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Asymmetric average consensus under SINR-based interference Asymmetric average consensus under SINR-based interference

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Date added: 07/07/2013
Date modified: 07/07/2013
Filesize: 286 Bytes
Downloads: 1668

Consensus algorithms are a family of distributed processes that are based on exchanging local information in order to obtain some particular global information. An example of these algorithms is the average consensus, in which the value to be obtained is the average of some initial data. Most of the existing consensus techniques assume unrealistic models of communications that require complex control mechanisms in practice. In contrast, we consider the average consensus algorithm under a realistic asynchronous and asymmetric scheme of communications, where the interferences constrain the information exchanged among the nodes. To ensure a correct operation in this scheme, we propose a link scheduling protocol that satisfies certain convergence conditions and maximizes the number of simultaneous links in each iteration of the consensus algorithm. This increase in the number of communications per iteration improves the performance of the consensus algorithm. Simulation results are presented to verify and clearly show the efficiency of our approach.

Delay distribution analysis of wireless personal area networks Delay distribution analysis of wireless personal area networks

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Date added: 02/25/2013
Date modified: 08/03/2013
Filesize: 383.83 kB
Downloads: 145

Characterizing the network delay distribution is a fundamental step to properly compensate the delay of Networked Control Systems (NCSs). Due to the random backoff mechanism employed by Wireless Personal Area Network (WPAN) protocols, it is difficult to derive such a distribution. In this paper, the probability distribution of the delay for successfully received packets in WPANs is characterized. The analysis uses a moment generating function method based on an extended Markov chain model. The model considers the exponential backoff process with retry limits, acknowledgements, unsaturated traffic, and variable packet size, and gives an accurate explicit expression of the probability distribution of the network delay. The probability distribution of the delay is a function of the traffic load, number of nodes, and parameters of the communication protocol. Monte Carlo simulations validate the analysis for different network and protocol parameters. We show that the probability distribution of the delay is significantly different from existing network models used for NCS design. Furthermore, the parameters of the communication protocol result to be critical to stabilize control systems.

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A Comparative Analysis of the Fast-Lipschitz Convergence Speed A Comparative Analysis of the Fast-Lipschitz Convergence Speed

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Date added: 02/25/2013
Date modified: 07/09/2013
Filesize: 269.64 kB
Downloads: 1068

Fast-Lipschitz optimization is a recently proposed framework useful for an important class of centralized and distributed optimization problems over peer-to-peer networks. The properties of Fast-Lipschitz problems allow to compute the solution without having to introduce Lagrange multipliers, as in most other methods. This is highly beneficial, since multipliers need to be communicated across the network and thus increase the communication complexity of solution algorithms. Although the convergence speed of Fast-Lipschitz optimization methods often outperforms Lagrangian methods in practice, there is not yet a theoretical analysis. This paper provides a fundamental step towards such an analysis. Sufficient conditions for superior convergence of the Fast-Lipschitz method are established. The results are illustrated by simple examples. It is concluded that optimization problems with quadratic cost functions and linear constraints are always better solved by Fast-Lipschitz optimization methods, provided that certain conditions hold on the eigenvalues of the Hessian of the cost function and constraints.

Decentralized Indoor Wireless Localization Using Compressed Sensing of Signal-Strength Fingerprints Decentralized Indoor Wireless Localization Using Compressed Sensing of Signal-Strength Fingerprints

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Date added: 02/25/2013
Date modified: 08/03/2013
Filesize: 286 Bytes
Downloads: 1693

This paper combines recent developments in sparse approximation and distributed consensus theory to efficiently perform decentralized localization in wireless networks. To this goal, we exploit the Compressed Sensing (CS) framework, which provides a new paradigm for recovering signals being sparse in some basis by means of a limited amount of random incoherent projections. In particular, we propose a novel decentralized technique that considers the spatial correlations among the received measurements at the base stations (BSs) to provide global accurate position estimation, while reducing significantly the amount of measurements exchanged among the BSs and required for accurate positioning. We exploit the common structure of the received measurements to design a gossip-based algorithm in order to alleviate the effects of radio channel-induced signal variations on the estimation accuracy. Experimental evaluation with real data demonstrates the superiority of the proposed decentralized CS-based localization technique over traditional fingerprinting methods in terms of the achieved positioning accuracy.

Physical-layer Intrusion Detection for Wireless Networks using Compressed Sensing Physical-layer Intrusion Detection for Wireless Networks using Compressed Sensing

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Date added: 02/25/2013
Date modified: 08/03/2013
Filesize: 591.1 kB
Downloads: 1469

The broadcast nature of wireless networks has been widely exploited by adversaries in order to cause severe denial-of-service attacks. Several algorithms are proposed in the literature for the detection and mitigation of such attacks at the physical and medium access layers. In this work, we combine recent advances in compressed sensing theory, along with a cumulative-sum anomaly-based algorithm, for the detection of physical-layer attacks. The algorithm considers a metric based on the Signal-to-Interference-plus-Noise-Ratio (SINR). Compressed sensing makes feasible the use of far fewer SINR measurements for effective intrusion detection. The performance evaluation based on real experimental data shows that attacks are detected with high accuracy using a small number of measurements.

