Datapath widths in state-of-the-art Turbo and Viterbi decoder implementations depend on estimated upper bounds of the differences of processed metrics. Aiming at highest area and energy efficiency, this paper presents...
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Datapath widths in state-of-the-art Turbo and Viterbi decoder implementations depend on estimated upper bounds of the differences of processed metrics. Aiming at highest area and energy efficiency, this paper presents guidelines for designing Turbo and Viterbi decoder datapaths with minimal widths. This is based on maximum absolute values of branch, state and path metric differences within theMax-Log-MAP respectively Viterbi decoding algorithm applying modulo normalization. The proposed methodology for determining the maximum absolute values covers punctured as well as n-input binary convolutional and Turbo codes so it accommodates higherradix add-compare-select operations. Maximum absolute values of metric differences and minimum datapath widths are presented for the 3GPP-LTE, DVB-RCS2 and IEEE-802.16 (WiMAX) compliant Turbo decoders and for the IEEE-802.11 (Wi-Fi), IEEE-802.16 (WiMAX) and 3GPP-LTE compliant Viterbi decoders. Besides, a new dynamic branch-metric saturation scheme is presented, which enables a further datapath width reduction within Turbo decoders. In total, a datapath width reduction of two bits (-20 %) is achieved applying radix-4 Max-Log-MAP arithmetic. An overall area-time-energy complexity reduction of 31% is achieved for a soft-input soft-output decoder and of 24% for the LTE Turbo decoder.
In high frequency high data rate transmission (HF-HDRT) systems, the intersymbol interference and deep fading of ionosphere channel seriously hindered the improvement of data transmission rate. In order to solve these...
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ISBN:
(纸本)9781479966370
In high frequency high data rate transmission (HF-HDRT) systems, the intersymbol interference and deep fading of ionosphere channel seriously hindered the improvement of data transmission rate. In order to solve these problems, a novel frequency domain iterative combining-equalization (FD-ICE) algorithm based on minimum mean square error (MMSE) criterion is proposed, which can realize diversity combining and equalization simultaneously, and iteratively exchange log-likelihood ratio values between soft-inputsoft-output (SISO) decoder and SISO combining-equalizer. Moreover, a simplified method fast frequency domain iterative combining-equalization (FFD-ICE) with low performance loss is given. Simulation results show that the proposed FD-ICE algorithm can provide a much better performance especially when more antennas are used and the low-complexity FFD-ICE algorithm can achieve an excellent trade off between complexity and performance. Both of the FD-ICE and the simplified FFD-ICE algorithm converge faster than the conventional iterative equalization.
The advent of turbo decoding techniques has revived the interest in soft-inputsoft-output (SISO) decoders that are capable of outputting reliability information (soft decisions). A classical way of implementing a SIS...
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ISBN:
(纸本)0780383443
The advent of turbo decoding techniques has revived the interest in soft-inputsoft-output (SISO) decoders that are capable of outputting reliability information (soft decisions). A classical way of implementing a SISO decoder for a linear block code is to use a trellis-based decoding algorithm, such as MAP, Max-Log-MAP or SOVA [1]. Recently, the idea of sectionalizing the trellis diagram representing a code has been proposed as a means to decrease the decoding complexity associated with the SISO decoders [1], [2]. In this paper, we investigate the application of a nonbinary SOVA decoding algorithm [3] to the sectionalized trellis of a binary linear block code. We generalize the nonbinary SOVA to a code with time-varying symbol set. Based on the above study, we also derive a new simplified algorithm, called the Nonbinary SOVA with Bit-Level Reliabilities (NSOVA with BLR), that we also investigate in terms of complexity for a serial and a parallel implementation. Based on the computational complexity figures for both algorithms,, we show that optimal sectionalizations can be found, that minimize the computational complexity entailed when using these algorithms for decoding.
This letter studies the numerical properties of Log-MAP-based soft-inputsoft-output decoding. The ranges of the differences between the path metrics, the softoutput, and the complete information are derived. Since t...
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This letter studies the numerical properties of Log-MAP-based soft-inputsoft-output decoding. The ranges of the differences between the path metrics, the softoutput, and the complete information are derived. Since the Log-MAP algorithm is functionally dependent only upon the differences between path metrics, not their magnitudes, a modulo normalization technique that is automatically implemented in two's complement arithmetic can be used to accommodate overflow of the path metrics. An expression for the minimum internal data width of a soft-input soft-output decoder that employs the modulo normalization technique is derived. As an application, the minimum internal data width of a decoder for the turbo code used in third-generation mobile communication systems is determined.
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