Distributed Diffusion-Based LMS for Node-Specific Adaptive Parameter Estimation

A distributed adaptive algorithm is proposed to solve a node-specific parameter estimation problem where nodes are interested in estimating parameters of local interest, parameters of common interest to a subset of nodes and parameters of global interest to the whole network. To address the different node-specific parameter estimation problems, this novel algorithm relies on a diffusion-based implementation of different Least Mean Squares (LMS) algorithms, each associated with the estimation of a specific set of local, common or global parameters. Coupled with the estimation of the different sets of parameters, the implementation of each LMS algorithm is only undertaken by the nodes of the network interested in a specific set of local, common or global parameters. The study of convergence in the mean sense reveals that the proposed algorithm is asymptotically unbiased. Moreover, a spatial-temporal energy conservation relation is provided to evaluate the steady-state performance at each node in the mean-square sense. Finally, the theoretical results and the effectiveness of the proposed technique are validated through computer simulations in the context of cooperative spectrum sensing in Cognitive Radio networks.Comment: 13 pages, 6 figure

Contributions of formal language theory to the study of dialogues

For more than 30 years, the problem of providing a formal framework for modeling dialogues has been a topic of great interest for the scientific areas of Linguistics, Philosophy, Cognitive Science, Formal Languages, Software Engineering and Artificial Intelligence. In the beginning the goal was to develop a "conversational computer", an automated system that could engage in a conversation in the same way as humans do. After studies showed the difficulties of achieving this goal Formal Language Theory and Artificial Intelligence have contributed to Dialogue Theory with the study and simulation of machine to machine and human to machine dialogues inspired by Linguistic studies of human interactions. The aim of our thesis is to propose a formal approach for the study of dialogues. Our work is an interdisciplinary one that connects theories and results in Dialogue Theory mainly from Formal Language Theory, but also from another areas like Artificial Intelligence, Linguistics and Multiprogramming. We contribute to Dialogue Theory by introducing a hierarchy of formal frameworks for the definition of protocols for dialogue interaction. Each framework defines a transition system in which dialogue protocols might be uniformly expressed and compared. The frameworks we propose are based on finite state transition systems and Grammar systems from Formal Language Theory and a multi-agent language for the specification of dialogue protocols from Artificial Intelligence. Grammar System Theory is a subfield of Formal Language Theory that studies how several (a finite number) of language defining devices (language processors or grammars) jointly develop a common symbolic environment (a string or a finite set of strings) by the application of language operations (for instance rewriting rules). For the frameworks we propose we study some of their formal properties, we compare their expressiveness, we investigate their practical application in Dialogue Theory and we analyze their connection with theories of human-like conversation from Linguistics. In addition we contribute to Grammar System Theory by proposing a new approach for the verification and derivation of Grammar systems. We analyze possible advantages of interpreting grammars as multiprograms that are susceptible of verification and derivation using the Owicki-Gries logic, a Hoare-based logic from the Multiprogramming field

Energy Efficiency Optimization in Green Wireless Communications

The rising energy concern and the ubiquity of energy-consuming wireless applications have sparked a keen interest in the development and deployment of energy-efficient and eco-friendly wireless communication technology. Green Wireless Communications aims to find innovative solutions to improve energy efficiency, and to relieve/reduce the carbon footprint of wireless industry, while maintaining/improving performance metrics. Looking back at the wireless communications of the past decades, the air-interface design and network deployment had mainly focused on the spectral efficiency, instead of energy efficiency. From the cellular network to the personal area network, no matter what size the wireless network is, the milestones along the evolutions of wireless networks had always been higher-and-higher data rates throughout these years. Most of these throughput-oriented optimizations lead to a full-power operation to support a higher throughput or spectral efficiency, which is typically not energy-efficient. To qualify as green wireless communications, we believe that a candidate technology needs to be of high energy efficiency, reduced electromagnetic pollution, and low-complexity. In this dissertation research, towards the evolution of the green wireless communications, we have extended our efforts in two important aspects of the wireless communications system: air-interface and networking. In the first aspect of this work, we study a promising green communications technology, the time reversal system, as a novel air-interface of the future green wireless communications. We propose a concept of time reversal division multiple access (TRDMA) as a novel wireless media access scheme for wireless broadband networks, and investigate its fundamental theoretical limits. Motivated by the great energy-harvesting potential of the TRDMA, we develop an asymmetric architecture for the TRDMA based multiuser networks. The unique asymmetric architecture shifts the most complexity to the BS in both downlink and uplink schemes, facilitating very low-cost terminal users in the networks. To further enhance the system performance, a 2D parallel interference cancellation scheme is presented to explore the inherent structure of the interference signals, and therefore efficiently improve the resulting SINR and system performance. In the second aspect of this work, we explore the energy-saving potential of the cooperative networking for cellular systems. We propose a dynamic base-station switching strategy and incorporate the cooperative base-station operation to improve the energy-efficiency of the cellular networks without sacrificing the quality of service of the users. It is shown that significant energy saving potential can be achieved by the proposed scheme

