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Geographic gossip: Efficient averaging for sensor networks

IEEE TRANSACTIONS ON signal processing 2008年第3期56卷 1205-1216页

作者： Dimakis, Alexandros D. G. Sarwate, Anand D. Wainwright, Martin J. Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94720 USA Univ Calif Berkeley Dept Stat Berkeley CA 94720 USA

Gossip algorithms for distributed computation are attractive due to their simplicity, distributed nature, and robustness in noisy and uncertain environments. However, using standard gossip algorithms can lead to a significant waste of energy by repeatedly recirculating redundant information. For realistic sensor network model topologies like grids and random geometric graphs, the inefficiency of gossip schemes is related to the slow mixing times of random walks on the communication graph. We propose and analyze an alternative gossiping scheme that exploits geographic information. By utilizing geographic routing combined with a simple resampling method, we demonstrate substantial gains over previously proposed gossip protocols. For regular graphs such as the ring or grid, our algorithm improves standard gossip by factors of n and root n, respectively. For the more challenging case of random geometric graphs, our algorithm computes the true average to accuracy E using O((n(1.5)/root log n) log epsilon(-1)) radio transmissions, which yields a root n/log n factor improvement over standard gossip algorithms. We illustrate these theoretical results with experimental comparisons between our algorithm and standard methods as applied to various classes of random fields.

关键词： aggregation problems consensus problems distributed signal processing gossip algorithms message-passing algorithms random geometric graphs sensor networks

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distributed beamforming for relay networks based on second-order statistics of the channel state information

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IEEE TRANSACTIONS ON signal processing 2008年第9期56卷 4306-4316页

作者： Havary-Nassab, Veria Shahbazpanahi, Shahram Grami, Ali Luo, Zhi-Quan Univ Ontario Inst Technol Fac Engn & Appl Sci Oshawa ON L1H 7K4 Canada Univ Minnesota Dept Elect & Comp Engn Minneapolis MN 55455 USA

In this paper, the problem of distributed beam-forming is considered for a wireless network which consists of a transmitter, a receiver, and r relay nodes. For such a network, assuming that the second-order statistics of the channel coefficients are available, we study two different beamforming design approaches. As the first approach, we design the beamformer through minimization of the total transmit power subject to the receiver quality of service constraint. We show that this approach yields a closed-form solution. In the second approach, the beamforming weights are obtained through maximizing the receiver signal-to-noise ratio (SNR) subject to two different types of power constraints, namely the total transmit power constraint and individual relay power constraints. We show that the total power constraint leads to a closed-form solution while the individual relay power constraints result in a quadratic programming optimization problem. The later optimization problem does not have a closed-form solution. However, it is shown that using semidefinite relaxation, this problem can be turned into a convex feasibility semidefinite programming (SDP), and therefore, can be efficiently solved using interior point methods. Furthermore, we develop a simplified, thus suboptimal, technique which is computationally more efficient than the SDP approach. In fact, the simplified algorithm provides the beamforming weight vector in a closed form. Our numerical examples show that as the uncertainty in the channel state information is increased, satisfying the quality of service constraint becomes harder, i.e., it takes more power to satisfy these constraints. Also our simulation results show that when compared to the SDP-based method, our simplified technique suffers a 2-dB loss in SNR for low to moderate values of transmit power.

关键词： convex feasibility problem distributed beamforming distributed signal processing relay networks semidefinite programming

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Performance analysis of universal distributed estimation in bandwidth-constrained sensor networks

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IEEE signal processing LETTERS 2008年第1期15卷 473-476页

作者： Zhang, Li Zhang, Xian-Da Gao, Qiubin Tsinghua Univ Dept Automat Natl Lab Informat Sci & Technol Beijing 100084 Peoples R China

This letter analyzes the performance of several typical one-bit universal distributed estimation schemes (DESs) in bandwidth-constrained sensor networks. We theoretically obtain the mean and mean-square error (MSE) of the DES based on binary form (BF) of the observation along with the MSE upper bound. It is proved that in some cases, the BF-based DES has larger MSE than the DES based on the complementary cumulative distribution function (CCDF) of the observation. Moreover, performance analysis is presented for the CCDF-based and BF-based DESs employing probabilistic quantization, respectively.

