Sequential decoding

About: Sequential decoding is a research topic. Over the lifetime, 8667 publications have been published within this topic receiving 204271 citations.

Iterative Decoding Trajectories of Parallel Concatenated Codes

Abstract: Mutual information transfer characteristics for soft in/soft out decoders are proposed as a tool to better understand the convergence behavior of iterative decoding schemes. The exchange of extrinsic information is visualized as a decoding trajectory in the Extrinsic Information Transfer Chart. This allows the prediction of turbo cliff position and bit error rate after an arbitrary number of iterations. The influence of code memory, generator polynomials as well as different constituent codes on the convergence behavior is studied for parallel concatenated codes.

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes

Abstract: From the Publisher: Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes combines trellises and trellis-based decoding algorithms for linear codes together in a simple and unified form. The approach is to explain the material in an easily understood manner with minimal mathematical rigor. Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes is intended for practicing communication engineers who want to have a fast grasp and understanding of the subject. This book can also be used as a text for advanced courses on the subject.

Fast Successive-Cancellation Decoding of Polar Codes: Identification and Decoding of New Nodes

Abstract: The decoding latency of polar codes can be reduced by implementing fast parallel decoders in the last stages of decoding. In this letter, we present five such decoders corresponding to different frozen-bit sequences to improve the decoding speed of polar codes. Implementing them achieves significant latency reduction without tangibly altering the bit-error-rate performance of the code.

Performance versus overhead for fountain codes over F q

Abstract: Fountain codes for packet erasure recovery are investigated over Galois fields of order q ? 2. It is shown through development of tight upper and lower bounds on the decoding failure probability under maximum likelihood decoding, that the adoption of higher order Galois fields is beneficial, in terms of performance, for linear random fountain codes. Moreover, it is illustrated how Raptor codes can provide performances very close to those of random fountain codes, with an affordable encoding and decoding complexity. Non-binary Raptor codes turn out to represent an appealing option for applications requiring severe constraints in terms of performance versus overhead, especially for small source block sizes.

Soft decision metric generation for QAM with channel estimation error

Abstract: The channel code bit log likelihood ratio (LLR) for soft decision decoding is derived for quadrature amplitude modulated signals (QAM). The effect of imperfect channel knowledge on soft decision decoding performance is studied. Our results indicate this effect increases with channel estimation error and/or QAM modulation level. A metric based on generalized log likelihood ratio (GLLR) is derived for soft decision channel decoding with imperfect channel knowledge. Numerical results show that the GLLR-based metric outperforms the conventional minimum distance decoding metric that does not take into account channel estimation error.