All-Integer Quantization for Low-Complexity Min-Sum Successive Cancellation Polar Decoder

It is widely acknowledged in communication theory that polar codes have been proven to achieve channel capacity across a range of communication channels. However, their exceptional performance is usually evaluated through simulations or analyses conducted under the assumption of infinite precision,...

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Main Authors: Wittawad Pimsri, Patinya Muangkammuen, Puripong Suthisopapan, Virasit Imtawil
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Applied Sciences
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Online Access:https://www.mdpi.com/2076-3417/15/6/3241
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author Wittawad Pimsri
Patinya Muangkammuen
Puripong Suthisopapan
Virasit Imtawil
author_facet Wittawad Pimsri
Patinya Muangkammuen
Puripong Suthisopapan
Virasit Imtawil
author_sort Wittawad Pimsri
collection DOAJ
description It is widely acknowledged in communication theory that polar codes have been proven to achieve channel capacity across a range of communication channels. However, their exceptional performance is usually evaluated through simulations or analyses conducted under the assumption of infinite precision, i.e., floating-point arithmetic, which represents an ideal numerical computation. To address this implementation challenge, this work proposes a min-sum successive cancellation (MS-SC) polar decoder employing all-integer quantization to improve practicality in real-world scenarios. To balance the trade-off between practicality and decoding performance, we investigate whether 5-bit all-integer quantization is the optimal choice for the MS-SC polar decoder. Moreover, the simulation results over fading channels show that the proposed decoder achieves a performance almost equivalent to the high-precision successive cancellation (SC) decoder. The integer-based calculation for the MS-SC polar decoder reduces computational complexity by <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>75</mn><mo>%</mo></mrow></semantics></math></inline-formula> compared to the conventional SC decoding algorithm with infinite-precision computation.
format Article
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spelling doaj-art-4886d9ed473d4df4bb08aeb013b6b70a2025-08-20T02:42:45ZengMDPI AGApplied Sciences2076-34172025-03-01156324110.3390/app15063241All-Integer Quantization for Low-Complexity Min-Sum Successive Cancellation Polar DecoderWittawad Pimsri0Patinya Muangkammuen1Puripong Suthisopapan2Virasit Imtawil3Department of Electrical Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, ThailandDepartment of Electrical Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, ThailandDepartment of Electrical Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, ThailandDepartment of Electrical Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, ThailandIt is widely acknowledged in communication theory that polar codes have been proven to achieve channel capacity across a range of communication channels. However, their exceptional performance is usually evaluated through simulations or analyses conducted under the assumption of infinite precision, i.e., floating-point arithmetic, which represents an ideal numerical computation. To address this implementation challenge, this work proposes a min-sum successive cancellation (MS-SC) polar decoder employing all-integer quantization to improve practicality in real-world scenarios. To balance the trade-off between practicality and decoding performance, we investigate whether 5-bit all-integer quantization is the optimal choice for the MS-SC polar decoder. Moreover, the simulation results over fading channels show that the proposed decoder achieves a performance almost equivalent to the high-precision successive cancellation (SC) decoder. The integer-based calculation for the MS-SC polar decoder reduces computational complexity by <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>75</mn><mo>%</mo></mrow></semantics></math></inline-formula> compared to the conventional SC decoding algorithm with infinite-precision computation.https://www.mdpi.com/2076-3417/15/6/3241polar codesSC decodingmin-sum approximationinteger quantization
spellingShingle Wittawad Pimsri
Patinya Muangkammuen
Puripong Suthisopapan
Virasit Imtawil
All-Integer Quantization for Low-Complexity Min-Sum Successive Cancellation Polar Decoder
Applied Sciences
polar codes
SC decoding
min-sum approximation
integer quantization
title All-Integer Quantization for Low-Complexity Min-Sum Successive Cancellation Polar Decoder
title_full All-Integer Quantization for Low-Complexity Min-Sum Successive Cancellation Polar Decoder
title_fullStr All-Integer Quantization for Low-Complexity Min-Sum Successive Cancellation Polar Decoder
title_full_unstemmed All-Integer Quantization for Low-Complexity Min-Sum Successive Cancellation Polar Decoder
title_short All-Integer Quantization for Low-Complexity Min-Sum Successive Cancellation Polar Decoder
title_sort all integer quantization for low complexity min sum successive cancellation polar decoder
topic polar codes
SC decoding
min-sum approximation
integer quantization
url https://www.mdpi.com/2076-3417/15/6/3241
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AT puripongsuthisopapan allintegerquantizationforlowcomplexityminsumsuccessivecancellationpolardecoder
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