Sequential decoding

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

Near optimum universal belief propagation based decoding of LDPC codes

Abstract: In this paper, we propose a normalized belief propagation-based algorithm which utilizes normalization to improve the accuracy of the soft values delivered by a previously proposed simplified belief propagation-based algorithm, and can achieve an error performance very close to that of belief propagation. We also extend the principle of normalization to improve the performance of the Max-Log-MAP algorithm in turbo decoding.

Binary Systematic Network Coding for Progressive Packet Decoding

Abstract: We consider binary systematic network codes and investigate their capability of decoding a source message either in full or in part. We carry out a probability analysis, derive closed-form expressions for the decoding probability and show that systematic network coding outperforms conventional network coding. We also develop an algorithm based on Gaussian elimination that allows progressive decoding of source packets. Simulation results show that the proposed decoding algorithm can achieve the theoretical optimal performance. Furthermore, we demonstrate that systematic network codes equipped with the proposed algorithm are good candidates for progressive packet recovery owing to their overall decoding delay characteristics.

Successive cancellation decoding of polar codes using stochastic computing

Abstract: Polar codes have emerged as the most favorable channel codes for their unique capacity-achieving property. To date, numerous approaches for efficient decoding of polar codes have been reported. However, these prior efforts focused on design of polar decoders via deterministic computation, while the behavior of stochastic polar decoder, which can have potential advantages such as low complexity and strong error-resilience, has not been studied in existing literatures. This paper, for the first time, investigates polar decoding using stochastic logic. Specifically, the commonly-used successive cancellation (SC) algorithm is reformulated into the stochastic form. Several methods that can potentially improve decoding performance are discussed and analyzed. Simulation results show that a stochastic SC decoder can achieve similar error-correcting performance as its deterministic counterpart. This work can pave the way for future hardware design of stochastic polar codes decoders.

Path partitions and forward-only trellis algorithms

Abstract: This is a semitutorial paper on trellis-based algorithms. We argue that most decoding/detection algorithms described on trellises can be formulated as path-partitioning algorithms, with proper definitions of mappings from subsets of paths to metrics of subsets. Thereby, the only two operations needed are path-concatenation and path-collection, which play the roles of multiplication and addition, respectively. Furthermore, we show that the trellis structure permits the path-partitioning algorithms to be formulated as forward-only algorithms (with structures resembling the Viterbi (1967) algorithm), thus eliminating the need for backward computations regardless of what task needs to be performed on the trellis. While all of the actual decoding/detection algorithms presented here are rederivations of variations of previously known methods, we believe that the exposition of the algorithms in a unified manner as forward-only path-partitioning algorithms is the most intuitive manner in which to generalize the Viterbi algorithm. We also believe that this approach may, in fact, influence the practical implementation of the algorithms as well as influence the construction of other forward-only algorithms (e.g., byte-wise forward-only detection algorithms).

Optimal binary phase codes and sidelobe-free decoding filters with application to incoherent scatter radar

Abstract: . This paper presents binary phase codes and corresponding decoding filters which are optimal in the sense that they produce no sidelobes and they maximise the signal-to-noise ratio (SNR henceforth). The search is made by investigating all possible binary phase codes with a given length. After selecting the code, the first step is to find a filter which produces no sidelobes. This is possible for all codes with no zeros in the frequency domain, and it turns out that most codes satisfy this requirement. An example of a code which cannot be decoded in this way is a code with a single phase, i.e. a long pulse. The second step is to investigate the SNR performance of the codes. Then the optimal code of a given length is the one with the highest SNR at the filter output. All codes with lengths of 3–25 bits were studied, which means investigating 33554428 binary phase codes. It turns out that all Barker codes except the 11-bit code are optimal in the above sense. It is well known that the performance of matched-filter decoding of Barker codes is better than decoding without sidelobes. In the case of the 7-bit Barker code, it is shown here that the SNR given by sidelobe-free decoding is nearly 30% worse than that of standard decoding, but for the 13-bit code sidelobe-free decoding is only about 5% worse. The deterioration of SNR should be evaluated against the benefits gained in disposing of the sidelobes, which, even for the 13-bit code, contribute by 7.1% to the total signal power from a homogeneous target. Thus, regions of weak scattering can be contaminated by the sidelobes from neighbouring layers of strong scattering, causing broadening of thin spatial structures and giving a lower spatial resolution than implied by the bit length. A practical example is shown where sidelobes mask a weak signal when the standard matched filter is used in the analysis. An improvement is achieved when sidelobe-free filtering is carried out. Key words. Radio science (ionospheric physics; signal processing; instruments and techniques)