellulaires auto-organisés

This thesis focuses on resources and power allocation problem in the fourth generation (4G) of cellular networks. To face the continuous growth of mobile users capacity requirements, operators need to densify their radio access network (RAN) infrastructure, to maximize the use of the available bandwidth in space. One of the major issues of this new architecture is the proximity of many base stations (BS) and the management of the interference they generate on each other's cell. Such constraints makes scientific community focus on Self-Optimized, Self-Organized Networks (SON) that allow network elements to optimize them-selves through decentralized decisions (no static network planning is required). A major interest of SON is their capability to scale to large and non-organized networks, as well as being able to adapt them-selves dynamically, by using distributed algorithms. In this context, this thesis proposes the study of two resource allocation problems. The first part of this thesis focuses on the optimisation of resource sharing, in the context of coordinated multi-points transmissions (CoMP). Performances of BS coordination are evaluated, using the uniform capacity criterion, as well as the trade-off between total capacity and fairness among users. We also propose a generalized and distributed method to select the set of coordination of BS, to optimize the capacity-fairness trade-off. In the second part of this thesis, we focus on optimizing the transmit power and resource allocation, in order to reduce electric consumption. We present two distributed algorithms: the first one is based on a stochastic optimisation (using Gibbs sampling), and tries to reach the global optimum state through decentralized decision. The second one is based on control theory, and uses target tracking as well as model predictive control to allocate resources and power in a dynamic channel scenario. In many cases, trade-offs are to be maid between opposite objectives when evaluating network performances (total throughput, fairness, energy consumption, etc.). In this thesis, we present most of the network performances using multi-objectives evaluations.Cette thèse s'intéresse aux problèmes d'allocations des ressources et de puissance dans les réseaux cellulaires de quatrième génération (4G). Pour faire face à la demande continuellement croissante en débit des utilisateurs mobiles, les opérateurs n'ont d'autre choix que de densifier leurs infrastructures d'accès au réseau radio (RAN), afin de maximiser l'utilisation de la bande passante disponible dans l'espace. Un des défis de cette nouvelle architecture est la coexistence de nombreuses cellules voisines et la gestion des interférences co-canal qu'elles génèrent entre elles. De telles contraintes ont amené la communauté scientifique à s'intéresser aux réseaux auto-organisés et auto-optimisés (SON), qui permettent aux réseaux de s'optimiser localement via des décisions décentralisées (sans planification statique). L'intérêt principal de tels réseaux est le passage à l'échelle des algorithmes distribués et la possibilité de s'adapter dynamiquement à de nouveaux environnements. Dans cette optique, nous proposons l'étude de deux problèmes d'allocation de ressources. La première partie de cette thèse se concentre sur l'optimisation de l'usage des ressources, dans un contexte de transmission coordonnée par plusieurs stations de base (CoMP). Les performances de la coordination de stations de base sont évaluées, selon le critère de capacité uniforme, ainsi que le compromis entre l'efficacité spectrale et l'équité entre les utilisateurs. Nous proposons également une méthode généralisée et distribuée de sélection de l'ensemble de stations en coopération, afin d'optimiser le compromis efficacité-équité. Dans une seconde partie, nous nous intéressons à l'optimisation de l'allocation des ressources et de puissance, dans le but de minimiser la consommation électrique du réseau. Nous présentons deux algorithmes dont les décisions sont décentralisées. Le premier est basé sur une optimisation stochastique (via l'échantillonneur de Gibbs) et permet une optimisation globale du système. Le second quant à lui est basé sur l'adaptation de la théorie du contrôle et utilise des modèles prédictifs et la poursuite de cibles pour allouer les ressources et les puissances dans un contexte de canaux et d'interférences dynamiques. Dans de nombreux cas, plusieurs objectifs concurrents sont à considérer pour évaluer les performances d'un réseau (capacité totale, équité, consommation électrique, etc.). Dans le cadre de cette thèse, nous nous efforçons à présenter les résultats sous la forme de compromis multi-objectifs

