Download Wireless Sensor Networks: Signal Processing and by Ananthram Swami PDF

By Ananthram Swami

This booklet specializes in theoretical facets of instant sensor networks, aiming at offering sign processing and communique views within the layout of large-scale sensor networks. Emphasis is at the primary houses of enormous scale sensor networks, disbursed sign processing and verbal exchange algorithms, and novel cross-layer layout paradigms for sensor networking. desk of contents primary homes and boundaries. Information-theoretic bounds on sensor community functionality. In-network info processing in instant sensor networks. The sensing potential of sensor networks. legislation of sensor community lifetime and its purposes. Detection in sensor networks. disbursed estimation lower than bandwidth and effort constraints. dispensed studying in instant sensor networks. Graphical versions and fusion in sensor networks. Randomized cooperative transmission in large-scale sensor networks. software based shortest course routing in ad-hoc sensor networks.

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Additional info for Wireless Sensor Networks: Signal Processing and Communications Perspectives

Example text

For (stationary, ergodic) point-to-point communication, these strategies are as good as the best strategies. This fact is known as the source/channel separation theorem. As we briefly discussed, there is no such theorem for communication problems of the sensor network type, and the extent of this lack is non-trivial: the performance deficiency of the best digital strategy with respect to the best general strategy can be exponential in the number of sensor nodes. More generally, the area of multi-terminal information theory is full of open problems.

XM )p(y|x1 , x2 , . . 61) that satisfy the conditions I (X1 , . . 62) k=1 for any partition {Wk }K k=1 of the set {1, 2, . . , M} into K subsets where K ≥ 2, and where W c denotes the complement of the set W in the set {1, 2, . . , M}, of the sets of rate vectors {(R1 , R2 , . . , RM ) : RS ≤ I (XS ; YSc |XSc ), for all S}. 62), was referred to as the dependence-balance condition. The evaluation of the theorem for concrete cases is complicated by the presence of the auxiliary random variable T .

PM . In spite of its apparent coarseness, this bound turns out to be tight in some non-trivial cases, including, for example, some Rayleigh-fading AWGN relay channels, see Kramer et al. (2005). Generally, however, the bound must be expected to be loose. 6 by the region labeled ‘Min-Max’. 12 for the linear Gaussian case. g. Telatar (1995)), as follows. 67) , n=1 where γ is chosen such that J˜ γ− n=1 1 βn2 + = Ptot . 12, it suffices to consider the scenario where the messages at all terminals are identical.

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