Volume 13 Issue 1
Feb.  2024
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Article Navigation >  Journal of Radars  > 2024  >  13(1): 160-173
Ren Bo, Shi Longfei, Wang Guoyu. Polarimetric Analysis of the Interference from Base Stations to UHF-band Radar[J]. Journal of Radars, 2016, 5(2): 164-173. doi: 10.12000/JR15134
Citation: LIU Yan, WAN Xianrong, and YI Jianxin. OFDM waveform design for joint radar-communication based on data distortion[J]. Journal of Radars, 2024, 13(1): 160–173. doi: 10.12000/JR23205
shu

OFDM Waveform Design for Joint Radar-communication Based on Data Distortion

DOI: 10.12000/JR23205

  • School of Electronic Information, Wuhan University, Wuhan 430072, China

Funds:  The National Natural Science Foundation of China (61931015, 62071335, 62250024), The Innovation Group Project of Natural Science Foundation of Hubei Province (2021CFA002), The Fundamental Research Funds for the Central Universities of China (2042022dx0001)
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  • Corresponding author: WAN Xianrong, xrwan@whu.edu.cn
  • Received Date: 2023-10-20
  • Rev Recd Date: 2023-12-28
    • Available Online: 2023-12-29
  • Publish Date: 2024-01-09
    Abstract
  • Orthogonal Frequency Division Multiplexing (OFDM) waveform design is one of the key physical layer technologies for achieving joint radar-communication. OFDM waveforms usually have issues with high Peak to Average Power Ratio (PAPR) and high waveform autocorrelation sidelobe levels. This paper proposes an integrated waveform design method based on data distortion to address the communication rate degradation problem of existing joint PAPR and autocorrelation sidelobe reduction methods. The paper also takes the Error Vector Magnitude (EVM) of communication data as one of the optimization objectives, reducing the communication bit error rate caused by data distortion. Firstly, an optimization model was constructed to minimize the Integrated Sidelobe Level Ratio (ISLR) and EVM under PAPR constraints. Secondly, based on the characteristics of the modulation constellation, the multi-objective high-dimensional non-convex optimization problem is transformed into two single objective optimization subproblems by using the data distortion of outer constellation modulation and all modulation data distortion. Convex relaxation operation and Alternating Direction Method of Multipliers (ADMM) are respectively used to solve the simplified subproblems, resulting in low ISLR waveform and low EVM waveform under PAPR constraint. The simulation results show that the integrated waveform designed by the proposed method can meet the requirements of PAPR, and has good sensing and communication performance.

     

