Joint localization and time synchronization in wireless sensor networks with anchor uncertainties

Although localization and synchronization share many aspects in common, they are traditionally treated separately. In this paper, we present a unified framework to jointly solve these two problems at the same time. The joint approach is attractive because it can solve both localization and synchronization using the same set of message exchanges. This is extremely important for energy saving, especially for the energy constrained wireless sensor networks. Furthermore, since the accuracy of localization and synchronization is very sensitive to the accuracy of anchor locations and timings, the joint localization and synchronization problem with inaccurate anchor is considered in this paper. A novel generalized total least squares (GTLS) based method is proposed and the Cramer-Rao lower bound (CRLB) for the joint localization and time synchronization is derived. Simulation results show that the mean square error performances of the proposed estimator can attain the CRLB. © 2009 IEEE.published_or_final_versionThe IEEE Conference on Wireless Communications and Networking (WCNC 2009), Budapest, Hungary, 5-8 April 2009. In Proceedings of IEEE WCNC, 2009, p. 1-

Distributed Clock Skew and Offset Estimation in Wireless Sensor Networks: Asynchronous Algorithm and Convergence Analysis

In this paper, we propose a fully distributed algorithm for joint clock skew and offs et estimation in wireless sensor networks based on belief propagation. In the proposed algorithm, each node can estimate its clock skew and offset in a completely distributed and asynchronous way: some nodes may update their estimates more frequently than others using outdated message from neighboring nodes. In addition, the proposed algorithm is robust to random packet loss. Such algorithm does not require any centralized information processing or coordination, and is scalable with network size. The proposed algorithm represents a unified framework that encompasses both classes of synchronous and asynchronous algorithms for network-wide clock synchronization. It is shown analytically that the proposed asynchronous algorithm converges to the optimal estimates with estimation mean-square-error at each node approaching the centralized Cram ́er-Rao bound under any network topology. Simulation results further show that the convergence speed is faster than that corresponding to a synchronous algorithm.published_or_final_versio

Fully Distributed Clock Skew And Offset Estimation In Wireless Sensor Networks

In this paper, we propose a fully distributed algorithm for joint clock skew and offset estimation in wireless sensor networks. With the proposed algorithm, each node can estimate its clock skew and offset by communicating only with its neighbors. Such algorithm does not require any centralized information processing or coordination. Simulation results show that estimation mean-square-error at each node converge to the centralized Cramér-Rao bound with only a few number of message exchanges.published_or_final_versio

Network-Wide Distributed Carrier Frequency Offsets Estimation and Compensation via Belief Propagation

In this paper, we propose a fully distributed algorithm for frequency offsets estimation in decentralized systems. The idea is based on belief propagation, resulting in that each node estimates its own frequency offsets by local computations and limited exchange of information with its direct neighbors. Such algorithm does not require any centralized information processing or knowledge of global network topology, thus is scalable with network size. It is shown analytically that the proposed algorithm always converges to the optimal estimates regardless of network topology. Simulation results demonstrate the fast convergence of the algorithm and show that estimation mean-squared-error at each node approaches the centralized Craḿer-Rao bound within a few iterations of message exchange.published_or_final_versio

Distributed CFOs Estimation and Compensation in Multi-cell Cooperative Networks

In this paper, we propose a fully distributed algorithm for frequency offsets estimation in multi-cell cooperative networks. The idea is based on belief propagation, resulting in that each base station or mobile user estimates its own frequency offsets by local computations and limited exchange of information with its direct neighbors in the cellular network. Such algorithm does not require any centralized information processing or knowledge of global network topology, thus is scalable with network size. Simulation results demonstrate the fast convergence of the algorithm and show that estimation mean-squared-error at each node touches the centralized Cramér-Rao bound within a few iterations of message exchange. © 2013 IEEE

Localization and time synchronization in wireless sensor networks: a unified approach

