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<p>The Successive Cancellation (SC) decoder for polar codes has the advantage of low computational complexity, its correction capability is limited by error propagation. Advanced decoders, such as the Cyclic Redundancy Check (CRC)-Assisted Successive Cancellation List (CA-SCL), overcome this limitation, but at the cost of high complexity, which limits their adoption in systems requiring fast processing times and high energy efficiency. To address this challenge, we develop an innovative approach to decoding polar codes, which combines SC and CA-SCL decoders. By analyzing the distribution of the first error positions, the decoding process is subdivided into three subframes: the first and the last subframes are decoded using low-complexity SC decoder, while the central subframe, which is more prone to errors, is processed by the CA-SCL decoder. The experimental results indicate a gain of about 0.2 dB in Signal-to-Noise Ratio (SNR) at a Bit Error Rate (BER) of <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(10^{-5}\)</EquationSource> <EquationSource Format="MATHML"><math> <msup> <mn>10</mn> <mrow> <mo>-</mo> <mn>5</mn> </mrow> </msup> </math></EquationSource> </InlineEquation>, along with a reduction in computational complexity of nearly 48%. Furthermore, by introducing an optimized adaptive metric that adjusts dynamically to the channel conditions, the decoding complexity is further decreased by approximately 59%. This leads to a better trade-off between decoding performance-complexity when compared with the CA-SCL decoder.</p>

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Low-complexity CA-SCL decoding for polar codes :A generalized selective computation approach

  • 期刊论文

  • 发表日期：

    2026年1月13日

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  • Mohamed Lamrini,
  • Zakarea Rahou,
  • Ismail Akharraz,
  • Abdelaziz Ahaitouf

摘要

The Successive Cancellation (SC) decoder for polar codes has the advantage of low computational complexity, its correction capability is limited by error propagation. Advanced decoders, such as the Cyclic Redundancy Check (CRC)-Assisted Successive Cancellation List (CA-SCL), overcome this limitation, but at the cost of high complexity, which limits their adoption in systems requiring fast processing times and high energy efficiency. To address this challenge, we develop an innovative approach to decoding polar codes, which combines SC and CA-SCL decoders. By analyzing the distribution of the first error positions, the decoding process is subdivided into three subframes: the first and the last subframes are decoded using low-complexity SC decoder, while the central subframe, which is more prone to errors, is processed by the CA-SCL decoder. The experimental results indicate a gain of about 0.2 dB in Signal-to-Noise Ratio (SNR) at a Bit Error Rate (BER) of \(10^{-5}\) 10 - 5 , along with a reduction in computational complexity of nearly 48%. Furthermore, by introducing an optimized adaptive metric that adjusts dynamically to the channel conditions, the decoding complexity is further decreased by approximately 59%. This leads to a better trade-off between decoding performance-complexity when compared with the CA-SCL decoder.