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On Approximation, Bounding & Exact Calculation of Block Error Probability for Random Codes

Ralf R. Müller

Published Dec 1, 2020• 2 citations
Publisher

Abstract

This paper presents a method to calculate the exact average block error probability of some random code ensembles under maximum-likelihood decoding. Deviating from Shannon's 1959 solid angle argument, we project the problem into two dimensions and apply standard trigonometry. This enables us to also analyze Gaussian random codes in additive white Gaussian noise and binary random codes for the binary symmetric channel. We find that the Voronoi regions harden doubly-exponential in the blocklength and utilize that to propose the new median bound that outperforms Shannon's 1959 sphere packing bound for the uniform spherical ensemble, whenever the code contains more than three codewords. Furthermore, we propose a very tight approximation to simplify computation of both exact error probability and the two bounds.

DOI
10.1109/globecom42002.2020.9322551

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This paper presents a method to calculate the exact average block error probability of some random code ensembles under maximum-likelihood decoding. Deviating from Shannon's 1959 solid angle argument, we project the problem into two dimensions and apply standard trigonometry. This enables us to also analyze Gaussian random codes in additive white Gaussian noise and binary random codes for the binary symmetric channel. We find that the Voronoi regions harden doubly-exponential in the blocklength and utilize that to propose the new median bound that outperforms Shannon's 1959 sphere packing bound for the uniform spherical ensemble, whenever the code contains more than three codewords. Furthermore, we propose a very tight approximation to simplify computation of both exact error probability and the two bounds.
This paper presents a method to calculate the exact average block error probability of some random code ensembles under maximum-likelihood decoding. The proposed method is applicable to various channels and ensembles. The focus is on both spherical and Gaussian random codes on the additive white Gaussian noise channel as well as binary random codes on both the binary symmetric channel and the binary erasure channel. While for the uniform spherical ensemble Shannon, in 1959, argued with solid angles in NNN-dimensional space, the presented approach projects the problem into two dimensions and applies standard trigonometry. This simplifies the derivation and also allows for the analysis of the independent identically distributed (i.i.d.) Gaussian ensemble which turns out to perform better for short blocklengths and high rates. Moreover, a new lower bound on the average block error probability of the uniform spherical ensemble is found. For codes with more than three codewords, it is tighter than the sphere packing bound, but requires exactly the same computing effort. Furthermore, tight approximations are proposed to simplify the computation of both the exact average error probability and the two bounds. For the binary symmetric channel and the binary erasure channel, bounds on the average block error probability for i.i.d.\ random coding are derived and compared to the exact calculations.
The block error probability under maximum likelihood decoding of general linear block codes and code ensembles over the q-ary symmetric channel is analyzed. The analysis makes use of two types of upper bounds and it is based on the codes (code ensembles) distance spectra. The first bound generalizes Poltyrev's union bound for the binary symmetric channel. The second bound relies on typical pairs decoding. The two bounds are developed in an asymptotic setting to analyze the behavior of linear block code ensembles, in terms of error exponent and maximum-likelihood decoding threshold. A sphere-packing lower bound is also developed, to provide a reference for the finite-length performance.
New lower bounds on the error probability of block codes with maximum-likelihood decoding are proposed. The bounds are obtained by applying a new lower bound on the probability of a union of events, derived by improving on de Caen's lower bound. The new bound includes an arbitrary function to be optimized in order to achieve the tightest results. Since the optimal choice of this function is known, but leads to a trivial and useless identity, we find several useful approximations for it, each resulting in a new lower bound. For the additive white Gaussian noise (AWGN) channel and the binary-symmetric channel (BSC), the optimal choice of the optimization function is stated and several approximations are proposed. When the bounds are further specialized to linear codes, the only knowledge on the code used is its weight enumeration. The results are shown to be tighter than the latest bounds in the current literature, such as those by Seguin (1998) and by Keren and Litsyn (2001). Moreover, for the BSC, the new bounds widen the range of rates for which the union bound analysis applies, thus improving on the bound to the error exponent compared with the de Caen-based bounds.
We derive both upper and lower bounds on the decoding error probability of maximum-likelihood (ML) decoded low-density parity-check (LDPC) codes. The results hold for any binary-input symmetric-output channel. Our results indicate that for various appropriately chosen ensembles of LDPC codes, reliable communication is possible up to channel capacity. However, the ensemble averaged decoding error probability decreases polynomially, and not exponentially. The lower and upper bounds coincide asymptotically, thus showing the tightness of the bounds. However, for ensembles with suitably chosen parameters, the error probability of almost all codes is exponentially decreasing, with an error exponent that can be set arbitrarily close to the standard random coding exponent.
The performance of maximum-likelihood (ML) decoded binary linear block codes over the additive white Gaussian noise (AWGN) channel is addressed via the tangential sphere bound (TSB) and two of its recent improved versions. The correspondence is focused on the derivation of the error exponents of these bounds. Although it was shown that some recent improvements of the TSB tighten this bound for finite-length codes, it is demonstrated in this correspondence that their error exponents coincide. For an arbitrary ensemble of binary linear block codes, the common value of these error exponents is explicitly expressed in terms of the asymptotic growth rate of the average distance spectrum
In this paper, we derive an upper bound for the average block error probability of a standard irregular low-density parity-check (LDPC) code ensemble under the maximum-likelihood (ML) decoding. Moreover, we show that the upper bound asymptotically decreases polynomially with the code length. Furthermore, when we consider several regular LDPC code ensembles as special cases of standard irregular ones over an additive white Gaussian noise channel, we numerically show that the signal-to-noise ratio (SNR) thresholds at which the proposed bound converges to zero as the code length tends to infinity are smaller than those for a bound provided by Miller et al. We also give an example of a standard irregular LDPC code ensemble which has a lower SNR threshold than a given regular LDPC code ensemble.