Title :
“Information-friction” and its impact on minimum energy per communicated bit
Author_Institution :
ECE, Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
Just as there are frictional losses associated with moving masses on a surface, what if there are frictional losses associated with moving information on a substrate? We propose to model these losses as proportional to “bit-meters” i.e., the product of mass of information (i.e., the number of bits) and the distance of information transport. For communication across a binary input AWGN channel decoded by decoders implemented using a simple circuit model, we derive unavoidable lower bounds on bit-meters for decoding computation. These bounds are translated into limits on energy consumption in decoding under the information-friction model. Using these lower bounds we show that the total (transmit + decoding) energy-per-bit must diverge to infinity as the target error probability is lowered.
Keywords :
AWGN channels; channel coding; decoding; binary input AWGN channel decoding; bit-meters; energy consumption; frictional losses; information transport distance; information-friction model; lower bounds; minimum energy per communicated bit; simple circuit model; target error probability; Channel models; Computational modeling; Decoding; Error probability; Integrated circuit modeling; Substrates;
Conference_Titel :
Information Theory Proceedings (ISIT), 2013 IEEE International Symposium on
Conference_Location :
Istanbul
DOI :
10.1109/ISIT.2013.6620679