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Selected Areas in Communications, IEEE Journal on

Issue 4 • Date May 2008

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Displaying Results 1 - 18 of 18
  • IEEE Journal on Selected Areas in Communications - May 2008 [Contents Continued on Back Cover]

    Publication Year: 2008 , Page(s): C1
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    Freely Available from IEEE
  • IEEE Communications Society

    Publication Year: 2008 , Page(s): C2
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  • Guest Editorial Control and Communications

    Publication Year: 2008 , Page(s): 577 - 579
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (521 KB)  

    The 13 papers in this special issue focus on control and communications. The papers are summarized here. View full abstract»

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  • On the design of globally optimal communication strategies for real-time noisy communication systems with noisy feedback

    Publication Year: 2008 , Page(s): 580 - 595
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (759 KB) |  | HTML iconHTML  

    A real-time communication system with noisy feedback is considered. The system consists of a Markov source, forward and backward discrete memoryless channels, and a receiver with limited memory. The receiver can send messages to the encoder over the backward noisy channel. The encoding at the encoder and the decoding, the feedback, and the memory update at the receiver must be done in real-time. A distortion metric that does not tolerate delays is given. The objective is to design an optimal real-time communication strategy, i.e., design optimal real-time encoding, decoding, feedback, and memory update strategies to minimize a total expected distortion over a finite horizon. This problem is formulated as a decentralized stochastic optimization problem and a methodology for its sequential decomposition is presented. This results in a set of nested optimality equations that can be used to sequentially determine optimal communication strategies. The methodology exponentially simplifies the search for determining an optimal real-time communication strategy. View full abstract»

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  • Joint preprocessing and feedback strategies for perfectly reconstructing equalizers

    Publication Year: 2008 , Page(s): 596 - 608
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (748 KB) |  | HTML iconHTML  

    In this paper we consider the transmission of discrete-valued data via a communication channel that is subject to (additive) noise with a known upper bound on its magnitude but otherwise completely unrestricted and unknown behavior. We consider a discrete-time setup and extend previous equalization strategies for perfect reconstruction by allowing linear preprocessing of the data and/or linear feedback from the receiver to the transmitter. We are interested in the characterization of general conditions that allow perfect reconstruction of the discrete data with any given (possibly nonzero) delay (and under all possible realizations of channel noise and a limit on the power of transmission) when linear preprocessing of the data and/or linear feedback from the receiver is employed. In particular, we obtain necessary and sufficient conditions for perfect reconstruction under either linear power-limited preprocessing or linear power- limited preprocessing along with linear feedback. We prove that in order to improve the conditions for perfect reconstruction, it is necessary that the feedback and preprocessing systems are unstable. We also consider the case when a Decision Feedback Equalizer (DFE) structure is imposed at the receiver and provide necessary conditions for improvements in the perfect reconstruction in terms of l1 norms of appropriate maps. In addition, a procedure that results in parametric l1 optimization is developed to design a DFE to improve the maximum tolerable noise bound. View full abstract»

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  • A distributed minimum variance estimator for sensor networks

    Publication Year: 2008 , Page(s): 609 - 621
    Cited by:  Papers (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2007 KB) |  | HTML iconHTML  

    A distributed estimation algorithm for sensor networks is proposed. A noisy time-varying signal is jointly tracked by a network of sensor nodes, in which each node computes its estimate as a weighted sum of its own and its neighbors' measurements and estimates. The weights are adaptively updated to minimize the variance of the estimation error. Both estimation and the parameter optimization is distributed; no central coordination of the nodes is required. An upper bound of the error variance in each node is derived. This bound decreases with the number of neighboring nodes. The estimation properties of the algorithm are illustrated via computer simulations, which are intended to compare our estimator performance with distributed schemes that were proposed previously in the literature. The results of the paper allow to trading-off communication constraints, computing efforts and estimation quality for a class of distributed filtering problems. View full abstract»

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  • Distributed Kalman filtering based on consensus strategies

    Publication Year: 2008 , Page(s): 622 - 633
    Cited by:  Papers (84)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (929 KB) |  | HTML iconHTML  

    In this paper, we consider the problem of estimating the state of a dynamical system from distributed noisy measurements. Each agent constructs a local estimate based on its own measurements and on the estimates from its neighbors. Estimation is performed via a two stage strategy, the first being a Kalman-like measurement update which does not require communication, and the second being an estimate fusion using a consensus matrix. In particular we study the interaction between the consensus matrix, the number of messages exchanged per sampling time, and the Kalman gain for scalar systems. We prove that optimizing the consensus matrix for fastest convergence and using the centralized optimal gain is not necessarily the optimal strategy if the number of exchanged messages per sampling time is small. Moreover, we show that although the joint optimization of the consensus matrix and the Kalman gain is in general a non-convex problem, it is possible to compute them under some relevant scenarios. We also provide some numerical examples to clarify some of the analytical results and compare them with alternative estimation strategies. View full abstract»

