Partitioned list decoding of polar codes: Analysis and improvement of finite length performance

S.A. Hashemi, M. Mondelli, H. Hassani, R. Urbanke, W. Gross, in:, 2017 IEEE Global Communications Conference, IEEE, 2017, pp. 1–7.


Conference Paper | Published | English
Author
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Abstract
Polar codes represent one of the major recent breakthroughs in coding theory and, because of their attractive features, they have been selected for the incoming 5G standard. As such, a lot of attention has been devoted to the development of decoding algorithms with good error performance and efficient hardware implementation. One of the leading candidates in this regard is represented by successive-cancellation list (SCL) decoding. However, its hardware implementation requires a large amount of memory. Recently, a partitioned SCL (PSCL) decoder has been proposed to significantly reduce the memory consumption [1]. In this paper, we examine the paradigm of PSCL decoding from both theoretical and practical standpoints: (i) by changing the construction of the code, we are able to improve the performance at no additional computational, latency or memory cost, (ii) we present an optimal scheme to allocate cyclic redundancy checks (CRCs), and (iii) we provide an upper bound on the list size that allows MAP performance.
Publishing Year
Date Published
2017-12-01
Proceedings Title
2017 IEEE Global Communications Conference
Page
1-7
Conference
GLOBECOM: Global Communications Conference
Conference Location
Singapore, Singapore
Conference Date
2017-12-04 – 2017-12-08
IST-REx-ID

Cite this

Hashemi SA, Mondelli M, Hassani H, Urbanke R, Gross W. Partitioned list decoding of polar codes: Analysis and improvement of finite length performance. In: 2017 IEEE Global Communications Conference. IEEE; 2017:1-7. doi:10.1109/glocom.2017.8254940
Hashemi, S. A., Mondelli, M., Hassani, H., Urbanke, R., & Gross, W. (2017). Partitioned list decoding of polar codes: Analysis and improvement of finite length performance. In 2017 IEEE Global Communications Conference (pp. 1–7). Singapore, Singapore: IEEE. https://doi.org/10.1109/glocom.2017.8254940
Hashemi, Seyyed Ali, Marco Mondelli, Hamed Hassani, Ruediger Urbanke, and Warren Gross. “Partitioned List Decoding of Polar Codes: Analysis and Improvement of Finite Length Performance.” In 2017 IEEE Global Communications Conference, 1–7. IEEE, 2017. https://doi.org/10.1109/glocom.2017.8254940.
S. A. Hashemi, M. Mondelli, H. Hassani, R. Urbanke, and W. Gross, “Partitioned list decoding of polar codes: Analysis and improvement of finite length performance,” in 2017 IEEE Global Communications Conference, Singapore, Singapore, 2017, pp. 1–7.
Hashemi SA, Mondelli M, Hassani H, Urbanke R, Gross W. 2017. Partitioned list decoding of polar codes: Analysis and improvement of finite length performance. 2017 IEEE Global Communications Conference. GLOBECOM: Global Communications Conference 1–7.
Hashemi, Seyyed Ali, et al. “Partitioned List Decoding of Polar Codes: Analysis and Improvement of Finite Length Performance.” 2017 IEEE Global Communications Conference, IEEE, 2017, pp. 1–7, doi:10.1109/glocom.2017.8254940.

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