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a completely distributed and asynchronous way: some nodes may update their estimates more frequently than others using outdated message from neighboring nodes.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

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

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

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

A multi-commodity discrete/continuum model for a traffic equilibrium system

We consider a city with several highly compact central business districts (CBDs). The commuters’ origins are continuously dispersed. The travel demand to each CBD, which is considered to be a distinct commodity of traffic movements, is dependent on the total travel cost to that CBD. The transportation system is divided into two layers: major freeways and a dense network of surface streets. Whereas the major freeway network is modelled according to the conventional discrete-network approach, the dense surface streets are approximated as a continuum. Travellers to each CBD can either travel within the continuum (surface streets) and then transfer to the discrete network (freeways) at an interchange (ramp) before moving to the CBD on the discrete network, or they can travel directly to the CBD within the continuum. Specific travel cost-flow relationships for the two layers of transportation facilities are considered. We develop a traffic equilibrium model for this discrete/continuum transportation system in which, for each origin–destination pair, no traveller can reduce his or her individual travel cost by unilaterally changing routes. The problem is formulated as a simultaneous optimisation programme with two sub-problems. One sub-problem is a traffic assignment problem from the interchanges to the CBD in the discrete network, and the other is a traffic assignment problem within a continuum system with multiple centres (i.e. the interchange points and the CBDs). A Newtonian algorithm based on sensitivity analyses of the two sub-problems is proposed to solve the resultant simultaneous optimisation programme. A numerical example is given to demonstrate the effectiveness of the proposed method.postprin

Distributed Bayesian hybrid power state estimation with PMU synchronization errors

Signal Processing for Communications SymposiumThis paper presents a distributed hybrid power state estimator, with measurements from both the traditional supervisory control and data acquisition (SCADA) system and the newly invented phasor measurement units (PMUs). The proposed distributed algorithm, which jointly estimates the power states and PMU phase errors, only involves local computations and limited information exchange between neighboring areas, thus alleviating the heavy communication burden compared to the centralized approach. Simulation results show that the performance of the proposed algorithm is very close to that of centralized optimal hybrid state estimates without sampling phase error.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

Continuum modeling approach to the spatial analysis of air quality and housing location choice

Today, air pollution is a great issue, and the transport sector is an important emission source. In this study, we present an integrated land use, transport, and environment model in which transport-related pollutants are assumed to influence people's housing location choices, and a continuum modeling approach is applied. The pollutants generated by the transport sector are dispersed by the wind and they affect air quality. The air quality changes people's housing choices, which in turn changes their travel behavior. We assume that the road users are continuously distributed over the city, that the road network is relatively dense, and that this network can be approximated as a continuum. The total demand is categorized into several classes, and the modeled region contains several subdistricts. People who live in different subdistricts or who belong to different classes of commuters are assumed to have different perceptions of travel time, air quality, and the housing provision–demand relationship. The finite element method and the Newton–Raphson algorithm are adopted to solve this problem, and a numerical valuation is given to illustrate the effectiveness and efficiency of the proposed model.postprin

CFO estimation in OFDM systems under timing and channel length uncertainties with model averaging

In this letter, we investigate the problem of CFO estimation in OFDM systems when the timing offset and channel length are not exactly known. Instead of explicitly estimating the timing offset and channel length, we employ a multi-model approach, where the timing offset and channel length can take multiple values with certain probabilities. The effect of multimodel is directly incorporated into the CFO estimator. Results show that the proposed estimator outperforms the estimator selecting only the most probable model and the method taking the maximal model. © 2006 IEEE.published_or_final_versio