Signal coding for low power: fundamental limits and practical realizations

S. Ramprasad, N.R. Shanbhag, I.N. Hajj
ISCAS '98. Proceedings of the 1998 IEEE International Symposium on Circuits and Systems (Cat. No.98CH36187)  
Transitions on high capacitance busses result in considerable system power dissipation. Therefore, various coding schemes have been proposed in the literature to encode the input signal in order to reduce the number of transitions. In this paper, we present: 1.) fundamental bounds on the activity reduction capability of any encoding scheme for a given source, and 2.) practical novel encoding schemes that approach these bounds. T h e fundamental bounds in 1.) are obtained via an
more » ... an information-theoretic approach where a signal x ( n ) with entropy rate ' H is coded with R bits per sample on average. T h e encoding schemes in 2.) are developed via a communication-theoretic approach, whereby a data source is Dassed through a decorrelating function fol-developed based upon the source-channel coding view. In this framework, a data source (characterized in a probabilistic manner) is passed through a decorrelating function fi first. Next, a variant of entropy coding function fi is employed, which reduces the transition activity. T h e framework is then employed to derive novel encoding schemes whereby practical forms for fi and fi are proposed. Simulation results with an encoding scheme for data busses indicate an average reduction in transition activity of 36%. We then examine the transition activity reducing efficiency of these coding schemes. This work is a continuation of our effort in developing an information-theoretic view of VLSI computation [5], whereby equivalence between computation and communication is being established. -- BOUNDS ON TRANSITION ACTIVITY lowed by a variant of entropy coding function which reduces the transition activitv. Simulation results with an encoding scheme for d a t a busses indicate an average reduction in transition activity of 36%.
doi:10.1109/iscas.1998.706776 fatcat:djidnjhqvfcu5gy7wrjkwvsyae