498 research outputs found
Distributed Consensus over Wireless Sensor Networks Affected by Multipath Fading
The design of sensor networks capable of reaching a consensus on a globally
optimal decision test, without the need for a fusion center, is a problem that
has received considerable attention in the last years. Many consensus
algorithms have been proposed, with convergence conditions depending on the
graph describing the interaction among the nodes. In most works, the graph is
undirected and there are no propagation delays. Only recently, the analysis has
been extended to consensus algorithms incorporating propagation delays. In this
work, we propose a consensus algorithm able to converge to a globally optimal
decision statistic, using a wideband wireless network, governed by a fairly
simple MAC mechanism, where each link is a multipath, frequency-selective,
channel. The main contribution of the paper is to derive necessary and
sufficient conditions on the network topology and sufficient conditions on the
channel transfer functions guaranteeing the exponential convergence of the
consensus algorithm to a globally optimal decision value, for any bounded delay
condition.Comment: Paper submitted to IEEE Transactions on Signal Processing, August
2007. Revised November 30, 2007. Accepted January 14, 200
Distributed Estimation and Control of Algebraic Connectivity over Random Graphs
In this paper we propose a distributed algorithm for the estimation and
control of the connectivity of ad-hoc networks in the presence of a random
topology. First, given a generic random graph, we introduce a novel stochastic
power iteration method that allows each node to estimate and track the
algebraic connectivity of the underlying expected graph. Using results from
stochastic approximation theory, we prove that the proposed method converges
almost surely (a.s.) to the desired value of connectivity even in the presence
of imperfect communication scenarios. The estimation strategy is then used as a
basic tool to adapt the power transmitted by each node of a wireless network,
in order to maximize the network connectivity in the presence of realistic
Medium Access Control (MAC) protocols or simply to drive the connectivity
toward a desired target value. Numerical results corroborate our theoretical
findings, thus illustrating the main features of the algorithm and its
robustness to fluctuations of the network graph due to the presence of random
link failures.Comment: To appear in IEEE Transactions on Signal Processin
Combined Soft Hard Cooperative Spectrum Sensing in Cognitive Radio Networks
Providing some techniques to enhance the performance of spectrum sensing in cognitive radio systems while accounting for the cost and bandwidth limitations in practical scenarios is the main objective of this thesis. We focus on an essential element of cooperative spectrum sensing (CSS) which is the data fusion that combines the sensing results to make the final decision. Exploiting the advantage of the superior performance of the soft schemes and the low bandwidth of the hard schemes by incorporating them in cluster based CSS networks is achieved in two different ways. First, a soft-hard combination is employed to propose a hierarchical cluster based spectrum sensing algorithm. The proposed algorithm maximizes the detection performances while satisfying the probability of false alarm constraint. Simulation results of the proposed algorithm are presented and compared with existing algorithms over the Nakagami fading channel. Moreover, the results show that the proposed algorithm outperforms the existing algorithms. In the second part, a low complexity soft-hard combination scheme is suggested by utilizing both one-bit and two-bit schemes to balance between the required bandwidth and the detection performance by taking into account that different clusters undergo different conditions. The scheme allocates a reliability factor proportional to the detection rate to each cluster to combine the results at the Fusion center (FC) by extracting the results of the reliable clusters. Numerical results obtained have shown that a superior detection performance and a minimum overhead can be achieved simultaneously by combining one bit and two schemes at the intra-cluster level while assigning a reliability factor at the inter-cluster level
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