Localization and synchronization are two important issues in communication systems and wireless sensor networks. These two problems are addressed in many applications, and share many aspects in common. However, these two problems are traditionally treated separately. In this paper, we present a unified framework to jointly solve these two problems at the same time. The maximum likelihood joint estimation of location and timing is firstly derived. Then, a more computationally efficient two-stage least square method is proposed. The Cramer-Rao lower bound for the joint localization and time synchronization is also derived. Simulation results show that the performances of the maximum likelihood and two-stage least square estimators can both achieve the Cramer-Rao lower bound. ©2008 IEEE.published_or_final_versionThe IEEE Asia-Pacific Conference on Circuits and Systems (APCCAS 2008), Macao, China, 30 November-3 December 2008. In Proceedings of IEEE APCCAS, 2008, p. 594-59

Frequency synchronization for multiuser MIMO-OFDM system using Bayesian approach

This paper addresses the problem of frequency synchronization in multiuser multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems. Different from existing work, a Bayesian approach is used in the parameter estimation problem. In this paper, the Bayes estimator for carrier frequency offset (CFO) estimation is proposed and the Bayesian Cramér-Rao bound (BCRB) is also derived in closed form. Direct implementation of the resultant estimation scheme with conventional methods is challenging since a high degree of mathematical sophistication is always required. To solve this problem, the Gibbs sampler is exploited with an efficient sample generation method. Simulation results illustrate the effectiveness of the proposed estimation scheme. ©2010 IEEE.published_or_final_versionThe 2010 IEEE Global Telecommunications Conference (GLOBECOM 2010), Miami, FL., 6-10 December 2010. In Globecom. IEEE Conference and Exhibition, 2010, p. 1-

Variational Inference-based Joint Interference Mitigation and OFDM Equalization Under High Mobility

In OFDM-based spectrum sharing networks, due to inefficient coordination or imperfect spectrum sensing, the signals from femtocells or secondary users appear as interference in a subset of subcarriers of the primary systems. Together with the inter-carrier interference (ICI) introduced by high mobility, equalizing one subcarrier now depends not only on whether interference exists, but also the neighboring subcarrier data. In this letter, we propose a novel approach to iteratively learn the statistics of noise plus interference across different subcarriers, and refine the soft data estimates of each subcarrier based on the variational inference. Simulation results show that the pro- posed method avoids the error floor effect, which is exhibited by existing algorithms without considering interference mitigation, and performs close to the ideal case with perfect ICI cancelation and knowledge of noise plus interference powers for optimal maximum a posteriori probability (MAP) equalizer.published_or_final_versio

QoS constrained robust MIMO transceiver design under unknown interference

We study the robust transceiver optimization in multiple-input multiple-output (MIMO) systems aiming at minimizing transmit power under probabilistic quality-of-service (QoS) requirements. Owing to the unknown distributed interference, the channel estimation error can be arbitrary distributed. Under this situation, the QoS requirements should account for the worst-case channel estimation error distribution. While directly finding the worst-case distribution is challenging, two methods are proposed to solve the robust transceiver design problem. One is based on the Chebyshev inequality, the other is based on a novel duality method. Simulation results show that the QoS requirement is satisfied by both proposed algorithms. Furthermore, among the two proposed methods, the duality method shows a superior performance in transmit power, while the Chebyshev method demonstrates a lower computational complexity. © 2012 IEEE.published_or_final_versio

Distributed Hybrid Power State Estimation under PMU Sampling Phase Errors

Phasor measurement units (PMUs) have the advan- tage of providing direct measurements of power states. However, as the number of PMUs in a power system is limited, the traditional supervisory control and data acquisition (SCADA) system cannot be replaced by the PMU-based system overnight. Therefore, hy- brid power state estimation taking advantage of both systems is im- portant. As experiments show that sampling phase errors among PMUs are inevitable in practical deployment, this paper proposes a distributed power state estimation algorithm under PMU phase er- rors. The proposed distributed algorithm only involves local com- putations and limited information exchange between neighboring areas, thus alleviating the heavy communication burden compared to the centralized approach. Simulation results show that the per- formance of the proposed algorithm is very close to that of central- ized optimal hybrid state estimates without sampling phase error.published_or_final_versio