Sequential decoding

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

Space-time decoding with imperfect channel estimation

Abstract: Under the assumption of a frequency-flat slow Rayleigh fading channel with multiple transmit and receive antennas, we examine the effects of imperfect estimation of the channel parameters on error probability when known pilot symbols are transmitted among information data. Three different receivers are considered. The first one derives an estimate of the channel [by using either a maximum-likelihood (ML) or a minimum mean square error (MMSE) criterion], and then uses this estimate in the same metric that would be applied if the channel were perfectly known. The second receiver derives again an estimate of the channel, but uses the ML metric conditioned on the channel estimate. Our last receiver simultaneously processes the pilot and data symbols received. Simulation results are exhibited, showing that only a relatively small percentage of the transmitted frame need be allocated to pilot symbols in order to experience an acceptable degradation of error probability due to imperfect channel knowledge. Algorithms for the recursive calculation of the decision metric of the last two receivers are also developed for application to sequential decoding of trellis space-time codes.

Windowed Decoding of Protograph-Based LDPC Convolutional Codes Over Erasure Channels

Abstract: We consider a windowed decoding scheme for LDPC convolutional codes that is based on the belief-propagation (BP) algorithm. We discuss the advantages of this decoding scheme and identify certain characteristics of LDPC convolutional code ensembles that exhibit good performance with the windowed decoder. We will consider the performance of these ensembles and codes over erasure channels with and without memory. We show that the structure of LDPC convolutional code ensembles is suitable to obtain performance close to the theoretical limits over the memoryless erasure channel, both for the BP decoder and windowed decoding. However, the same structure imposes limitations on the performance over erasure channels with memory.

Bounds on the maximum likelihood decoding error probability of low density parity check codes

Abstract: We derive both upper and lower bounds on the decoding error probability of maximum-likelihood (ML) decoded low-density parity-check (LDPC) codes. The results hold for any binary-input symmetric-output channel. Our results indicate that for various appropriately chosen ensembles of LDPC codes, reliable communication is possible up to channel capacity. However, the ensemble averaged decoding error probability decreases polynomially, and not exponentially. The lower and upper bounds coincide asymptotically, thus showing the tightness of the bounds. However, for ensembles with suitably chosen parameters, the error probability of almost all codes is exponentially decreasing, with an error exponent that can be set arbitrarily close to the standard random coding exponent.

The algebraic decoding of Goppa codes

Abstract: An interesting class of linear error-correcting codes has been found by Goppa [3], [4]. This paper presents algebraic decoding algorithms for the Goppa codes. These algorithms are only a little more complex than Berlekamp's well-known algorithm for BCH codes and, in fact, make essential use of his procedure. Hence the cost of decoding a Goppa code is similar to the cost of decoding a BCH code of comparable block length.

Approaching Shannon performance by iterative decoding of linear codes with low-density generator matrix

Abstract: We propose the use of linear codes with low density generator matrix to achieve a performance similar to that of turbo and standard low-density parity check codes. The use of iterative decoding techniques - message passing -over the corresponding graph achieves a performance close to the Shannon theoretical limit. As an advantage with respect to turbo and standard low-density parity check codes, the complexity of the decoding and encoding procedures is very low.