On Scaling Rules for Energy of VLSI Polar Encoders and Decoders

It is shown that all polar encoding schemes of rate $R>\frac{1}{2}$ of block length $N$ implemented according to the Thompson VLSI model must take energy $E\ge\Omega\left(N^{3/2}\right)$. This lower bound is achievable up to polylogarithmic factors using a mesh network topology defined by Thompson and the encoding algorithm defined by Arikan. A general class of circuits that compute successive cancellation decoding adapted from Arikan's butterfly network algorithm is defined. It is shown that such decoders implemented on a rectangle grid for codes of rate $R>2/3$ must take energy $E\ge\Omega(N^{3/2})$, and this can also be reached up to polylogarithmic factors using a mesh network. Capacity approaching sequences of energy optimal polar encoders and decoders, as a function of reciprocal gap to capacity $\chi = (1-R/C)^{-1}$, have energy that scales as $\Omega\left(\chi^{5.325}\right)\le E \le O\left(\chi^{7.05}\log^{4}\left(\chi\right)\right)$

Energy, Latency, and Reliability Tradeoffs in Coding Circuits

It is shown that fully-parallel encoding and decoding schemes with asymptotic block error probability that scales as $O\left(f\left(n\right)\right)$ have Thompson energy that scales as $\Omega\left(\sqrt{\ln f\left(n\right)}n\right)$. As well, it is shown that the number of clock cycles (denoted $T\left(n\right)$) required for any encoding or decoding scheme that reaches this bound must scale as $T\left(n\right)\ge\sqrt{\ln f\left(n\right)}$. Similar scaling results are extended to serialized computation. The Grover information-friction energy model is generalized to three dimensions and the optimal energy of encoding or decoding schemes with probability of block error $P_\mathrm{e}$ is shown to be at least $\Omega\left(n\left(\ln P_{\mathrm{e}}\left(n\right)\right)^{\frac{1}{3}}\right)$.Comment: 13 pages, 2 figures, submitted for journal publication, submitted in part for presentation at 2016 International Symposium on Information Theor