Non-uniform quantizers with SC polar based channel-optimized decoders

Hasan, Alaa A.; Marsland, Ian

doi:10.1109/iemcon.2017.8117162

Cited by 3 publications

(4 citation statements)

References 7 publications

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“…Due to the symmetry of the additive white gaussian noise (AWGN) channel, its likelihood ratio is also roughly symmetrical, which is suitable for symmetrized quantization processing. In [10]; the author proved that the function of the number of decoder iterations is related to the exponent of the message amplitude, and the range and accuracy of the quantized message in the decoder will affect the BER leveling. Therefore, we design a new quantization method with (Q + 1)-bit non-uniform quantization.…”

Section: Quantitative Algorithmmentioning

confidence: 99%

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High-Speed Digital Detector for the Internet of Things Assisted by Signal’s Intensity Quantification

Zhang

Wang

2021

Front. Phys.

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This paper proposes a high-speed digital detector for the Internet of Things (IoT) assisted by signal’s intensity quantification. The detector quantifies the amplitude of each pixel of the detected image and converts it into a digital signal, which can be directly applied to the IoT with wireless communication system. Two types of amplitude quantization algorithms, uniform quantization and non-uniform quantization, are applied to the detector, which further improves the quality of the detected image and the robustness of the image signal in a noisy environment. Related simulations have been established to verify the accuracy of the models and algorithms.

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Section: Quantitative Algorithmmentioning

confidence: 99%

“…The proposed algorithm compress the image effectively without harming the quality of the compressed image. [10] shows that the non-uniform quantized polar decoder is capable to perform performance close to floating point performance.…”

Section: Introductionmentioning

confidence: 96%

High-Speed Digital Detector for the Internet of Things Assisted by Signal’s Intensity Quantification

Zhang

Wang

2021

Front. Phys.

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“…Our main contributions in this thesis, which are published or submitted for publication in [20][21][22][23][24][25][26][27][28][29] can be summarized as follows:…”

Section: Related Publicationsmentioning

confidence: 99%

“…• [23][24][25] We have proposed a method to find the linear correction factor of the approximate LLRs for decoding SC polar codes over unknown fading channels and unavailable fading gain. Hoping to maximize the channel capacity, we proved that this approximation is fulfilled the consistency condition and maximized only with true LLRs so that it works as a measure for LLR reliability.…”

Section: Related Publicationsmentioning

confidence: 99%

Efficient Log Likelihood Ratio Estimation for Polar Codes

Hasan¹

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First, I thank God, the Gracious and the Merciful, for His countless blessings.I am truly honored and fortunate to have been advised by Prof. Ian D. Marsland. This thesis would not have been possible without his guidance and support. He has been a constant source of inspiration, knowledge, and creativity. I feel I am one of the few lucky persons whose supervisor is a guide and teacher put together. His doors were always open for discussions which range from coding theory to programming tactics. I would also like to acknowledge his efforts to improve my writing skills which were non-existent before. For all the above and many other reasons I would like to express my deepest gratitude and appreciation to him.

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