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    Created with Highcharts 5.0.7Chart context menuAccess Area Distribution其他: 6.6 %其他: 6.6 %其他: 1.4 %其他: 1.4 %Boiling Springs: 0.1 %Boiling Springs: 0.1 %Botswana: 0.1 %Botswana: 0.1 %Burlington: 0.1 %Burlington: 0.1 %Canada: 0.1 %Canada: 0.1 %Canton: 0.1 %Canton: 0.1 %China: 0.8 %China: 0.8 %Egypt: 0.1 %Egypt: 0.1 %France: 0.4 %France: 0.4 %Greece: 0.1 %Greece: 0.1 %Herndon: 0.0 %Herndon: 0.0 %Hong Kong, China: 0.1 %Hong Kong, China: 0.1 %Howard: 0.1 %Howard: 0.1 %India: 0.0 %India: 0.0 %Iran (ISLAMIC Republic Of): 0.2 %Iran (ISLAMIC Republic Of): 0.2 %Italy: 0.2 %Italy: 0.2 %Korea Republic of: 0.4 %Korea Republic of: 0.4 %Malvern: 0.0 %Malvern: 0.0 %Matale: 0.2 %Matale: 0.2 %Palo Alto: 0.1 %Palo Alto: 0.1 %Pathum Thani: 0.5 %Pathum Thani: 0.5 %Portugal: 0.1 %Portugal: 0.1 %San Mateo: 0.1 %San Mateo: 0.1 %Singapore: 0.1 %Singapore: 0.1 %Taichung: 0.0 %Taichung: 0.0 %Taiwan, China: 0.0 %Taiwan, China: 0.0 %Thailand: 0.1 %Thailand: 0.1 %Turkey: 0.1 %Turkey: 0.1 %United States: 0.4 %United States: 0.4 %Viet Nam: 0.1 %Viet Nam: 0.1 %[]: 2.5 %[]: 2.5 %万隆: 0.3 %万隆: 0.3 %三亚: 0.2 %三亚: 0.2 %上海: 2.2 %上海: 2.2 %东京: 0.4 %东京: 0.4 %东京都: 0.0 %东京都: 0.0 %东莞: 0.2 %东莞: 0.2 %中卫: 0.1 %中卫: 0.1 %临汾: 0.4 %临汾: 0.4 %丹东: 0.0 %丹东: 0.0 %乌鲁木齐: 0.1 %乌鲁木齐: 0.1 %伊斯坦布尔: 0.1 %伊斯坦布尔: 0.1 %伦敦: 0.1 %伦敦: 0.1 %佛山: 0.1 %佛山: 0.1 %保定: 0.1 %保定: 0.1 %兰州: 0.1 %兰州: 0.1 %兰辛: 0.1 %兰辛: 0.1 %凤凰城: 0.1 %凤凰城: 0.1 %加利福尼亚州: 0.1 %加利福尼亚州: 0.1 %北京: 8.7 %北京: 8.7 %匹兹堡: 0.1 %匹兹堡: 0.1 %十堰: 0.1 %十堰: 0.1 %南京: 2.6 %南京: 2.6 %南昌: 0.1 %南昌: 0.1 %南通: 0.0 %南通: 0.0 %卡拉奇: 0.0 %卡拉奇: 0.0 %厦门: 0.1 %厦门: 0.1 %台北: 0.3 %台北: 0.3 %台州: 0.0 %台州: 0.0 %台湾: 0.0 %台湾: 0.0 %合肥: 0.9 %合肥: 0.9 %吉隆坡: 0.1 %吉隆坡: 0.1 %呼和浩特: 0.0 %呼和浩特: 0.0 %哈尔滨: 0.3 %哈尔滨: 0.3 %哥伦布: 0.0 %哥伦布: 0.0 %喀什: 0.0 %喀什: 0.0 %圣彼得堡: 0.1 %圣彼得堡: 0.1 %大庆: 0.1 %大庆: 0.1 %大连: 0.1 %大连: 0.1 %天津: 0.0 %天津: 0.0 %太原: 0.6 %太原: 0.6 %奥胡斯: 0.3 %奥胡斯: 0.3 %奥马哈: 0.1 %奥马哈: 0.1 %孟买: 0.1 %孟买: 0.1 %宁波: 0.1 %宁波: 0.1 %安庆: 0.1 %安庆: 0.1 %安康: 0.1 %安康: 0.1 %宣城: 0.3 %宣城: 0.3 %巴中: 0.1 %巴中: 0.1 %巴黎: 0.1 %巴黎: 0.1 %布洛涅-比扬古: 0.1 %布洛涅-比扬古: 0.1 %常德: 0.0 %常德: 0.0 %广州: 0.8 %广州: 0.8 %库比蒂诺: 0.2 %库比蒂诺: 0.2 %开封: 0.1 %开封: 0.1 %张家口: 0.3 %张家口: 0.3 %张家界: 