Efficient Parallel Turbo-Decoding for High-Throughput Wireless Systems

Roth, Christoph; Belfanti, Sandro; Benkeser, Christian; Huang, Qiuting

doi:10.1109/tcsi.2013.2290831

Cited by 32 publications

(19 citation statements)

References 20 publications

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“…A sliding window scheme called Next Iteration Initialization (NII) [8] has been widely employed in many turbo decoder implementations [9,10] because it requires no dummy backward metrics and guard windows compared to the conventional algorithm. We further split a NII sliding window into two parts, each of whom is decoded by a decoding unit.…”

Section: Optimized Decoding Algorithmmentioning

confidence: 99%

A multi-core-based heterogeneous parallel turbo decoder

Zeng

Zhang

et al. 2017

IEICE Electron. Express

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It has always been a challenging task to implement a turbo decoder because it's typically the most compute-intensive and time-consuming part in a wireless communication system. This becomes especially obvious when realizing a turbo decoder through CPUs or GPUs. In this paper, we present a heterogeneous and highly reconfigurable parallel turbo decoder for LTE by employing a multi-core processor platform. A modified sliding-window algorithm is proposed to fully exploit the parallelism of turbo decoder, and a SIMD hardware module is designed for the multi-core processor to accelerate the decoding process. Synthesized result in a 65-nm CMOS process shows that the whole system can run at a maximum clock frequency of 830 MHz, and a decoding throughput of 135 Mbps is achieved for a codeword block length of 6144 at 6 iterations. In addition, the speed-up rate compared to an unaccelerated implementation through the same multicore platform is in the order of 800%.

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Section: Optimized Decoding Algorithmmentioning

confidence: 99%

A multi-core-based heterogeneous parallel turbo decoder

Zeng

Zhang

et al. 2017

IEICE Electron. Express

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“…Further detailed reading on the pre-backward technique is available in [40]. Other windowing techniques include the Previous Iteration Value Initialization (PIVI) technique of [39], [41], which is also known as State-Metric Propagation (SMP) [42]. This avoids the extra computation associated with the pre-backwards step by initializing the windows during the current turbo decoding iteration using the boundary conditions 'inherited' from the previous iteration.…”

Section: Four-level Quantizationmentioning

confidence: 99%

20 Years of Turbo Coding and Energy-Aware Design Guidelines for Energy-Constrained Wireless Applications

Brejza

Maunder

et al. 2016

IEEE Commun. Surv. Tutorials

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Abstract-During the last two decades, wireless communication has been revolutionized by near-capacity Error-Correcting Codes (ECCs), such as Turbo Codes (TCs), which offer a lower Bit Error Ratio (BER) than their predecessors, without requiring an increased transmission Energy Consumption (EC). Hence, TCs have found widespread employment in spectrum-constrained wireless communication applications, such as cellular telephony, Wireless Local Area Network (WLAN) and broadcast systems. Recently however, TCs have also been considered for energyconstrained wireless communication applications, such as Wireless Sensor Networks (WSNs) and the 'Internet of Things' (IoT). In these applications, TCs may also be employed for reducing the required transmission EC, instead of improving the BER. However, TCs have relatively high computational complexities and hence the associated signal-processing-related ECs are not insignificant. Therefore, when parameterizing TCs for employment in energy-constrained applications, both the processing EC and the transmission EC must be jointly considered. In this tutorial, we investigate holistic design methodologies conceived for this purpose. We commence by introducing turbo coding in detail, highlighting the various parameters of TCs and characterizing their impact on the encoded bit rate, on the Radio Frequency (RF) bandwidth requirement, on the transmission EC and on the BER. Following this, energy-efficient TC decoder ApplicationSpecific Integrated Circuit (ASIC) architecture designs are exemplified and the processing EC is characterized as a function of the TC parameters. Finally, the TC parameters are selected in order to minimize the sum of the processing EC and the transmission EC.

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“…Among all the references, [18,22,31] mainly focus on the interleaver design like our work. The multi-stage network from [22,29] introduces a Batcher network based parallel interleaver for high throughput decoding. However, the network has to be reconstructed when different level of parallelism is required.…”

Section: Comparison Analysismentioning

confidence: 99%

“…This work TCAS-I 2014 [29] TCAS-I 2014 [30] TCAS-I 2014 [31] JSSC 2013 [32] DATE 2013 [33] ISTC 2012 [15] Integration 2011 [18] JSSC 2011 [22] Standard ( …”

Section: Referencementioning

confidence: 99%

High performance parallel turbo decoder with configurable interleaving network for LTE application

Yan

et al. 2016

Integration

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Efficient Parallel Turbo-Decoding for High-Throughput Wireless Systems

Cited by 32 publications

References 20 publications

A multi-core-based heterogeneous parallel turbo decoder

A multi-core-based heterogeneous parallel turbo decoder

20 Years of Turbo Coding and Energy-Aware Design Guidelines for Energy-Constrained Wireless Applications

High performance parallel turbo decoder with configurable interleaving network for LTE application

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