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ABSTRACT: To realize energy efficient broadcasting receivers the complexity of the applied algorithms should be adaptive, i.e. the number of required operations should decrease with improving reception conditions. In case of channel decoding algorithms this adaptive behavior can be achieved by syndrome based decoding methods, which allow a reduction of the receiver's energy consumption in above-average reception conditions. This paper extends the syndrome decoding approach to trellis coded modulation, as applied in the ATSC DTV system. Furthermore, the application of the syndrome concept to receivers based on Turbo equalization is considered. In this case the syndrome approach enables a reduction of the soft output decoder's complexity.
Signals, Systems and Computers (ASILOMAR), 2010 Conference Record of the Forty Fourth Asilomar Conference on; 12/2010
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ABSTRACT: This paper investigates the implementation of a trellis based syndrome decoder on symmetric multiprocessor (SMP) platforms. Two advantages of the proposed approach will be exposed: First, compared to conventional parallel Viterbi decoder implementations, the syndrome decoder achieves a higher parallel efficiency in terms of speedup on the SMP platform. This is realized by reducing the computational overhead of the parallel Viterbi algorithm implementation. Second, it offers an adaptive complexity, i.e. the number of decoding operations decreases with improving transmission conditions. This property can be exploited to reduce the average energy consumption of a radio receiver. Measurement results are shown for two SMP platforms: ARM's MPCore and Intel's Core i7.
Wireless Communication Systems (ISWCS), 2010 7th International Symposium on; 10/2010
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ABSTRACT: Turbo equalization is a powerful method to iteratively detect and decode convolutionally encoded data that is corrupted by inter symbol interference (ISI) and Gaussian noise. It is based on the exchange of reliability information between the equalizer and the decoder, which is typically some sort of maximum a posteriori (MAP) decoder. While the number of remaining errors in the received sequence decreases during the iteration process, the computational effort for decoding remains unchanged in each iteration. In this paper a syndrome based MAP decoder is proposed, that is capable of reducing the computational decoding effort during the iteration process without significantly influencing the convergence behavior.
Turbo Codes and Iterative Information Processing (ISTC), 2010 6th International Symposium on; 10/2010
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ABSTRACT: A block processing approach for decoding of convolutional codes is proposed. The approach is based on the fact that it is possible for Scarce-State-Transition decoding and syndrome decoding to determine the probability of a certain trellis state before the actual decoding happens. This allows the separation of the received sequence into independant blocks with known initial and final states, thus making overlapping or modifications of the encoder or the information stream unnecessary. The proposed scheme offers potentials for both parallelization and reduction of power consumption.
Wireless Communication Systems. 2008. ISWCS '08. IEEE International Symposium on; 11/2008
