In many existing optical and magnetic digital recording systems, data is usually encoded by a cascade of several encoders, followed by a channel with IS1 (intersymbol interference). Conventional receivers follow a one-path approach, where an equalizer is followed by a cascade of appropriate decoders. We propose a backward compatible iterative receiver which uses generalized erasures. An AZD (am...

We propose a framework for iterative joint sourcechannel decoding of JPEG2000 codestreams. At the encoder, JPEG2000 is used to perform source coding with certain error resilience (ER) modes, and LDPC codes are used to perform channel coding. During decoding, the source decoder uses the ER modes to identify corrupt sections of the codestream and provides this information to the channel decoder. ...

In this contribution we investigate the performance of the UMTS Long Term Evolution (LTE) physical layer using turbo coding and 64QAM with Gray mapping. We show how the mapping of systematic and parity bits to the six different bit positions defining one complex 64QAM symbol influences the convergence of the turbo decoder and thereby the bit error rate (BER) performance as well as number of nec...

Turbo codes are usually constructed using systematic recursive convolutional codes (SRCC’s) as constituent codes. In this paper, we introduce a new class of turbo codes that uses nonsystematic recursive convolutional codes (NSRCC’s) as constituent codes. A systematic constituent code then becomes a particular case of this more general class. The use of this larger class of constituent codes enh...

| Soft-input/soft-output symbol decoding plays a signiicant role in iterative decoding. We propose a simple optimal soft-input/soft-output symbol decoding algorithm for linear block codes which requires one forward recursion using a trellis. For many codes the decoding complexity is lower than previous methods, such as the algorithm by Bahl et. al. 1], and the decrease is shown at its most when...

Soft-input/soft-output symbol decoding plays a significant role in iterative decoding. We propose a simple optimal soft-input/softoutput symbol decoding algorithm for linear block codes which requires one forward recursion using a trellis. For many codes the decoding complexity is lower than previous methods, such as the algorithm by Bahl et al. [1], and the decrease is shown at its most when d...

Motivated by the success of iterative decoding algorithms, we consider the general problem of making inferences based on observed data, which are known a-priori to satisfy multiple sets of constraints. We consider relative entropy minimisation and an iterative algorithm for its calculation, which exploits the presence of multiple constraints. Using these principles, optimal iterative decoders, ...

You will recall that the capacity of the binary erasure channel (BEC) with erasure probability p is 1 − p. It was proved [LMSS01] that LDPC codes can achieve the capacity of these channels. In particular, for any � > 0, there exists an infinite family of LDPC codes that have arbitrarily low error probability on the BEC with erasure probability 1 − p − �. To explain how these codes are construct...

In the above paper [1], the second paragraph of the introduction was accidentally omitted. This paragraph and corresponding citations should appear as follows. As for iterative decoding of LDPC codes, there are two main scheduling approaches, probabilistic approaches and deterministic approaches. Although both scheduling approaches provide better complexity/performance tradeoff than their stand...

Clipping is applied to superposition coding systems to reduce the peak-to-average power ratio (PAPR) of the transmitted signal. The performance limit is investigated through evaluating the mutual information driven by the induced peak-power-limited input signals. It is shown that the channel capacity can be approached by clipped superposition coding systems. To alleviate the performance degrada...