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  • Randomized consensus algorithms over large scale networks

    Publication Year: 2008 , Page(s): 634 - 649
    Cited by:  Papers (73)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (557 KB) |  | HTML iconHTML  

    Various randomized consensus algorithms have been proposed in the literature. In some case randomness is due to the choice of a randomized network communication protocol. In other cases, randomness is simply caused by the potential unpredictability of the environment in which the distributed consensus algorithm is implemented. Conditions ensuring the convergence of these algorithms have already been proposed in the literature. As far as the rate of convergence of such algorithms, two approaches can be proposed. One is based on a mean square analysis, while a second is based on the concept of Lyapunov exponent. In this paper, by some concentration results, we prove that the mean square convergence analysis is the right approach when the number of agents is large. Differently from the existing literature, in this paper we do not stick to average preserving algorithms. Instead, we allow to reach consensus at a point which may differ from the average of the initial states. The advantage of such algorithms is that they do not require bidirectional communication among agents and thus they apply to more general contexts. Moreover, in many important contexts it is possible to prove that the displacement from the initial average tends to zero, when the number of agents goes to infinity. View full abstract»

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  • Distributed function calculation and consensus using linear iterative strategies

    Publication Year: 2008 , Page(s): 650 - 660
    Cited by:  Papers (39)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (415 KB) |  | HTML iconHTML  

    Given an arbitrary network of interconnected nodes, we develop and analyze a distributed strategy that enables a subset of the nodes to calculate any given function of the node values. Our scheme utilizes a linear iteration where, at each time-step, each node updates its value to be a weighted average of its own previous value and those of its neighbors. We show that this approach can be viewed as a linear dynamical system, with dynamics that are given by the weight matrix of the linear iteration, and with outputs for each node that are captured by the set of values that are available to that node at each time-step. In connected networks with time-invariant topologies, we use observability theory to show that after running the linear iteration for a finite number of time-steps with almost any choice of weight matrix, each node obtains enough information to calculate any arbitrary function of the initial node values. The problem of distributed consensus via linear iterations, where all nodes in the network calculate the same function, is treated as a special case of our approach. In particular, our scheme allows nodes in connected networks with time-invariant topologies to reach consensus on any arbitrary function of the initial node values in a finite number of steps for almost any choice of weight matrix. View full abstract»

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  • Optimizing controller location in networked control systems with packet drops

    Publication Year: 2008 , Page(s): 661 - 671
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (605 KB) |  | HTML iconHTML  

    In networked control, there is locational freedom in choosing the node at which to locate the controller, so as to mitigate the effects of packet losses in the network. What is the optimal location for the placement of the control logic? Second, what is the optimal control law in that position? The difficulty in answering these two questions is that analysis of optimality in networked control systems subject to random packet drops suffers from Witsenhausen's 'non-classical information pattern'. Thus, the general problem is considered intractable. We make headway on this problem by using a "Long Packet Assumption", LPA, which allows packets to be arbitrarily long. This is not intended for implementation, but only to develop a lower bound on the cost. In particular, under this assumption the optimal controller location can be shown to be collocated with the actuator. For this position, under the LPA, we can also calculate the optimal cost, which is then a lower bound on the optimal cost for the original problem for all locations. Despite the apparent strength of the LPA, we have found that this lower bound is often close to currently realizable upper bounds. This establishes the near optimality of currently implementable controllers in such instances. Using the lower bound on cost we obtain a necessary condition for stabilizability over all controller locations. This condition matches known sufficient conditions for some special cases, thus establishing a necessary and sufficient condition for location optimized stabilizability of networked control systems with packet loss. View full abstract»

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  • Control over unreliable networks affected by packet erasures and variable transmission delays

    Publication Year: 2008 , Page(s): 672 - 685
    Cited by:  Papers (17)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (706 KB) |  | HTML iconHTML  

    This paper describes a novel control strategy aimed at achieving good performance over an unreliable communication network affected by packet loss and variable transmission delays. The key ingredient in the method described here is to use the large data packet frame size of typical modern communication protocols to transmit control sequences which cover multiple data-dropout and delay scenarios. Stability and performance of the resultant scheme are addressed under nominal networked conditions. Simulations verify that the strategy performs exceptionally well under realistic conditions with noise and unmeasured disturbances. View full abstract»

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  • Zero-error target tracking with limited communication

    Publication Year: 2008 , Page(s): 686 - 694
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (868 KB) |  | HTML iconHTML  

    We study the problem of target tracking in a sensor network environment. In particular, we consider a target that moves according to a Markov chain, and a tracker that queries sets of sensors to obtain tracking information. We are interested in finding the minimum number of queries per time step such that a target is trackable under three different requirements. First we investigate the case where the tracker is required to know the exact location of the target at each time step. We then relax this requirement and explore the case where the tracker may lose track of the target at a given time step, but it is able to ";catch-up"; at a later time, regaining up-to-date information about the target's track. Finally, we consider the case where tracking information is only known after a delay of d time steps. We provide necessary and sufficient conditions on the number of queries per time step to track in the above three cases. These conditions are stated in terms of the entropy rate of the target's Markov chain. View full abstract»

