Information Friction and Its Implications on Minimum Energy Required for Communication

Just as there are frictional losses associated with moving masses on a surface, what if there were frictional losses associated with moving information on a substrate? Indeed, many modes of communication suffer from such frictional losses. 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. We use this information-friction model to understand the fundamental energy requirements on encoding and decoding in communication circuitry. First, for communication across a binary input additive white Gaussian noise channel, we arrive at fundamental limits on bit-meters (and thus energy consumption) for decoding implementations that have a predetermined input-independent length of messages. For encoding, we relax the fixed-length assumption and derive bounds for flexible-message-length implementations. Using these lower bounds, we show that the total (transmit + encoding + decoding) energy-per-bit must diverge to infinity as the target error probability is lowered to zero. Furthermore, the closer the communication rate is maintained to the channel capacity (as the target error probability is lowered to zero), the fast required decoding energy diverges to infinity.