Abstract
Collaborative signal processing is one of the most promising applications that are currently being investigated for sensor networks. In this paper, we use FFT computation as a vehicle to highlight the issues involved in realizing distributed computations over sensor networks that have global and local communication and synchronization characteristics. We present a power efficient algorithm for computing 1-D Fast Fourier Transform (FFT) over single and multi-hop wireless sensor networks. The proposed algorithm reduces the number of transmissions, eliminates typical redundant computations in a distributed FFT algorithm and uniformly maps complex multiplications over all the sensors nodes by introducing an extra bit-complement permutation stage after first (log2N)/2 iterations. We show that the proposed algorithm improves energy consumption by 36% on the average on multi-hop sensor networks. This saving in energy consumption significantly improves the battery life of the sensor nodes thereby increasing lifetime of the sensor network.
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