0.1 %张家界: 0.1 %德罕: 0.1 %德罕: 0.1 %意法半: 0.0 %意法半: 0.0 %成都: 0.8 %成都: 0.8 %扬州: 0.1 %扬州: 0.1 %拉贾斯坦: 0.1 %拉贾斯坦: 0.1 %新乡: 0.1 %新乡: 0.1 %新余: 0.1 %新余: 0.1 %新加坡: 0.2 %新加坡: 0.2 %无锡: 0.1 %无锡: 0.1 %昆明: 0.4 %昆明: 0.4 %昌吉回族自治州: 0.0 %昌吉回族自治州: 0.0 %晋城: 0.4 %晋城: 0.4 %朝阳: 0.0 %朝阳: 0.0 %本那比: 0.1 %本那比: 0.1 %杭州: 1.0 %杭州: 1.0 %查尔斯顿: 0.1 %查尔斯顿: 0.1 %株洲: 0.0 %株洲: 0.0 %格兰特县: 0.1 %格兰特县: 0.1 %桂林: 0.2 %桂林: 0.2 %武汉: 2.0 %武汉: 2.0 %毕节: 0.0 %毕节: 0.0 %汉中: 0.1 %汉中: 0.1 %汕头: 0.0 %汕头: 0.0 %江门: 0.0 %江门: 0.0 %沈阳: 0.2 %沈阳: 0.2 %沙田: 0.1 %沙田: 0.1 %法兰克福: 0.4 %法兰克福: 0.4 %泰米尔纳德: 0.1 %泰米尔纳德: 0.1 %洛阳: 0.1 %洛阳: 0.1 %济南: 0.1 %济南: 0.1 %海口: 0.2 %海口: 0.2 %淮南: 0.0 %淮南: 0.0 %深圳: 1.0 %深圳: 1.0 %温州: 0.0 %温州: 0.0 %渭南: 0.7 %渭南: 0.7 %湖州: 0.1 %湖州: 0.1 %湘潭: 0.1 %湘潭: 0.1 %湛江: 0.1 %湛江: 0.1 %漯河: 0.3 %漯河: 0.3 %烟台: 0.0 %烟台: 0.0 %瓦拉纳西县: 0.1 %瓦拉纳西县: 0.1 %石家庄: 0.1 %石家庄: 0.1 %福州: 0.1 %福州: 0.1 %秦皇岛: 0.1 %秦皇岛: 0.1 %纽约: 0.4 %纽约: 0.4 %美国伊利诺斯芝加哥: 0.1 %美国伊利诺斯芝加哥: 0.1 %肇庆: 0.1 %肇庆: 0.1 %芒廷维尤: 28.4 %芒廷维尤: 28.4 %芝加哥: 0.6 %芝加哥: 0.6 %苏州: 0.8 %苏州: 0.8 %蚌埠: 0.1 %蚌埠: 0.1 %衡水: 0.1 %衡水: 0.1 %衢州: 0.1 %衢州: 0.1 %西宁: 16.6 %西宁: 16.6 %西安: 2.4 %西安: 2.4 %贵阳: 0.1 %贵阳: 0.1 %赣州: 0.0 %赣州: 0.0 %运城: 0.8 %运城: 0.8 %连云港: 0.1 %连云港: 0.1 %邢台: 0.1 %邢台: 0.1 %邯郸: 0.1 %邯郸: 0.1 %郑州: 0.1 %郑州: 0.1 %都伯林: 0.2 %都伯林: 0.2 %重庆: 0.3 %重庆: 0.3 %长春: 0.0 %长春: 0.0 %长沙: 0.6 %长沙: 0.6 %长治: 0.3 %长治: 0.3 %青岛: 0.1 %青岛: 0.1 %香港: 0.4 %香港: 0.4 %香港特别行政区: 0.5 %香港特别行政区: 0.5 %马哈拉施特拉: 0.0 %马哈拉施特拉: 0.0 %马鞍山: 0.0 %马鞍山: 0.0 %鹰潭: 0.0 %鹰潭: 0.0 %其他其他Boiling SpringsBotswanaBurlingtonCanadaCantonChinaEgyptFranceGreeceHerndonHong Kong, ChinaHowardIndiaIran (ISLAMIC Republic Of)ItalyKorea Republic ofMalvernMatalePalo AltoPathum ThaniPortugalSan MateoSingaporeTaichungTaiwan, ChinaThailandTurkeyUnited StatesViet Nam[]万隆三亚上海东京东京都东莞中卫临汾丹东乌鲁木齐伊斯坦布尔伦敦佛山保定兰州兰辛凤凰城加利福尼亚州北京匹兹堡十堰南京南昌南通卡拉奇厦门台北台州台湾合肥吉隆坡呼和浩特哈尔滨哥伦布喀什圣彼得堡大庆大连天津太原奥胡斯奥马哈孟买宁波安庆安康宣城巴中巴黎布洛涅-比扬古常德广州库比蒂诺开封张家口张家界德罕意法半成都扬州拉贾斯坦新乡新余新加坡无锡昆明昌吉回族自治州晋城朝阳本那比杭州查尔斯顿株洲格兰特县桂林武汉毕节汉中汕头江门沈阳沙田法兰克福泰米尔纳德洛阳济南海口淮南深圳温州渭南湖州湘潭湛江漯河烟台瓦拉纳西县石家庄福州秦皇岛纽约美国伊利诺斯芝加哥肇庆芒廷维尤芝加哥苏州蚌埠衡水衢州西宁西安贵阳赣州运城连云港邢台邯郸郑州都伯林重庆长春长沙长治青岛香港香港特别行政区马哈拉施特拉马鞍山鹰潭

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      沈阳化工大学材料科学与工程学院 沈阳 110142

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