Implicit Coordination in Two-Agent Team Problems; Application to Distributed Power Allocation

The central result of this paper is the analysis of an optimization problem which allows one to assess the limiting performance of a team of two agents who coordinate their actions. One agent is fully informed about the past and future realizations of a random state which affects the common payoff of the agents whereas the other agent has no knowledge about the state. The informed agent can exchange his knowledge with the other agent only through his actions. This result is applied to the problem of distributed power allocation in a two-transmitter $M-$band interference channel, $M\geq 1$, in which the transmitters (who are the agents) want to maximize the sum-rate under the single-user decoding assumption at the two receivers; in such a new setting, the random state is given by the global channel state and the sequence of power vectors used by the informed transmitter is a code which conveys information about the channel to the other transmitter.Comment: 6 pages, appears as WNC3 2014: International Workshop on Wireless Networks: Communication, Cooperation and Competition - International Workshop on Resource Allocation, Cooperation and Competition in Wireless Network

Implicit Coordination in Two-Agent Team Problems; Application to Distributed Power Allocation

Abstract-The central result of this paper is the analysis of an optimization problem which allows one to assess the limiting performance of a team of two agents who coordinate their actions. One agent is fully informed about the past and future realizations of a random state which affects the common payoff of the agents whereas the other agent has no knowledge about the state. The informed agent can exchange his knowledge with the other agent only through his actions. This result is applied to the problem of distributed power allocation in a two-transmitter M −band interference channel, M ≥ 1, in which the transmitters (who are the agents) want to maximize the sum-rate under the single-user decoding assumption at the two receivers; in such a new setting, the random state is given by the global channel state and the sequence of power vectors used by the informed transmitter is a code which conveys information about the channel to the other transmitter

Association of SUMOlation Pathway Genes With Stroke in a Genome-wide Association Study in India

OBJECTIVE: To undertake a genome-wide association study (GWAS) to identify genetic variants for stroke in an Indian population. METHODS: In a hospital-based case-control study, 8 teaching hospitals in India recruited 4,088 participants, including 1,609 stroke cases. Imputed genetic variants were tested for association with stroke subtypes using both single-marker and gene-based tests. Association with vascular risk factors was performed with logistic regression. Various databases were searched for replication, functional annotation, and association with related traits. Status of candidate genes previously reported in the Indian population was also checked. RESULTS: Associations of vascular risk factors with stroke were similar to previous reports and show modifiable risk factors such as hypertension, smoking, and alcohol consumption as having the highest effect. Single-marker–based association revealed 2 loci for cardioembolic stroke (1p21 and 16q24), 2 for small vessel disease stroke (3p26 and 16p13), and 4 for hemorrhagic stroke (3q24, 5q33, 6q13, and 19q13) at p < 5 × 10(−8). The index single nucleotide polymorphism of 1p21 is an expression quantitative trait locus (p(lowest) = 1.74 × 10(−58)) for RWDD3 involved in SUMOylation and is associated with platelet distribution width (1.15 × 10(−9)) and 18-carbon fatty acid metabolism (p = 7.36 × 10(−12)). In gene-based analysis, we identified 3 genes (SLC17A2, FAM73A, and OR52L1) at p < 2.7 × 10(−6). Eleven of 32 candidate gene loci studied in an Indian population replicated (p < 0.05), and 21 of 32 loci identified through previous GWAS replicated according to directionality of effect. CONCLUSIONS: This GWAS of stroke in an Indian population identified novel loci and replicated previously known loci. Genetic variants in the SUMOylation pathway, which has been implicated in brain ischemia, were identified for association with stroke

Développement et application des bornes issues de la théorie de l'information à certains types de problèmes de coordination

With the rise in connectivity between appliances (Internet of Things), new avenues for coordination between various entities have opened up. At the same time, recent information theoretical results have provided bounds for the performance that any coordination scheme could achieve under certain information structures. In this thesis, we further develop those information theoretical results with the aim of making them applicable more easily to practical problems. In this regard, the contribution of this thesis is twofold: 1) Further developing the aforementioned information theoretical results to provide insights into the structure of the solutions to optimization problem posed in them, as well as generalizing some results. 2) Developing algorithms which exploit the theoretical framework provided by Information theory to devise practical, decentralized and robust coordination schemes. The generality of the approach lends itself to various applications, of which the following were treated: power optimization in wireless networks, power consumption scheduling in smart grid applications, as well as Witsenhausen counterexample, an important toy problem in control theory. Various opportunities still lie ahead to exploit the framework and tools developed herein. Indeed, they could be useful even in domains which have not been explored in this thesis but which require coordination between agents with different information available to each.Avec la montée de la connectivité entre les appareils (internet des objets), nouvelles possibilités de coordination entre les différentes entités ont ouvert. En même temps, des résultats récents, issus de la théorie de l'information, ont fourni des limites pour la performance optimale que tout système de coordination pourrait atteindre sous certaines structures d'information. Dans cette thèse, nous développons ces résultats théoriques dans le but de les rendre plus facilement applicable aux problèmes pratiques. À cet égard, la contribution de cette thèse est double : 1) En outre développer les résultats théoriques pour fournir un aperçu de la structure des solutions au problème d'optimisation posés dans les travaux antérieurs, ainsi que la généralisation des résultats. 2) Développer des algorithmes qui exploitent le cadre théorique fourni par les travaux antérieurs pour concevoir des mécanismes de coordination pratiques, décentralisées et robustes. La généralité de l'approche se prête à diverses applications, dont les éléments suivants ont été traités: optimisation de puissance dans les réseaux sans fil, planification de la consommation d'énergie dans les applications de réseau intelligent, ainsi que Witsenhausen contre-exemple, un problème important issu de la théorie du contrôle. Diverses possibilités sont encore à venir pour exploiter le cadre et les outils développés ici. En effet, ils pourraient être utiles même dans des domaines qui ne sont pas abordés dans cette thèse, mais qui nécessitent une coordination entre les agents avec des informations différentes à la disposition de chacun

