A 2.15GBit/s turbo code decoder for LTE advanced base station applications

Ilnseher, Thomas; Kienle, Frank; Weis, Christian; Wehn, Norbert

doi:10.1109/istc.2012.6325191

Cited by 41 publications

(72 citation statements)

References 11 publications

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“…The first method we will discuss is pipelining, which is employed extensively within the architectures of [48], [51], [52]. Pipelining reduces the critical path between two registers by adding additional registers to the middle of this path.…”

Section: A Data Path Considerationsmentioning

confidence: 99%

“…Figure 12 shows an example of pipelining in the turbo decoder of [51], which uses a similar decoder core to that proposed by the authors of [46], [49]. High-throughput turbo decoders, such as those proposed by [49], [52], [53], typically employ a multitude of these cores in parallel. The architecture of Figure 12 employs separate hardware units for calculating the α (forward state-metrics) and β (reverse state-metrics), each having dedicated hardware for generating the γ values.…”

Section: A Data Path Considerationsmentioning

confidence: 99%

“…Another beneficial technique for the implementation of turbo decoders is the Radix-4 transformation of [44], [52], which combines two trellis stages into a single one. Owing to this, the decoder considers twice the number of a priori LLRs at once and the number of transitions emerging from each state of the Radix-4 trellis is squared.…”

Section: B Algorithm Controlmentioning

confidence: 99%

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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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Section: A Data Path Considerationsmentioning

confidence: 99%

Section: A Data Path Considerationsmentioning

confidence: 99%

Section: B Algorithm Controlmentioning

confidence: 99%

See 1 more Smart Citation

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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“…In [12], the parallelism of the Log-MAP algorithm was increased by decomposing the trellis into K number of sub-trellises and performing the Log-MAP algorithm on each in parallel, hence reducing the corresponding processing time by a factor of 1/K. Other approaches include pipelining the operations of the Log-MAP algorithm [13], so that different operations are performed in parallel, in different parts of the decoding hardware. Similarly, the radix-4 technique can be employed for processing two trellis stages at a time [13].…”

Section: Introductionmentioning

confidence: 99%

“…Other approaches include pipelining the operations of the Log-MAP algorithm [13], so that different operations are performed in parallel, in different parts of the decoding hardware. Similarly, the radix-4 technique can be employed for processing two trellis stages at a time [13]. Furthermore, some of the Log-MAP calculations can be replaced with lower-complexity approximations [11], so that a greater number of these calculations can be performed in parallel using the same amount of hardware.…”

Section: Introductionmentioning

confidence: 99%

Bit-by-Bit Iterative Decoding Expedites the Convergence of Repeat Accumulate Decoders

Chen

Zhang

Maunder

et al. 2015

IEEE Trans. Commun.

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Abstract-In this paper, we propose bit-by-bit iterative decoding for expediting the convergence of Repeat Accumulate (RA) decoders. In a conventional RA decoder, the repeat and accumulate component decoders are operated iteratively, in order to facilitate near-capacity communication. However, whenever one decoder is activated, the other is kept idle. The outputs of the active component decoder are stored until its operation is completed, whereupon the outputs are forwarded to the other decoder all at once and the activation of the decoders is swapped. The proposed bit-by-bit RA decoder expedites this process by allowing both component decoders to operate simultaneously, continuously exchanging outputs without buffering. We present both EXtrinsic Information Transfer (EXIT) charts and Bit Error Ratio (BER) results, which demonstrate that the proposed bit-by-bit RA decoder requires fewer decoding iterations to converge, at the cost of a slightly increased complexity per decoding iteration. Overall, we demonstrate that in a range of practical scenarios, the proposed bit-by-bit RA offers gains of up to 0.86 dB, without imposing any additional decoding complexity and without requiring any additional transmissionenergy, -bandwidth or -duration.

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Towards Tbit/s Wireless Communication Baseband Processing: When Shannon meets Moore

Herrmann

Wehn

2021

Multi‐Processor System‐on‐Chip 2

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A 2.15GBit/s turbo code decoder for LTE advanced base station applications

Cited by 41 publications

References 11 publications

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

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

Bit-by-Bit Iterative Decoding Expedites the Convergence of Repeat Accumulate Decoders

Towards Tbit/s Wireless Communication Baseband Processing: When Shannon meets Moore

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