关键词： distributed estimation distributed signal processing quantization sensor networks

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distributed peer-to-peer multiplexing using ad hoc relay networks

Distributed peer-to-peer multiplexing using ad hoc relay net...

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33rd IEEE International Conference on Acoustics, Speech and signal processing

作者： Fazeli-Dehkordy, Siavash Gazor, Saeed Shahbazpanahi, Shahram Queens Univ Dept Elect & Comp Eng Walter Light Hall Kingston ON K7L 3N6 Canada Univ Ontario Inst Technol Fac Engn & Appl Sci London ON LIH 7K4 Canada

ISBN: (纸本)9781424414833

We consider an ad hoc network consisting of d source-destination pairs and R relaying nodes. Each source wishes to transmit its data to its corresponding destination through the relay network. Each relay in the network transmits a properly scaled version of its received signal thereby cooperating with other relays to deliver each source's data to the corresponding destination. Assuming a minimal cooperation among the relaying nodes, we design a distributed beamformer such that the total relay transmit power dissipated by all relays is minimized while, at the same time, the quality of services at all destinations are guaranteed to be above certain pre-defined thresholds. We show that using a semi-definite relaxation approach, the power minimization problem can be turned into a semi-definite programming (SDP) optimization, and therefore, it can be solved efficiently using interior point methods. Our results show that the distributed relay multiplexing is possible and may be beneficial depending on the channel conditions.

关键词： distributed beamforming relay networks semi-definite programming convex feasibility problem distributed signal processing

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distributed average consensus with increased convergence rate

Distributed average consensus with increased convergence rat...

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33rd IEEE International Conference on Acoustics, Speech and signal processing

作者： Oreshkin, Boris N. Aysal, Tuncer C. Coates, Mark J. McGill Univ Dept Elect & Comp Engn Montreal PQ H3A 2T5 Canada

ISBN: (纸本)9781424414833

The average consensus problem in the distributed signal processing context is addressed by linear iterative algorithms, with asymptotic convergence to the consensus. The convergence of the average consensus for an arbitrary weight matrix satisfying the convergence conditions is unfortunately slow restricting the use of the developed algorithms in applications. In this paper, we propose the use of linear extrapolation methods in order to accelerate distributed linear iterations. We provide analytical and simulation results that demonstrate the validity and effectiveness of the proposed scheme. Finally, we report simulation results showing that the generalized version of our algorithm, when a grid search for the unknown optimum value of mixing parameter is used, significantly outperforms the optimum consensus algorithm based on weight matrix optimization.

关键词： distributed signal processing average consensus linear prediction

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Bandwidth-efficient distributed estimation in inhomogeneous wireless sensor networks

Bandwidth-efficient distributed estimation in inhomogeneous ...

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IEEE Wireless Communications and Networking Conference

作者： Zhang, Li Zhang, Xian-Da Gao, Qiubin Han, Fang-Ming Tsinghua Univ Dept Automat Tsinghua Natl Lab Informat Sci & Technol Beijing 100084 Peoples R China

ISBN: (纸本)9781424419968

This paper presents a distributed estimation scheme (DES) along with the bit allocation algorithm, which minimizes the total required bandwidth while ensuing a given average estimation mean-squared error (MSE). The DES comprises of a probabilistic Lloyd-Max quantization rule, and a best linear unbiased estimation (BLUE). Since the optimum bit allocation problem does not have a closed form, we present a suboptimal solution utilizing the alternating minimization (AM) algorithm. Finally, simulation results are provided to show the effectiveness of the proposed DES along with the bit allocation algorithm.

关键词： distributed estimation quantization distributed signal processing sensor networks

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Network beamforming based on second order statistics of the channel state information

Network beamforming based on second order statistics of the ...

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33rd IEEE International Conference on Acoustics, Speech and signal processing

作者： Havary-Nassab, Veria Shahbazpanahi, Shahram Grami, Ali Luo, Zhi-Quan Univ Western Ontario Fac Engn & Appl Sci Inst Technol Oshawa ON L1H 7K4 Canada

ISBN: (纸本)9781424414833

The problem of distributed beamforming is considered for a network which consists of a transmitter, a receiver, and r relay nodes. Assuming that the second order statistics of the channel coefficients are available, we design a distributed beamforming technique via maximization of the receiver signal-to-noise ratio (SNR) subject to individual relay power constraints. We show that using semi-definite relaxation, this SNR maximization can be turned into a convex feasibility semi-definite programming problem, and therefore, it can be efficiently solved using interior point methods. We also obtain a performance bound for the semi-definite relaxation and show that the semi-definite relaxation approach provides a c-approximation to the (nonconvex) SNR maximization problems where c = O((log r)(-1)) and r is the number of relays.

