Secure Noise-and-Forward Relaying with Polar Codes

Lecture Notes in Electrical Engineering - Communications, Signal Processing, and Systems ◽

10.1007/978-981-13-6264-4_26 ◽

2019 ◽

pp. 216-223

Author(s):

Bin Duo ◽

Peng Zhang ◽

Yanmei Hu ◽

Yong Fang ◽

Yong Jia ◽

...

Keyword(s):

Polar Codes

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An Adaptive Fusion Successive Cancellation List Decoder for Polar Codes with Cyclic Redundancy Check

IEICE Transactions on Communications ◽

10.1587/transcom.2019ebp3031 ◽

2020 ◽

Vol E103.B (1) ◽

pp. 43-51 ◽

Cited By ~ 1

Author(s):

Yuhuan WANG ◽

Hang YIN ◽

Zhanxin YANG ◽

Yansong LV ◽

Lu SI ◽

...

Keyword(s):

Polar Codes ◽

Cyclic Redundancy Check ◽

Successive Cancellation ◽

Adaptive Fusion ◽

List Decoder

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Compact specification of polar codes

Information and Control Systems ◽

10.31799/1684-8853-2019-1-40-47 ◽

2019 ◽

pp. 40-47

Author(s):

R. A. Morozov ◽

P. V. Trifonov

Keyword(s):

Storage Capacity ◽

Low Complexity ◽

Practical Implementation ◽

Polar Codes ◽

Practical Relevance ◽

Memory Consumption ◽

Full Size ◽

The Family ◽

Erasure Probability ◽

Binary Erasure Channel

Introduction:Practical implementation of a communication system which employs a family of polar codes requires either to store a number of large specifications or to construct the codes by request. The first approach assumes extensive memory consumption, which is inappropriate for many applications, such as those for mobile devices. The second approach can be numerically unstable and hard to implement in low-end hardware. One of the solutions is specifying a family of codes by a sequence of subchannels sorted by reliability. However, this solution makes it impossible to separately optimize each code from the family.Purpose:Developing a method for compact specifications of polar codes and subcodes.Results:A method is proposed for compact specification of polar codes. It can be considered a trade-off between real-time construction and storing full-size specifications in memory. We propose to store compact specifications of polar codes which contain frozen set differences between the original pre-optimized polar codes and the polar codes constructed for a binary erasure channel with some erasure probability. Full-size specification needed for decoding can be restored from a compact one by a low-complexity hardware-friendly procedure. The proposed method can work with either polar codes or polar subcodes, allowing you to reduce the memory consumption by 15–50 times.Practical relevance:The method allows you to use families of individually optimized polar codes in devices with limited storage capacity.

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