Cognitive Orthogonal Precoder for Two-tiered Networks Deployment

In this work, the problem of cross-tier interference in a two-tiered (macro-cell and cognitive small-cells) network, under the complete spectrum sharing paradigm, is studied. A new orthogonal precoder transmit scheme for the small base stations, called multi-user Vandermonde-subspace frequency division multiplexing (MU-VFDM), is proposed. MU-VFDM allows several cognitive small base stations to coexist with legacy macro-cell receivers, by nulling the small- to macro-cell cross-tier interference, without any cooperation between the two tiers. This cleverly designed cascaded precoder structure, not only cancels the cross-tier interference, but avoids the co-tier interference for the small-cell network. The achievable sum-rate of the small-cell network, satisfying the interference cancelation requirements, is evaluated for perfect and imperfect channel state information at the transmitter. Simulation results for the cascaded MU-VFDM precoder show a comparable performance to that of state-of-the-art dirty paper coding technique, for the case of a dense cellular layout. Finally, a comparison between MU-VFDM and a standard complete spectrum separation strategy is proposed. Promising gains in terms of achievable sum-rate are shown for the two-tiered network w.r.t. the traditional bandwidth management approach.Comment: 11 pages, 9 figures, accepted and to appear in IEEE Journal on Selected Areas in Communications: Cognitive Radio Series, 2013. Copyright transferred to IEE

Cooperative tracking for persistent littoral undersea surveillance

Thesis (Nav. E.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.Includes bibliographical references (leaves 39-40).The US Navy has identified a need for an autonomous, persistent, forward deployed system to Detect, Classify, and Locate submarines. In this context, we investigate a novel method for multiple sensor platforms acting cooperatively to locate an uncooperative target. Conventional tracking methods based on techniques such as Kalman filtering or particle filters have been used with great success for tracking targets from a single manned platform; the application of these methods can be difficult for a cooperative tracking scenario with multiple unmanned platforms that have considerable navigation error. This motivates investigation of an alternative, set-based tracking algorithm, first proposed by Detweiler et al. for sensor network localization, to the cooperative tracking problem. The Detweiler algorithm is appealing for its conceptual simplicity and minimal assumptions about the target motion. The key idea of this approach is to compute the temporal evolution of potential target positions in terms of bounded regions that grow between measurements as the target moves and shrink when measurements do occur based on an assumed worst-case bound for uncertainty.(cont.) In this thesis, we adapt the Detweiler algorithm to the scenario of cooperative tracking for persistent undersea surveillance, and explore its limitations when applied to this domain. The algorithm has been fully implemented and tested both in simulation and with postprocessing of autonomous surface craft (ASC) data from the PLUSNet Monterey Bay 2006 experiment. The results indicate that the method provides disappointing performance when applied to this domain, especially in situations where communication links between the autonomous tracking platforms are poor. We conclude that the method is more appropriate for a "large N" tracking scenario, with a large number of small, expendable tracking nodes, instead of our intended scenario with a smaller number of more sophisticated mobile trackers. The method may also be useful as an adjunct to a conventional Bayesian tracker, to reject implausible target tracks and focus computational resources on regions where the target is present.by Robert Derek Scott.S.M.Nav.E

Finite-SNR Diversity-Multiplexing-Delay Tradeoff in Half-Duplex Hybrid ARQ Relay Channels

International audienceIn this paper, we consider a delay-limited hybrid automatic repeat request (HARQ) protocol that makes use of incremental redundancy over the three-node decode-and-forward (DF) relay fading channel where one source cooperates with a relay to transmit information to the destination. We provide an estimate of the diversity-multiplexing tradeoff (DMT) at finite signal to noise ratio (SNR) based on tight bounds on outage probabilities for two channel models. The results for the long term quasi-static channel highlight the distributed diversity, ie. the cooperative space diversity, and the HARQ coding gain, achieved by soft combining the successive transmitted punctured codewords via incremental redundancy. On the other hand, the results for the short term quasi-static channel illustrate the diversity gains obtained thanks to cooperative space diversity and time diversity, along with the HARQ coding gain. Using the DMT formulation, we show that equal power partitioning between the source and the relay nodes provides close to optimal performance. Furthermore, thanks to the extension of the finite-SNR DMT to the finite-SNR diversity-multiplexing-delay tradeoff, we show that, unlike the asymptotic SNR analysis, the ARQ delay, defined as the number of retransmissions rounds, impacts the performance of the HARQ relay protocol for high effective multiplexing gain