关键词： distributed beamforming relay networks semidefinite programming convex feasibility problem distributed signal processing

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distributed Incremental Quantization and Estimation for Wireless Sensor Networks

Distributed Incremental Quantization and Estimation for Wire...

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68th IEEE Vehicular Technology Conference

作者： Zhang, Li Zhang, Xian-Da Tsinghua Univ Dept Automat Tsinghua Natl Lab Informat Sci & Technol Beijing 100084 Peoples R China

ISBN: (纸本)9781424417223;9781424417216

This paper proposes a distributed incremental quantization and estimation scheme by which each sensor can make a maximum likelihood estimation (MLE) of the unknown parameter based on its local observations and the quantized messages transmitted by the previous sensor. We derive the upper bound of the estimation mean squared error (MSE) of the proposed scheme, and propose the bit allocation algorithms, which minimize the total required bandwidth while ensuring a given MSE performance. Simulation results demonstrate that the proposed scheme requires much less bandwidth, but achieves around 40% MSE reduction compared with the distributed adaptive quantization and estimation scheme.

关键词： distributed estimation incremental quantization distributed signal processing sensor networks

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distributed peer-to-peer target tracking in wireless sensor networks

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SENSORS 2007年第6期7卷 1001-1027页

作者： Wang, Xue Wang, Sheng Bi, Dao-Wei Ma, Jun-Jie Tsinghua Univ State Key lab Precis Measurement Technol & Instru Beijing 100084 Peoples R China

Target tracking is usually a challenging application for wireless sensor networks (WSNs) because it is always computation-intensive and requires real-time processing. This paper proposes a practical target tracking system based on the auto regressive moving average (ARMA) model in a distributed peer-to-peer (P2P) signal processing framework. In the proposed framework, wireless sensor nodes act as peers that perform target detection, feature extraction, classification and tracking, whereas target localization requires the collaboration between wireless sensor nodes for improving the accuracy and robustness. For carrying out target tracking under the constraints imposed by the limited capabilities of the wireless sensor nodes, some practically feasible algorithms, such as the ARMA model and the 2-D integer lifting wavelet transform, are adopted in single wireless sensor nodes due to their outstanding performance and light computational burden. Furthermore, a progressive multi-view localization algorithm is proposed in distributed P2P signal processing framework considering the tradeoff between the accuracy and energy consumption. Finally, a real world target tracking experiment is illustrated. Results from experimental implementations have demonstrated that the proposed target tracking system based on a distributed P2P signal processing framework can make efficient use of scarce energy and communication resources and achieve target tracking successfully.

关键词： wireless sensor networks target tracking distributed signal processing peer-to-peer ARMA model

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Rate-constrained distributed estimation in wireless sensor networks

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IEEE TRANSACTIONS ON signal processing 2007年第5期55卷 1634-1643页

作者： Li, Junlin AlRegib, Ghassan Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA

In this paper, we consider the distributed parameter estimation in wireless sensor networks where a total bit rate constraint is imposed. We study the optimal tradeoff between the number of active sensors and the quantization bit rate for each active sensor to minimize the estimation mean-square error (MSE). To facilitate the solution, we first introduce a concept of equivalent 1-bit MSE function. Next, we present an optimal distributed estimation algorithm for homogeneous sensor networks based on minimizing the equivalent 1-bit MSE function. Then, we present a quasi-optimal distributed estimation algorithm for heterogeneous sensor networks, which is also based on the equivalent I-bit MSE function, and the upper bound of the estimation MSE of the proposed algorithm is addressed. Furthermore, a theoretical nonachievable lower bound of the estimation MSE under the total bit rate constraint is stated and it is shown that our proposed algorithm is quasi-optimal within a factor 2.2872 of the theoretical lower bound. Simulation results also show that significant reduction in estimation MSE is achieved by our proposed algorithm when compared with other uniform methods.

关键词： best linear unbiased estimator (BLUE) collaborative signal processing distributed estimation distributed signal processing wireless sensor networks

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