{"title":"基于哈达玛矩阵和黎曼矩阵的 SLM,用于降低 OTFS 信号的 PAPR","authors":"Aare Gopal, Desireddy Krishna Reddy","doi":"10.1002/itl2.591","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>In this letter, we study the peak-to-average power ratio (PAPR) reduction and bit error rate (BER) performances of the Hadamard and Riemann matrix-based selected mapping (SLM) technique for Orthogonal Time Frequency Space (OTFS) signals. Unlike the conventional phase sequence based on <span></span><math>\n <semantics>\n <mrow>\n <mrow>\n <mo>{</mo>\n <mrow>\n <mo>±</mo>\n <mn>1</mn>\n </mrow>\n <mo>,</mo>\n <mrow>\n <mo>±</mo>\n <mi>j</mi>\n </mrow>\n <mo>}</mo>\n </mrow>\n </mrow>\n <annotation>$$ \\left\\{\\pm 1,\\pm j\\right\\} $$</annotation>\n </semantics></math>, which requires the entire sequence to extract the original signal at the receiver, the Hadamard and Riemann matrix-based SLM techniques require only the row index of the matrix, reducing the additional information necessary to extract the signal. Simulation results are presented to verify the PAPR and BER performance. The results are also compared with the existing normalized <i>μ</i>-law, rooting <i>μ</i>-law, and conventional SLM methods. The results demonstrate that the Riemann-based SLM technique shows significant performance improvement.</p>\n </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"7 6","pages":""},"PeriodicalIF":0.9000,"publicationDate":"2024-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hadamard and Riemann Matrix-Based SLM for PAPR Reduction in OTFS Signal\",\"authors\":\"Aare Gopal, Desireddy Krishna Reddy\",\"doi\":\"10.1002/itl2.591\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>In this letter, we study the peak-to-average power ratio (PAPR) reduction and bit error rate (BER) performances of the Hadamard and Riemann matrix-based selected mapping (SLM) technique for Orthogonal Time Frequency Space (OTFS) signals. Unlike the conventional phase sequence based on <span></span><math>\\n <semantics>\\n <mrow>\\n <mrow>\\n <mo>{</mo>\\n <mrow>\\n <mo>±</mo>\\n <mn>1</mn>\\n </mrow>\\n <mo>,</mo>\\n <mrow>\\n <mo>±</mo>\\n <mi>j</mi>\\n </mrow>\\n <mo>}</mo>\\n </mrow>\\n </mrow>\\n <annotation>$$ \\\\left\\\\{\\\\pm 1,\\\\pm j\\\\right\\\\} $$</annotation>\\n </semantics></math>, which requires the entire sequence to extract the original signal at the receiver, the Hadamard and Riemann matrix-based SLM techniques require only the row index of the matrix, reducing the additional information necessary to extract the signal. Simulation results are presented to verify the PAPR and BER performance. The results are also compared with the existing normalized <i>μ</i>-law, rooting <i>μ</i>-law, and conventional SLM methods. The results demonstrate that the Riemann-based SLM technique shows significant performance improvement.</p>\\n </div>\",\"PeriodicalId\":100725,\"journal\":{\"name\":\"Internet Technology Letters\",\"volume\":\"7 6\",\"pages\":\"\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2024-10-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Internet Technology Letters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/itl2.591\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"TELECOMMUNICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Internet Technology Letters","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/itl2.591","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
Hadamard and Riemann Matrix-Based SLM for PAPR Reduction in OTFS Signal
In this letter, we study the peak-to-average power ratio (PAPR) reduction and bit error rate (BER) performances of the Hadamard and Riemann matrix-based selected mapping (SLM) technique for Orthogonal Time Frequency Space (OTFS) signals. Unlike the conventional phase sequence based on , which requires the entire sequence to extract the original signal at the receiver, the Hadamard and Riemann matrix-based SLM techniques require only the row index of the matrix, reducing the additional information necessary to extract the signal. Simulation results are presented to verify the PAPR and BER performance. The results are also compared with the existing normalized μ-law, rooting μ-law, and conventional SLM methods. The results demonstrate that the Riemann-based SLM technique shows significant performance improvement.