🤖 AI Summary
This work addresses the challenge of balancing decoding efficiency and error-correction performance in polar codes for high-throughput, low-latency data channels. The authors propose an enhanced speculative successive cancellation (Spec-SC) decoding architecture that executes left and right decoding branches in parallel and introduces a novel stopping criterion based on Hamming and ellipsoidal distances, significantly accelerating decoding at low-rate nodes. Additionally, codeword membership detection is integrated to optimize performance at high-rate nodes. The proposed method achieves substantially lower decoding latency compared to both fast simplified successive cancellation (FSSC) and the original Spec-SC schemes, while incurring negligible degradation in block error rate.
📝 Abstract
Next-generation data-channel applications of polar codes demand decoding algorithms with high throughput and low latency. The recently proposed speculative successive cancellation (Spec-SC) decoding reduces average decoding latency by speculatively executing the right branch of successive cancellation (SC) decoding in parallel with the left branch, verifying the result once the g-function is computed. In this paper, we propose new acceptance criteria based on Hamming distance and ellipsoidal distance that improve acceptance rates, enabling greater speed-ups for lower-rate nodes. We further show that combining code membership testing with speculative decoding accelerates high-rate nodes as well. Numerical results confirm that both approaches outperform fast simplified SC (FSSC) decoding and Spec-SC with the original acceptance condition in terms latency by a wide margin, with virtually identical error-rate performance.