On the Capacity-Achieving Input of the Gaussian Channel with Polar Quantization
The polar receiver architecture is a receiver design that captures the envelope and phase information of the signal rather than its in-phase and quadrature components. Several studies have demonstrated the robustness of polar receivers to phase noise and other nonlinearities. Yet, the information-th...
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description | The polar receiver architecture is a receiver design that captures the envelope and phase information of the signal rather than its in-phase and quadrature components. Several studies have demonstrated the robustness of polar receivers to phase noise and other nonlinearities. Yet, the information-theoretic limits of polar receivers with finite-precision quantizers have not been investigated in the literature. The main contribution of this work is to identify the optimal signaling strategy for the additive white Gaussian noise (AWGN) channel with polar quantization at the output. More precisely, we show that the capacity-achieving modulation scheme has an amplitude phase shift keying (APSK) structure. Using this result, the capacity of the AWGN channel with polar quantization at the output is established by numerically optimizing the probability mass function of the amplitude. The capacity of the polar-quantized AWGN channel with \(b_1\)-bit phase quantizer and optimized single-bit magnitude quantizer is also presented. Our numerical findings suggest the existence of signal-to-noise ratio (SNR) thresholds, above which the number of amplitude levels of the optimal APSK scheme and their respective probabilities change abruptly. Moreover, the manner in which the capacity-achieving input evolves with increasing SNR depends on the number of phase quantization bits. |
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Several studies have demonstrated the robustness of polar receivers to phase noise and other nonlinearities. Yet, the information-theoretic limits of polar receivers with finite-precision quantizers have not been investigated in the literature. The main contribution of this work is to identify the optimal signaling strategy for the additive white Gaussian noise (AWGN) channel with polar quantization at the output. More precisely, we show that the capacity-achieving modulation scheme has an amplitude phase shift keying (APSK) structure. Using this result, the capacity of the AWGN channel with polar quantization at the output is established by numerically optimizing the probability mass function of the amplitude. The capacity of the polar-quantized AWGN channel with \(b_1\)-bit phase quantizer and optimized single-bit magnitude quantizer is also presented. Our numerical findings suggest the existence of signal-to-noise ratio (SNR) thresholds, above which the number of amplitude levels of the optimal APSK scheme and their respective probabilities change abruptly. Moreover, the manner in which the capacity-achieving input evolves with increasing SNR depends on the number of phase quantization bits.</description><identifier>EISSN: 2331-8422</identifier><identifier>DOI: 10.48550/arxiv.2205.05850</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Amplitudes ; Codes ; Computer Science - Information Theory ; Counters ; Information theory ; Mathematics - Information Theory ; Measurement ; Noise ; Optimization ; Phase shift keying ; Quadratures ; Random noise ; Receivers ; Robustness (mathematics) ; Signal to noise ratio</subject><ispartof>arXiv.org, 2022-07</ispartof><rights>2022. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). 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Our numerical findings suggest the existence of signal-to-noise ratio (SNR) thresholds, above which the number of amplitude levels of the optimal APSK scheme and their respective probabilities change abruptly. Moreover, the manner in which the capacity-achieving input evolves with increasing SNR depends on the number of phase quantization bits.