Efficient Training for Fingerprint Based Positioning Using Matrix Completion Efficient Training for Fingerprint Based Positioning Using Matrix Completion

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Date added: 02/25/2013
Date modified: 02/25/2013
Filesize: 266.96 kB
Downloads: 930

Fingerprint localization methods are extensively used in many location-aware applications in pervasive computing. In this paper, we propose a new framework in order to reduce the exhaustive calibration procedure during the training phase in fingerprint-based systems. In particular, we minimize the number of Received Signal Strength (RSS) fingerprints by sensing a subset of the available channels in a WLAN. We exploit the spatial correlation structure of the RSS fingerprints to reconstruct the signature map. The problem is formulated according to the recently introduced Matrix Completion (MC) framework, which provides a new paradigm for reconstructing low rank data matrices from a small number of randomly sampled entries. Analytical studies and simulations are provided to show the performance of the proposed technique in terms of reconstruction and location error.

Real-time scheduling in LTE for smart grids Real-time scheduling in LTE for smart grids

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Date added: 02/06/2013
Date modified: 12/28/2013
Filesize: 286 Bytes
Downloads: 1826

 

The latest wireless network, 3GPP Long Term Evolution (LTE), is considered to be a promising solution for smart grids because it provides both low latency and large bandwidth. However, LTE was not originally intended for smart grids applications, where data generated by the grid have specific delay requirements that are different from traditional data or voice communications. In this paper, the specific requirements imposed by a smart grids on the LTE communication infrastructure is first determined. The latency offered by the LTE network to smart grids components is investigated and an empirical mathematical model of the distribution of the latency is established. It is shown by experimental results that with the current LTE up-link scheduler, smart grid latency requirements are not always satisfied and that only a limited number of components can be accommodated. To overcome such a deficiency, a new scheduler of the LTE medium access control is proposed for smart grids. The scheduler is based on a mathematical linear optimization problem that considers simultaneously both the smart grid components and common user equipments. An algorithm for the solution to such a problem is derived based on a theoretical analysis. Simulation results based on this new scheduler illustrate the analysis. It is concluded that LTE can be effectively used in smart grids if new schedulers are employed for improving latency.

Analytical Modeling of Multi-hop IEEE 802.15.4 Networks Analytical Modeling of Multi-hop IEEE 802.15.4 Networks

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Date added: 02/06/2013
Date modified: 02/07/2014
Filesize: 286 Bytes
Downloads: 1749

 

Many of the existing analytical studies of the IEEE 802.15.4 medium access control (MAC) protocol are not adequate because they are often based on assumptions such as homogeneous traffic and ideal carrier sensing, which are far from the reality for multi-hop networks, particularly in the presence of mobility. In this paper, a new generalized analysis of the unslotted IEEE 802.15.4 MAC is presented. The analysis considers the effects induced by heterogeneous traffic due to multi-hop routing and different traffic generation patterns among the nodes of the network, and the hidden terminals due to reduced carrier sensing capabilities. The complex relation between MAC and routing protocols is modeled and novel results on this interaction are derived. For various network configurations, it is studied under which conditions routing decisions based on packet loss probability or delay lead to an unbalanced distribution of the traffic load across multi-hop paths. It is shown that these routing decisions tend to direct traffic toward nodes with high packet generation rates, with potential catastrophic effects for the node’s energy consumption. It is concluded that heterogeneous traffic and limited carrier sensing range play an essential role on the performance and that routing should account for the presence of dominant nodes to balance the traffic distribution across the network.

Rate Allocation for Quantized Control Over Binary Symmetric Channels Rate Allocation for Quantized Control Over Binary Symmetric Channels

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Date added: 01/29/2013
Date modified: 08/03/2013
Filesize: 286 Bytes
Downloads: 1714

 

Utility maximization in networked control systems (NCSs) is difficult in the presence of limited sensing and communication resources. In this paper, a new communication rate optimization method for state feedback control over a noisy channel is proposed. Linear dynamic systems with quantization errors, limited transmission rate, and noisy communication channels are considered. The most challenging part of the optimization is that no closed-form expressions are available for assessing the performance and the optimization problem is nonconvex. The proposed method consists of two steps: (i) the overall NCS performance measure is expressed as a function of rates at all time instants by means of high-rate quantization theory, and (ii) a constrained optimization problem to minimize a weighted quadratic objective function is solved. The proposed method is applied to the problem of state feedback control and the problem of state estimation. Monte Carlo simulations illustrate the performance of the proposed rate allocation. It is shown numerically that the proposed method has better performance when compared to arbitrarily selected rate allocations. Also, it is shown that in certain cases nonuniform rate allocation can outperform the uniform rate allocation, which is commonly considered in quantized control systems, for feedback control over noisy channels.

Bandwidth-Reduction Analog Mappings For AWGN Channels With Side Information Bandwidth-Reduction Analog Mappings For AWGN Channels With Side Information

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Date added: 10/28/2012
Date modified: 12/30/2013
Filesize: 327.71 kB
Downloads: 1393

 

Recently, the joint source-channel coding schemes based on analog mappings have gained prominence. Their simplicity and low delay compared to other coding strategies make them more suitable for real-time applications. In this work, we propose a novel joint source channel coding scheme, based also on analog mappings, for a point-to-point communication channel with side information at the receiver (also known as Wyner-Ziv scenario).