We revisit the information-theoretic analysis of bit-interleaved coded modulation (BICM) by modeling the BICM decoder as a mismatched decoder. The mismatched decoding model is well defined for finite, yet arbitrary, block lengths, and naturally captures the channel memory among the bits belonging to the same symbol. We give two independent proofs of the achievability of the BICM capacity calculated by Caire et al., where BICM was modeled as a set of independent parallel binary-input channels whose output is the bitwise log-likelihood ratio. Our first achievability proof uses typical sequences, and shows that due to the random coding construction, the interleaver is not required. The second proof is based on the random coding error exponents with mismatched decoding, where the largest achievable rate is the generalized mutual information. Moreover, the generalized mutual information of the mismatched decoder coincides with the infinite-interleaver BICM capacity. We show that the error exponent-and hence the cutoff rate-of the BICM mismatched decoder is upper-bounded by that of coded modulation and may thus be lower than in the infinite-interleaved model; for binary reflected Gray mapping in Gaussian channels the loss in error exponent is small. We also consider the mutual information appearing in the analysis of iterative decoding of BICM with extrinsic information transfer (EXIT) charts: if the symbol metric has knowledge of the transmitted symbol, EXIT mutual information admits a representation as a pseudo-generalized mutual information, which is in general not achievable. A different symbol decoding metric, for which the extrinsic side information refers to the hypothesized symbol, induces a generalized mutual information lower than the coded modulation capacity. In this case, perfect extrinsic side information turns the mismatched-decoder error exponent into that of coded modulation.

This paper investigates the performance of M-ary amplitude-phase shift keying (APSK) digital modulation over typical nonlinear satellite channels. The effect of the satellite nonlinearity is studied, and distortion pre- and post-compensation techniques for coded APSK are presented. Moreover, clock timing, signal amplitude and carrier phase recovery schemes are discussed. For the latter, a new class of non turbo decoder-aided closed-loop phase synchronizers featuring good performance and low complexity is studied. Finally, an end-to-end coded APSK system simulator inclusive of the satellite channel model and synchronization sub-systems is discussed and its performance compared to standard trellis-coded QAM concatenated with Reed-Solomon codes, showing a remarkable gain in both power and spectral efficiency. Coded APSK, recently selected for the new standard -DVB-S2- for digital video broadcasting and interactive broadband satellite services, is shown to represent a powerand spectral-efficient solution for satellite nonlinear channels

This paper considers the problem of channel coding with a given (possibly suboptimal) maximum-metric decoding rule. A cost-constrained random-coding ensemble with multiple auxiliary costs is introduced, and is shown to achieve error exponents and second-order coding rates matching those of constant-composition random coding, while being directly applicable to channels with infinite or continuous alphabets. The number of auxiliary costs required to match the error exponents and second-order rates of constant-composition coding is studied, and is shown to be at most two. For independent identically distributed random coding, asymptotic estimates of two well-known non-asymptotic bounds are given using saddlepoint approximations. Each expression is shown to characterize the asymptotic behavior of the corresponding random-coding bound at both fixed and varying rates, thus unifying the regimes characterized by error exponents, second-order rates, and moderate deviations. For fixed rates, novel exact asymptotics expressions are obtained to within a multiplicative 1+o(1) term. Using numerical examples, it is shown that the saddlepoint approximations are highly accurate even at short block lengths.

The principle of coding in the signal space follows directly from Shannon’s analysis of waveform Gaussian channels subject to an input constraint. The early design of communication systems focused separately on modulation, namely signal design and detection, and error correcting codes, which deal with errors introduced at the demodulator of the underlying waveform channel. The correct perspective of signal-space coding, although never out of sight of information theorists, was brought back into the focus of coding theorists and system designers by Imai’s and Ungerböck’s pioneering works on coded modulation. More recently, powerful families of binary codes with a good tradeoff between performance and decoding complexity have been (re-)discovered. Bit-Interleaved Coded Modulation (BICM) is a pragmatic approach combining the best out of both worlds: it takes advantage of the signal-space coding perspective, whilst allowing for the use of powerful families of binary codes with virtually any modulation format. BICM avoids the need for the complicated and somewhat less flexible design typical of coded modulation. As a matter of fact, most of today’s systems that achieve high spectral efficiency such as DSL, Wireless LANs, WiMax and evolutions thereof, as well as systems based on low spectral efficiency orthogonal modulation, feature BICM, making BICM the de-facto general coding technique for waveform channels. The theoretical characterization of BICM is at the basis of efficient coding design techniques and also of improved BICM decoders, e.g., those based on the belief propagation iterative algorithm and approximations thereof. In this text, we review the theoretical foundations of BICM under the unified framework of error exponents for mismatched decoding. This framework allows an accurate analysis without any particular assumptions on the length of the interleaver or independence between the multiple bits in a symbol. We further consider the sensitivity of the BICM capacity with respect to the signal-to-noise ratio (SNR), and obtain a wideband regime (or low-SNR regime) characterization. We review efficient tools for the error probability analysis of BICM that go beyond the standard approach of considering infinite interleaving and take into consideration the dependency of the coded bit observations introduced by the modulation. We also present bounds that improve upon the union bound in the region beyond the cutoff rate, and are essential to characterize the performance of modern randomlike codes used in concatenation with BICM. Finally, we turn our attention to BICM with iterative decoding, we review extrinsic information transfer charts, the area theorem and code design via curve fitting. We conclude with an overview of some applications of BICM beyond the classical coherent Gaussian channel.

This correspondence presents a simple method to accurately compute the error probability of bit-interleaved coded modulation (BICM). Thanks to the binary-input output-symmetric (BIOS) nature of the channel, the pairwise error probability (PEP) is equal to the tail probability of a sum of random variables with a particular distribution. This probability is in turn computed with a saddlepoint approximation. Its precision is numerically validated for coded transmission over standard Gaussian noise and fully interleaved fading channels for both convolutional and turbo-like codes.

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