</description><subject>Amplitudes</subject><subject>Codes</subject><subject>Computer Science - Information Theory</subject><subject>Counters</subject><subject>Information theory</subject><subject>Mathematics - Information Theory</subject><subject>Measurement</subject><subject>Noise</subject><subject>Optimization</subject><subject>Phase shift keying</subject><subject>Quadratures</subject><subject>Random noise</subject><subject>Receivers</subject><subject>Robustness (mathematics)</subject><subject>Signal to noise ratio</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GOX</sourceid><recordid>eNotj01Lw0AYhBdBsNT-AE8ueE7cj-xHjiVoLRSi0Ht4s8maLXETk021_npj62kOM8zMg9AdJXGihSCPMHy7Y8wYETERWpArtGCc00gnjN2g1TgeCCFMKiYEX6A89zg0Nc6gB-PCKVqbxtVH59_x1vdTwJ09-xuYxtGBx1kD3tct_nKhwa9dCwN-m8AH9wPBdf4WXVtox3r1r0u0f37aZy_RLt9ss_UuAsF0ZAy3piRc0spWWhlZU6pApYIzbkVpQSsqqTa6IlRLndBUGE7LlCSsKqFM-BLdX2rPtEU_uA8YTsUfdXGmnhMPl0Q_dJ9TPYbi0E2Dnz8VTEqu50Gl-S9uZFmH</recordid><startdate>20220706</startdate><enddate>20220706</enddate><creator>Neil Irwin Bernardo</creator><creator>Zhu, Jingge</creator><creator>Evans, Jamie</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>AKY</scope><scope>AKZ</scope><scope>GOX</scope></search><sort><creationdate>20220706</creationdate><title>On the Capacity-Achieving Input of the Gaussian Channel with Polar Quantization</title><author>Neil Irwin Bernardo ; Zhu, Jingge ; Evans, Jamie</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a528-cc3fcb0361dfd87c6e117a795323f5bfa871618c8d018684195c31b9042dbab43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Amplitudes</topic><topic>Codes</topic><topic>Computer Science - Information Theory</topic><topic>Counters</topic><topic>Information theory</topic><topic>Mathematics - Information Theory</topic><topic>Measurement</topic><topic>Noise</topic><topic>Optimization</topic><topic>Phase shift keying</topic><topic>Quadratures</topic><topic>Random noise</topic><topic>Receivers</topic><topic>Robustness (mathematics)</topic><topic>Signal to noise ratio</topic><toplevel>online_resources</toplevel><creatorcontrib>Neil Irwin Bernardo</creatorcontrib><creatorcontrib>Zhu, Jingge</creatorcontrib><creatorcontrib>Evans, Jamie</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>arXiv Computer Science</collection><collection>arXiv Mathematics</collection><collection>arXiv.org</collection><jtitle>arXiv.org</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Neil Irwin Bernardo</au><au>Zhu, Jingge</au><au>Evans, Jamie</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>On the Capacity-Achieving Input of the Gaussian Channel with Polar Quantization</atitle><jtitle>arXiv.org</jtitle><date>2022-07-06</date><risdate>2022</risdate><eissn>2331-8422</eissn><abstract>The polar receiver architecture is a receiver design that captures the envelope and phase information of the signal rather than its in-phase and quadrature components. Several studies have demonstrated the robustness of polar receivers to phase noise and other nonlinearities. Yet, the information-theoretic limits of polar receivers with finite-precision quantizers have not been investigated in the literature. The main contribution of this work is to identify the optimal signaling strategy for the additive white Gaussian noise (AWGN) channel with polar quantization at the output. More precisely, we show that the capacity-achieving modulation scheme has an amplitude phase shift keying (APSK) structure. Using this result, the capacity of the AWGN channel with polar quantization at the output is established by numerically optimizing the probability mass function of the amplitude. The capacity of the polar-quantized AWGN channel with \(b_1\)-bit phase quantizer and optimized single-bit magnitude quantizer is also presented. Our numerical findings suggest the existence of signal-to-noise ratio (SNR) thresholds, above which the number of amplitude levels of the optimal APSK scheme and their respective probabilities change abruptly. Moreover, the manner in which the capacity-achieving input evolves with increasing SNR depends on the number of phase quantization bits.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><doi>10.48550/arxiv.2205.05850</doi><oa>free_for_read</oa></addata></record> |
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subjects | Amplitudes Codes Computer Science - Information Theory Counters Information theory Mathematics - Information Theory Measurement Noise Optimization Phase shift keying Quadratures Random noise Receivers Robustness (mathematics) Signal to noise ratio |
title | On the Capacity-Achieving Input of the Gaussian Channel with Polar Quantization |
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