A framework for computing power consumption scheduling functions under uncertainty

International audience— One of the goals of this paper is to make a step further towards knowing how an electrical appliance should exploit the available information to schedule its power consumption; mainly, this information corresponds here to an imperfect forecast of the non-controllable (exogenous) load or electricity price. Reaching this goal led us to three key results which can be used for other settings which involve multiple agents with partial information: 1. In terms of modeling, we exploit the principal component analysis to approximate the exogenous load and show its full relevance; 2. Under some reasonable but improvable assumptions, this work provides a full characterization of the set of feasible payoffs which can be reached by a set of appliances having partial information; 3. A distributed algorithm is provided to compute good power consumption scheduling functions. These results are exploited in the numerical analysis, which provides several new insights into the power consumption scheduling problem. We provide first results for the standard cost functions, transformer aging in particular, where we compare our method with iterative water filling algorithm (IWFA). We test our proposed algorithm on real data and show that it is more robust with respect to noise in the signals received. We also observe that our proposed method becomes even more relevant when the proportion of appliances with smart counters increase

Distributed Power Control with Partial Channel State Information: Performance Characterization and Design

International audienceOne of the goals of this paper is to contribute to finding distributed power control strategies which exploit efficiently the information available about the global channel state; it may be local or noisy. A suited way of measuring the global efficiency of a distributed power control scheme is to use the long-term utility region. First, we provide the utility region characterization for general utility functions when the channel state obeys an independent block fading law and the observation structure is memoryless. Second, the corresponding theorem is exploited to construct an iterative algorithm which provides one-shot power control strategies. The performance of the proposed algorithm is assessed for energy-efficient and spectrally efficient communications and shown to perform much better than state-of-the-art techniques, with the additional advantage of being applicable even in the presence of arbitrary observation structures such as those corresponding to noisy channel gain estimates

Efficient 3D Placement of UAVs with QoS assurance in Ad Hoc Wireless Networks

International audienceIn this work, we consider a wireless communication system consisting of multiple rotary-wing unmanned aerial vehicles (UAVs) used as aerial base stations (ABSs) in order to provide downlink connectivity to the user terminals (UEs) on the ground. Towards investigating power efficient deployment strategies for such a system, the contribution of this article is twofold: we formalize the relevant multi-objective optimization problem, and secondly develop Particle Swarm Optimization (PSO) based techniques for optimization of the individual objectives, which are then exploited in an iterative manner. The relevant optimization objectives for reducing the total power consumed are the number of base stations (BSs) and their transmit powers. The optimization is performed while assuring minimum quality-of-service constraints (QoSs) such as per-user coverage probability and per-user rate. Through system level simulations, we show that the developed approach ensures great reductions for both the number of base stations as well as their individual transmit power, thus saving initial deployment cost as well as reducing operational costs induced due to energy consumption

A framework for optimal decentralized power control with partial CSI

International audience— In this paper, we use a recent information theoretical result to develop a general framework for finding optimal power control policies in the case of interference channels. The aforementioned result characterizes the achievable payoffs for an N-Agent (transmitters in our application) coordination problem with a certain information structure. We then provide an algorithm which exploits the characterization of achievable payoffs by conditional probability distributions to find optimal decision functions for the transmitters. Due to its general nature, the developed framework is conducive for applications to diverse scenarios in wireless communications. In this article, we restrict our attention to the case of decentralized power control in interference channels for different utility functions namely sum-rate, sum-energy and sum-goodput. Our approach has the following salient features: 1) The method proposes optimal power control functions for any given utility function as opposed to ad-hoc solutions for different utilities proposed in the literature, and 2) Noise in the channel estimation is taken into account, thus providing robust optimal solutions