15,405 research outputs found
Cooperative Synchronization in Wireless Networks
Synchronization is a key functionality in wireless network, enabling a wide
variety of services. We consider a Bayesian inference framework whereby network
nodes can achieve phase and skew synchronization in a fully distributed way. In
particular, under the assumption of Gaussian measurement noise, we derive two
message passing methods (belief propagation and mean field), analyze their
convergence behavior, and perform a qualitative and quantitative comparison
with a number of competing algorithms. We also show that both methods can be
applied in networks with and without master nodes. Our performance results are
complemented by, and compared with, the relevant Bayesian Cram\'er-Rao bounds
Cooperative Network Synchronization: Asymptotic Analysis
Accurate clock synchronization is required for collaborative operations among nodes across wireless networks. Compared with traditional layer-by-layer methods, cooperative network synchronization techniques lead to significant improvement in performance, efficiency, and robustness. This paper develops a framework for the performance analysis of cooperative network synchronization. We introduce the concepts of cooperative dilution intensity (CDI) and relative CDI to characterize the interaction between agents, which can be interpreted as properties of a random walk over the network. Our approach enables us to derive closed-form asymptotic expressions of performance limits, relating them to the quality of observations as well as the network topology
Cooperative Transmissions in Wireless Sensor Networks with Imperfect Synchronization
AbstractĂSTBC-encoded cooperative transmission is studied in a typical wireless sensor network communication protocol LEACH (Low-Energy Adaptive Clustering Hierarchy). The effect of imperfect synchronization among cooperative sensors is studied and a new STBC encoding scheme is proposed when asynchronism becomes significant. Cooperation overhead and energy efficiency are analyzed. The analysis and simulation results demonstrate that cooperative transmission is promising in wireless sensor networks in spite of the increased cost of synchronization and circuitry energy consumption
Differential Distributed Space-Time Coding with Imperfect Synchronization
Differential distributed space-time coding (D-DSTC) has been considered to
improve both diversity and data-rate in cooperative communications in the
absence of channel information. However, conventionally, it is assumed that
relays are perfectly synchronized in the symbol level. In practice, this
assumption is easily violated due to the distributed nature of the relay
networks. This paper proposes a new differential encoding and decoding process
for D-DSTC systems with two relays. The proposed method is robust against
synchronization errors and does not require any channel information at the
destination. Moreover, the maximum possible diversity and symbol-by-symbol
decoding are attained. Simulation results are provided to show the performance
of the proposed method for various synchronization errors and the fact that our
algorithm is not sensitive to synchronization error.Comment: to appear in IEEE Globecom, 201
Cooperative Simultaneous Localization and Synchronization in Mobile Agent Networks
Cooperative localization in agent networks based on interagent time-of-flight
measurements is closely related to synchronization. To leverage this relation,
we propose a Bayesian factor graph framework for cooperative simultaneous
localization and synchronization (CoSLAS). This framework is suited to mobile
agents and time-varying local clock parameters. Building on the CoSLAS factor
graph, we develop a distributed (decentralized) belief propagation algorithm
for CoSLAS in the practically important case of an affine clock model and
asymmetric time stamping. Our algorithm allows for real-time operation and is
suitable for a time-varying network connectivity. To achieve high accuracy at
reduced complexity and communication cost, the algorithm combines particle
implementations with parametric message representations and takes advantage of
a conditional independence property. Simulation results demonstrate the good
performance of the proposed algorithm in a challenging scenario with
time-varying network connectivity.Comment: 13 pages, 6 figures, 3 tables; manuscript submitted to IEEE
Transaction on Signal Processin
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