Error Floor Removal for Bit-Interleaved Coded Modulation with Iterative Detection

Pfletschinger, Stephan; Sanzi, F.

doi:10.1109/twc.2006.05163

Cited by 67 publications

(50 citation statements)

References 21 publications

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“…Similarly to the LDPC BICM-ID construction, we can design an improved BICM-ID scheme based on RA codes [93,120,127]. In particular, we consider the accumulator shown in Figure 5.17 of rate a m m .…”

Section: Ra Bicm-idmentioning

confidence: 99%

“…The optimized RA-BICM-ID codes could be further improved by introducing irregularity at the accumulator side, and by possibly optimizing the connections at the accumulator and the constellation mapping. A number of improved BICM-ID code constructions have been proposed in the literature [93,120,121,127]. Based on the concepts illustrated in this section, turbo-coded modulation schemes [99] can also be put into the BICM-ID framework.…”

Section: Concluding Remarks and Related Workmentioning

confidence: 99%

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Bit-Interleaved Coded Modulation

Fàbregas

Martinez

Caire

2007

FNT in Communications and Information Theory

186

165

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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. List of Abbreviations, Acronyms, and SymbolsRatio between average bit energy and noise spectral densityReliability function at rate R E bicm 0 (ρ, s) BICM random coding exponent E cm 0 (ρ) CM random coding exponent ...

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Section: Ra Bicm-idmentioning

confidence: 99%

Section: Concluding Remarks and Related Workmentioning

confidence: 99%

Bit-Interleaved Coded Modulation

Fàbregas

Martinez

Caire

2007

FNT in Communications and Information Theory

186

165

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“…The interleaved u : is then encoded by a rate-1 recursive systematic convolutional (RSC) code, producing bit stream v : . This rate-1 RSC coding is also called 'doping' [21] since the output bits are doped with both info-bits and parity-bits. Then after the mapping of bits v : to 8PSK constellation, the signal is transmitted over the additive white Gaussian noise (AWGN) channel.…”

Section: System Overviewmentioning

confidence: 99%

“…Then after the mapping of bits v : to 8PSK constellation, the signal is transmitted over the additive white Gaussian noise (AWGN) channel. Dependencies between the modulated symbols are introduced by the inner RSC code, for the purpose of reaching EXIT point (1, 1) [21], which corresponds to error-floor removed iterative decoding.…”

Section: System Overviewmentioning

confidence: 99%

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Irregular 8PSK mapping for variable length codes with small blocks in a BICM-ID system

Dai

Zhang

Gao

et al. 2015

J Wireless Com Network

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Iterative decoding is an effective technique to approach the channel capacity for very large block sizes with enough iterations. However, due to the limitation of bandwidth and delay, small blocks of data are much more commonly applied in practical communications, and low iteration counts are usually preferred for both decoding complexity and delay consideration. In such cases, the design rules of near capacity decoding-which is generally asymptotic with respect to the block size-may cause inferior performance. To overcome this problem for 8-phase shift keying (8PSK) modulated variable length codes (VLCs), an irregular mapping scheme for the transmission system of bit-interleaved coded modulation with iterative decoding (BICM-ID) is studied in this paper. A submapping searching algorithm and an irregular mapping optimization algorithm are proposed aiming at maximizing the extrinsic mutual information after a target number of iterations. Simulation results show that for small data block size with a low iteration count, our scheme has advantages with respect to the existing near capacity systems optimized by the asymptotic tools.

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