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Decoding Complexity (decoding + complexity)
Selected AbstractsEnhanced system design for download and streaming services using Raptor codes,,EUROPEAN TRANSACTIONS ON TELECOMMUNICATIONS, Issue 2 2009Tiago Gasiba Raptor codes have been recently standardised by 3rd Generation Partnership Project (3GPP) to be used in the application layer (AL) for multimedia broadcast and multicast services (MBMS) including download delivery and streaming delivery. Furthermore, digital video broadcast (DVB) has also recommended the inclusion of these Raptor codes for IP-datacast services. In this paper, enhancements on the system and receiver design using Raptor codes are studied, namely the permeable layer receiver (PLR) and the individual post-repair mechanism. With the PLR, the partial information ignored in the conventional receiver is passed from lower layer to higher layer. We show how a practical and efficient implementation of the Raptor decoder as a PLR can be done, which can not only achieve huge performance gains, but the gains can be achieved at an affordable low decoding complexity. Whereas the PLR is employed for enhancing both download and streaming services, the post-repair aims at guaranteeing reliable download delivery when a feedback channel is available. We propose here two efficient post-repair algorithms which fully exploit the properties of the Raptor codes. One allows to find a minimum set of source symbols to be requested in the post-delivery, and another allows to find a sufficient number of consecutive repair symbols. Selected simulations verify the good performance of proposed techniques. Copyright © 2008 John Wiley & Sons, Ltd. [source] BEAST decoding for block codesEUROPEAN TRANSACTIONS ON TELECOMMUNICATIONS, Issue 4 2004Irina E. Bocharova BEAST is a Bidirectional Efficient Algorithm for Searching code Trees. In this paper, it is used for decoding block codes over a binary-input memoryless channel. If no constraints are imposed on the decoding complexity (in terms of the number of visited nodes during the search), BEAST performs maximum-likelihood (ML) decoding. At the cost of a negligible performance degradation, BEAST can be constrained to perform almost-ML decoding with significantly reduced complexity. The benchmark for the complexity assessment is the number of nodes visited by the Viterbi algorithm operating on the minimal trellis of the code. The decoding complexity depends on the trellis structure of a given code, which is illustrated by three different forms of the generator matrix for the (24, 12, 8) Golay code. Simulation results that assess the error-rate performance and the decoding complexity of BEAST are presented for two longer codes. Copyright © 2004 AEI [source] Construction, analysis and performance of generalised woven codesEUROPEAN TRANSACTIONS ON TELECOMMUNICATIONS, Issue 2 2004Martin Bossert Generalised woven codes (WC) are constructed by combining the woven code structure with the idea of generalised concatenated codes, also known as multi-level codes. The required nested inner convolutional code is analysed. The encoder structure of this new class of codes is described and fundamental code parameters are derived. It is shown that generalised WC have a free distance which is superior to that of comparable WC. Several iterative and non-iterative decoding strategies are discussed. It is shown that the decoding complexity of the nested inner code is not larger than the decoding complexity of its mother code. Finally, bit error rates obtained from simulations are discussed and compared with other code structures like WC. Copyright © 2004 AEI [source] A forward-only recursion algorithm for MAP decoding of linear block codesINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 8 2002Hans-Jürgen Zepernick Abstract The evolution of digital mobile communications along with the increase of integrated circuit complexity has resulted in frequent use of error control coding to protect information against transmission errors. Soft decision decoding offers better error performance compared to hard decision decoding but on the expense of decoding complexity. The maximum a posteriori (MAP) decoder is a decoding algorithm which processes soft information and aims at minimizing bit error probability. In this paper, a matrix approach is presented which analytically describes MAP decoding of linear block codes in an original domain and a corresponding spectral domain. The trellis-based decoding approach belongs to the class of forward-only recursion algorithms. It is applicable to high rate block codes with a moderate number of parity bits and allows a simple implementation in the spectral domain in terms of storage requirements and computational complexity. Especially, the required storage space can be significantly reduced compared to conventional BCJR-based decoding algorithms. Copyright © 2002 John Wiley & Sons, Ltd. [source] | ||||||||||