Radio resource sharing optimisation for self-organized networks

Cette thèse s'intéresse aux problèmes d'allocations des ressources et de puissance dans les réseaux cellulaires de quatrième génération (4G). Pour faire face à la demande continuellement croissante en débit des utilisateurs mobiles, les opérateurs n'ont d'autre choix que de densifier leurs infrastructures d'accès au réseau radio (RAN), afin de maximiser l'utilisation de la bande passante disponible dans l'espace. Un des défis de cette nouvelle architecture est la coexistence de nombreuses cellules voisines et la gestion des interférences co-canal qu'elles génèrent entre elles. De telles contraintes ont amené la communauté scientifique à s'intéresser aux réseaux auto-organisés et auto-optimisés (SON), qui permettent aux réseaux de s'optimiser localement via des décisions décentralisées (sans planification statique). L'intérêt principal de tels réseaux est le passage à l'échelle des algorithmes distribués et la possibilité de s'adapter dynamiquement à de nouveaux environnements. Dans cette optique, nous proposons l'étude de deux problèmes d'allocation de ressources. La première partie de cette thèse se concentre sur l'optimisation de l'usage des ressources, dans un contexte de transmission coordonnée par plusieurs stations de base (CoMP). Les performances de la coordination de stations de base sont évaluées, selon le critère de capacité uniforme, ainsi que le compromis entre l'efficacité spectrale et l'équité entre les utilisateurs. Nous proposons également une méthode généralisée et distribuée de sélection de l'ensemble de stations en coopération, afin d'optimiser le compromis efficacité-équité. Dans une seconde partie, nous nous intéressons à l'optimisation de l'allocation des ressources et de puissance, dans le but de minimiser la consommation électrique du réseau. Nous présentons deux algorithmes dont les décisions sont décentralisées. Le premier est basé sur une optimisation stochastique (via l'échantillonneur de Gibbs) et permet une optimisation globale du système. Le second quant à lui est basé sur l'adaptation de la théorie du contrôle et utilise des modèles prédictifs et la poursuite de cibles pour allouer les ressources et les puissances dans un contexte de canaux et d'interférences dynamiques. Dans de nombreux cas, plusieurs objectifs concurrents sont à considérer pour évaluer les performances d'un réseau (capacité totale, équité, consommation électrique, etc.). Dans le cadre de cette thèse, nous nous efforçons à présenter les résultats sous la forme de compromis multi-objectifs.This thesis focuses on resources and power allocation problem in the fourth generation (4G) of cellular networks. To face the continuous growth of mobile users capacity requirements, operators need to densify their radio access network (RAN) infrastructure, to maximize the use of the available bandwidth in space. One of the major issues of this new architecture is the proximity of many base stations (BS) and the management of the interference they generate on each other's cell. Such constraints makes scientific community focus on Self-Optimized, Self-Organized Networks (SON) that allow network elements to optimize them-selves through decentralized decisions (no static network planning is required). A major interest of SON is their capability to scale to large and non-organized networks, as well as being able to adapt them-selves dynamically, by using distributed algorithms. In this context, this thesis proposes the study of two resource allocation problems. The first part of this thesis focuses on the optimisation of resource sharing, in the context of coordinated multi-points transmissions (CoMP). Performances of BS coordination are evaluated, using the uniform capacity criterion, as well as the trade-off between total capacity and fairness among users. We also propose a generalized and distributed method to select the set of coordination of BS, to optimize the capacity-fairness trade-off. In the second part of this thesis, we focus on optimizing the transmit power and resource allocation, in order to reduce electric consumption. We present two distributed algorithms: the first one is based on a stochastic optimisation (using Gibbs sampling), and tries to reach the global optimum state through decentralized decision. The second one is based on control theory, and uses target tracking as well as model predictive control to allocate resources and power in a dynamic channel scenario. In many cases, trade-offs are to be maid between opposite objectives when evaluating network performances (total throughput, fairness, energy consumption, etc.). In this thesis, we present most of the network performances using multi-objectives evaluations

Joint Coordinated Multicell Processing and MIMO: Selection of Base Stations and Gain

Abstract—In this paper, we provide the analysis of the downlink Coordinated Multiple Point (CoMP) used in conjunction with the basic MIMO. The CoMP is the joint multi-cell transmission from several BS to mobiles, coupled here to an open-loop MIMO technique that does not require the perfect channel state knowledge. We show by simulation, that even for 4 × 4 MIMO transmission, the CoMP can improve the spectral efficiency for some mobiles, depending on capacity outage requirements