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  • Integration of communication and control using discrete time Kuramoto models for multivehicle coordination over broadcast networks

    Publication Year: 2008 , Page(s): 695 - 705
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (713 KB) |  | HTML iconHTML  

    This paper considers the integration of communication and control with respect to the task of coordinated heading control for a group of N vehicles with the energy efficiency of communications in mind. The heading control employed on each vehicle is a discretization of the well-known Kuramoto model of nonlinearly coupled oscillators over a sequence of logical graphs. Stability for both all-to-all and random one- to-all broadcasts is shown to be dependent on the coupling strength, K, and the time discretization, DeltaT. For desired system performance characteristics, DeltaT imposes a tight deadline by which the state information (M bits) must be propagated through the communication network. Routing optimization with respect to minimizing energy consumption is formulated considering the DeltaT deadline. Due to the tight time deadline, a one-to-all single- hop broadcasting scheme is shown to be more energy efficient for practical choices of M/DeltaT. The proposed modularization is illustrated via a set of simulations where the overall communication energy to reach alignment is optimized. View full abstract»

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  • A novel Hα control strategy for design of a robust dynamic routing algorithm in traffic networks

    Publication Year: 2008 , Page(s): 706 - 718
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1990 KB) |  | HTML iconHTML  

    In this paper novel centralized and decentralized routing control strategies based on minimization of the worst-case queuing length are proposed. The centralized routing problem is formulated as an Hinfin optimal control problem to achieve a robust routing performance in presence of multiple and unknown fast time-varying network delays. Unlike similar previous work in the literature the delays in the queuing model are assumed to be unknown and time-varying. A Linear Matrix Inequality (LMI) constraint is obtained to design a delay-dependent Hinfin controller. The physical constraints that are present in the network are then expressed as LMI feasibility conditions. Our proposed centralized routing scheme is then reformulated in a decentralized frame work. This modification yields an algorithm that obtains the "fastest route", increases the robustness against multiple unknown time-varying delays, and enhances the scalability of the algorithm to large scale traffic networks. Simulation results are presented to illustrate and demonstrate the effectiveness and capabilities of our proposed novel dynamic routing strategies. View full abstract»

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  • The end-to-end rate control in multiple-hop wireless networks: Cross-layer formulation and optimal allocation

    Publication Year: 2008 , Page(s): 719 - 731
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (859 KB) |  | HTML iconHTML  

    In this paper, we study the theoretical problem of the end-to-end rate assignment for multi-hop wireless networks. Specifically, we consider the problem of joint congestion control, random access and power control design with multi-hop transmissions and interference-limited link rates. In order to address both the end-to-end throughput maximization and energy efficiency, we formulate this problem into a cross-layer design problem under a realistic interference-based communication model, which captures the attainable link capacity in practice. There are primarily three challenges in this design: 1) how to formulate the cross-layer design; 2) how to solve the non- convex and non-separable problem efficiently; more importantly 3) under a reasonably complexity, how to design a distributed algorithm that can realize this formulation while maintaining the architectural modularity among different layers. First, we propose a novel method that can convert a non- convex and non-separable programming into an equivalent convex programming problem. The problem is solved by a dual decomposition technique. We show that the resulting algorithm can be practically realized. We then design a distributed algorithm that jointly considers random access and power control to adapt for the transport layer congestion status. Simulation results confirm that the proposed algorithm can achieve close to the global optimum within reasonable convergence times. View full abstract»

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  • An on-line learning algorithm for energy efficient delay constrained scheduling over a fading channel

    Publication Year: 2008 , Page(s): 732 - 742
    Cited by:  Papers (25)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (579 KB) |  | HTML iconHTML  

    In this paper, we consider the problem of energy efficient scheduling under average delay constraint for a single user fading channel. We propose a new approach for on-line implementation of the optimal packet scheduling algorithm. This approach is based on reformulating the value iteration equation by introducing a virtual state called post-decision state. The resultant value iteration equation becomes amenable to online implementation based on stochastic approximation. This approach has an advantage that an explicit knowledge of the probability distribution of the channel state as well as the arrivals is not required for the implementation. We prove that the on-line algorithm indeed converges to the optimal policy. View full abstract»

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  • IEEE Communications Society 2008 Board of Governors

    Publication Year: 2008 , Page(s): C3
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  • Contents - Continued from front cover

    Publication Year: 2008 , Page(s): C4
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Aims & Scope

IEEE Journal on Selected Areas in Communications focuses on all telecommunications, including telephone, telegraphy, facsimile, and point-to-point television, by electromagnetic propagation.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Muriel Médard
MIT