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Practical Dynamic SC-Flip Polar Decoders: Algorithm and Implementation

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 Added by Furkan Ercan
 Publication date 2020
and research's language is English




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SC-Flip (SCF) is a low-complexity polar code decoding algorithm with improved performance, and is an alternative to high-complexity (CRC)-aided SC-List (CA-SCL) decoding. However, the performance improvement of SCF is limited since it can correct up to only one channel error ($omega=1$). Dynamic SCF (DSCF) algorithm tackles this problem by tackling multiple errors ($omega geq 1$), but it requires logarithmic and exponential computations, which make it infeasible for practical applications. In this work, we propose simplifications and approximations to make DSCF practically feasible. First, we reduce the transcendental computations of DSCF decoding to a constant approximation. Then, we show how to incorporate special node decoding techniques into DSCF algorithm, creating the Fast-DSCF decoding. Next, we reduce the search span within the special nodes to further reduce the computational complexity. Following, we describe a hardware architecture for the Fast-DSCF decoder, in which we introduce additional simplifications such as metric normalization and sorter length reduction. All the simplifications and approximations are shown to have minimal impact on the error-correction performance, and the reported Fast-DSCF decoder is the only SCF-based architecture that can correct multiple errors. The Fast-DSCF decoders synthesized using TSMC $65$nm CMOS technology can achieve a $1.25$, $1.06$ and $0.93$ Gbps throughput for $omega in {1,2,3}$, respectively. Compared to the state-of-the-art fast CA-SCL decoders with equivalent FER performance, the proposed decoders are up to $5.8times$ more area-efficient. Finally, observations at energy dissipation indicate that the Fast-DSCF is more energy-efficient than its CA-SCL-based counterparts.



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Polar codes are a class of capacity achieving error correcting codes that has been recently selected for the next generation of wireless communication standards (5G). Polar code decoding algorithms have evolved in various directions, striking different balances between error-correction performance, speed and complexity. Successive-cancellation list (SCL) and its incarnations constitute a powerful, well-studied set of algorithms, in constant improvement. At the same time, different implementation approaches provide a wide range of area occupations and latency results. 5G puts a focus on improved error-correction performance, high throughput and low power consumption: a comprehensive study considering all these metrics is currently lacking in literature. In this work, we evaluate SCL-based decoding algorithms in terms of error-correction performance and compare them to low-density parity-check (LDPC) codes. Moreover, we consider various decoder implementations, for both polar and LDPC codes, and compare their area occupation and power and energy consumption when targeting short code lengths and rates. Our work shows that among SCL-based decoders, the partitioned SCL (PSCL) provides the lowest area occupation and power consumption, whereas fast simplified SCL (Fast-SSCL) yields the lowest energy consumption. Compared to LDPC decoder architectures, different SCL implementations occupy up to 17.1x less area, dissipate up to 7.35x less power, and up to 26x less energy.
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Polar codes are a class of channel capacity achieving codes that has been selected for the next generation of wireless communication standards. Successive-cancellation (SC) is the first proposed decoding algorithm, suffering from mediocre error-correction performance at moderate code length. In order to improve the error-correction performance of SC, two approaches are available: (i) SC-List decoding which keeps a list of candidates by running a number of SC decoders in parallel, thus increasing the implementation complexity, and (ii) SC-Flip decoding that relies on a single SC module, and keeps the computational complexity close to SC. In this work, we propose the partitioned SC-Flip (PSCF) decoding algorithm, which outperforms SC-Flip in terms of error-correction performance and average computational complexity, leading to higher throughput and reduced energy consumption per codeword. We also introduce a partitioning scheme that best suits our PSCF decoder. Simulation results show that at equivalent frame error rate, PSCF has up to $5 times$ less computational complexity than the SC-Flip decoder. At equivalent average number of iterations, the error-correction performance of PSCF outperforms SC-Flip by up to $0.15$ dB at frame error rate of $10^{-3}$.
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