Adaptive low-power analog/digital converters for wireless sensor networks

The paper addresses the problem of power consumption of sensor nodes in a wireless network. An integrated low-power analog/digital converter (ADC) is presented that is particularly suited for wireless sensor applications. The converter makes use of information theoretic redundancy in the input signal for reducing the conversion workload and performing data compression on-the-fly during conversion (entropy-coding A/D converter). Thus, energy is saved both in signal conversion and transmission. Experimental results from a prototype chip are presented. The converter is especially suitable for sensor networks that maintain a global data model. This is further illustrated on an exemplary scenario of distributed wave detection. It is shown that sensor signal detection and acquisition in this type of applications can be carried out very efficiently with entropy-coding converters used in the sensor nodes.

[1]  Allen Gersho,et al.  Vector quantization and signal compression , 1991, The Kluwer international series in engineering and computer science.

[2]  Harold J. Kushner,et al.  A simulation study of a decentralized detection problem , 1982 .

[3]  Samuel Madden,et al.  Distributed regression: an efficient framework for modeling sensor network data , 2004, Third International Symposium on Information Processing in Sensor Networks, 2004. IPSN 2004.

[4]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[5]  K. Uyttenhove,et al.  Speed-power-accuracy trade-off in high-speed ADCs: what about nano-electronics? , 2001, Proceedings of the IEEE 2001 Custom Integrated Circuits Conference (Cat. No.01CH37169).

[6]  D. Schroeder,et al.  A low-power entropy-coding analog/digital converter with integrated data compression , 2003, ESSCIRC 2004 - 29th European Solid-State Circuits Conference (IEEE Cat. No.03EX705).

[7]  Charles Ray Smith.  Bayesian approach to multisensor data fusion , 1992, Defense, Security, and Sensing.

[8]  P.K. Varshney,et al.  Optimal Data Fusion in Multiple Sensor Detection Systems , 1986, IEEE Transactions on Aerospace and Electronic Systems.

[9]  Robert R. Tenney,et al.  Detection with distributed sensors , 1980 .