Unified Scaling of Polar Codes: Error Exponent, Scaling Exponent, Moderate Deviations, and Error Floors

preprint2016arXivOpen access

Abstract

Consider the transmission of a polar code of block length NN and rate RR over a binary memoryless symmetric channel WW and let PeP_e be the block error probability under successive cancellation decoding. In this paper, we develop new bounds that characterize the relationship of the parameters RR, NN, PeP_e, and the quality of the channel WW quantified by its capacity I(W)I(W) and its Bhattacharyya parameter Z(W)Z(W). In previous work, two main regimes were studied. In the error exponent regime, the channel WW and the rate R<I(W)R<I(W) are fixed, and it was proved that the error probability PeP_e scales roughly as 2−N2^{-\sqrt{N}}. In the scaling exponent approach, the channel WW and the error probability PeP_e are fixed and it was proved that the gap to capacity I(W)−RI(W)-R scales as N−1/μN^{-1/μ}. Here, μμ is called scaling exponent and this scaling exponent depends on the channel WW. A heuristic computation for the binary erasure channel (BEC) gives μ=3.627μ=3.627 and it was shown that, for any channel WW, 3.579≤μ≤5.7023.579 \le μ\le 5.702. Our contributions are as follows. First, we provide the tighter upper bound μ≤4.714μ\le 4.714 valid for any WW. With the same technique, we obtain μ≤3.639μ\le 3.639 for the case of the BEC, which approaches very closely its heuristically derived value. Second, we develop a trade-off between the gap to capacity I(W)−RI(W)-R and the error probability PeP_e as functions of the block length NN. In other words, we consider a moderate deviations regime in which we study how fast both quantities, as functions of the block length NN, simultaneously go to 00. Third, we prove that polar codes are not affected by error floors. To do so, we fix a polar code of block length NN and rate RR. Then, we vary the channel WW and we show that the error probability PeP_e scales as the Bhattacharyya parameter Z(W)Z(W) raised to a power that scales roughly like N\sqrt{N}.

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