A CORDIC-Based Low-Power Statistical Feature Computation Engine for WSN Applications

Faculty of Physical Sciences and Engineering, University of Southampton, United Kingdom, SO17 1BJ Email: [email protected] K. Maharatna Faculty of Physical Sciences and Engineering, University of Southampton, United Kingdom, SO17 1BJ Email: [email protected], Telephone: +44(0)2380599322 Abstract: In this paper we present a carry-save arithmetic (CSA) based Coordinate Rotation Digital Computer (CORDIC) engine for computing eight fundamental time domain statistical features. These features are used commonly in association with major classifiers in remote health monitoring systems with an aim of executing them on a node of Wireless Sensor Network (WSN). The engine computes all the eight features sequentially in 3n clock cycles where n is the number of data samples. We further present a comparative analysis of the hardware complexity of our proposed architecture with an alternate architecture which does not use CORDIC (instead uses standalone array multiplier, divider, square rooter and logarithm converter). The hardware complexity of the two architectures presented in terms of full adder count reflects the effectiveness of using CORDIC for the given application. The engine was synthesized using the STMicroelectronics 130 nm technology library and occupied 205K NAND2 equivalent cell area and consumed 1nW dynamic power @ 50 Hz as estimated using Prime time. Therefore, the design can be applicable for low-power realtime operations within a WSN node.