Low-Complexity Soft-Decision Viterbi Algorithm for IM/DD 56-Gb/s PAM-4 System

2019 ◽  
Vol 31 (5) ◽  
pp. 361-364 ◽  
Author(s):  
Hae Young Rha ◽  
Sang-Rok Moon ◽  
Hun-Sik Kang ◽  
Seung-Woo Lee ◽  
In-Ki Hwang ◽  
...  
2018 ◽  
Vol 127 ◽  
pp. 284-292 ◽  
Author(s):  
M.S. El Kasmi Alaoui ◽  
S. Nouh ◽  
A. Marzak

Electronics ◽  
2018 ◽  
Vol 8 (1) ◽  
pp. 10 ◽  
Author(s):  
Vicente Torres ◽  
Javier Valls ◽  
Maria Canet ◽  
Francisco García-Herrero

In this work, we present a new architecture for soft-decision Reed–Solomon (RS) Low-Complexity Chase (LCC) decoding. The proposed architecture is scalable and can be used for a high number of test vectors. We propose a novel Multiplicity Assignment stage that sorts and stores only the location of the errors inside the symbols and the powers of α that identify the positions of the symbols in the frame. Novel schematics for the Syndrome Update and Symbol Modification blocks that are adapted to the proposed sorting stage are also presented. We also propose novel solutions for the problems that arise when a high number of test vectors is processed. We implemented three decoders: a η = 4 LCC decoder and two decoders that only decode 31 and 60 test vectors of true η = 5 and η = 6 LCC decoders, respectively. For example, our η = 4 decoder requires 29% less look-up tables in Virtex-V Field Programmable Gate Array (FPGA) devices than the best soft-decision RS decoder published to date, while has a 0.07 dB coding gain over that decoder.


2021 ◽  
Vol 8 (4) ◽  
pp. 1-25
Author(s):  
Saleh Khalaj Monfared ◽  
Omid Hajihassani ◽  
Vahid Mohsseni ◽  
Dara Rahmati ◽  
Saeid Gorgin

In this work, we present a novel bitsliced high-performance Viterbi algorithm suitable for high-throughput and data-intensive communication. A new column-major data representation scheme coupled with the bitsliced architecture is employed in our proposed Viterbi decoder that enables the maximum utilization of the parallel processing units in modern parallel accelerators. With the help of the proposed alteration of the data scheme, instead of the conventional bit-by-bit operations, 32-bit chunks of data are processed by each processing unit. This means that a single bitsliced parallel Viterbi decoder is capable of decoding 32 different chunks of data simultaneously. Here, the Viterbi’s Add-Compare-Select procedure is implemented with our proposed bitslicing technique, where it is shown that the bitsliced operations for the Viterbi internal functionalities are efficient in terms of their performance and complexity. We have achieved this level of high parallelism while keeping an acceptable bit error rate performance for our proposed methodology. Our suggested hard and soft-decision Viterbi decoder implementations on GPU platforms outperform the fastest previously proposed works by 4.3{\times } and 2.3{\times } , achieving 21.41 and 8.24 Gbps on Tesla V100, respectively.


Author(s):  
M. N. Sakib ◽  
V. Mahalingam ◽  
A. J. Wong ◽  
W. J. Gross ◽  
O. Liboiron-Ladouceur

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