scholarly journals On Error Performance and Concatenated Coding of Polar Codes in AWGN Channels

2020 ◽  
Vol 768 ◽  
pp. 072075
Author(s):  
Jing Jin ◽  
Rui Deng ◽  
Tiansheng Liu ◽  
Liping Li
Keyword(s):  
Polar Codes ◽  
Error Performance ◽  
Concatenated Coding

scholarly journals An Enhanced Decoding Algorithm for Coded Compressed Sensing with Applications to Unsourced Random Access

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 676
Author(s):  
Vamsi K. Amalladinne ◽  
Jamison R. Ebert ◽  
Jean-Francois Chamberland ◽  
Krishna R. Narayanan
Keyword(s):  
Computational Complexity ◽  
Random Access ◽  
Base Station ◽  
Decoding Algorithm ◽  
Error Performance ◽  
Distributed Sensor Networks ◽  
Concatenated Coding ◽  
Distributed Sensor ◽  
Wide Range ◽  
Transmission Period

Unsourced random access (URA) has emerged as a pragmatic framework for next-generation distributed sensor networks. Within URA, concatenated coding structures are often employed to ensure that the central base station can accurately recover the set of sent codewords during a given transmission period. Many URA algorithms employ independent inner and outer decoders, which can help reduce computational complexity at the expense of a decay in performance. In this article, an enhanced decoding algorithm is presented for a concatenated coding structure consisting of a wide range of inner codes and an outer tree-based code. It is shown that this algorithmic enhancement has the potential to simultaneously improve error performance and decrease the computational complexity of the decoder. This enhanced decoding algorithm is applied to two existing URA algorithms, and the performance benefits of the algorithm are characterized. Findings are supported by numerical simulations.

scholarly journals Reduced Path Successive Cancellation List Decoding for Polar Codes

2021 ◽  
Vol 11 (1) ◽  
pp. 12-23
Author(s):  
Walled Khalid Abdulwahab ◽  
Abdulkareem Abdulrahman Kadhim
Keyword(s):  
Computational Complexity ◽  
Gaussian Noise ◽  
Fading Channel ◽  
Additive White Gaussian Noise ◽  
Optimization Procedure ◽  
Polar Codes ◽  
List Decoding ◽  
Error Performance ◽  
Successive Cancellation ◽  
5G Systems

Polar codes have already been adopted in 5G systems to improve error performance. Successive cancellation list (SCL) decoding is usually used at the decoder and involves lengthy processing. Therefore, different methods have been developed to reduce an SCL decoder’s complexity. In this paper, a reduced path successive cancellation list (RP-SCL) decoder is presented to reduce this complexity, where some decoding paths are pruned. The pruning is achieved by using three different thresholds: two for the path metric and one for the pruning depth in the decoding tree. An optimization procedure is considered to determine the optimum settings for these thresholds. The simulation tests are carried out over models of an additive white Gaussian noise channel and a fading channel by using 5G environments. The results reveal that the proposed RP-SCL decoder provides the complexity reduction in terms of the average number of processed paths at high SNR. Additionally, the computational complexity and the memory requirements decrease.

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

2020 ◽  
Vol E103.B (1) ◽  
pp. 43-51 ◽  
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

Compact specification of polar codes

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. 

Polar Codes

2014 ◽  
Author(s):  
David Wasserman
Keyword(s):  
Polar Codes
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