电子学报
電子學報
전자학보
Acta Electronica Sinica
2015年
10期
1924-1929
,共6页
罗仁泽%党煜蒲%李芮%杨娇%何国林
囉仁澤%黨煜蒲%李芮%楊嬌%何國林
라인택%당욱포%리예%양교%하국림
OFDM随钻无线传输系统%峰均比 (PAPR)%选择性映射 (SLM)%快速傅立叶逆变换 (IFFT)
OFDM隨鑽無線傳輸繫統%峰均比 (PAPR)%選擇性映射 (SLM)%快速傅立葉逆變換 (IFFT)
OFDM수찬무선전수계통%봉균비 (PAPR)%선택성영사 (SLM)%쾌속부립협역변환 (IFFT)
OFDM while-drilling wireless transmission systems%peak-to-average power ratio (PAPR)%selected mapping (SLM)%inverse fast Fourier transform (IFFT)
目前随钻测井信号无法实现高速传输,现有的井下泥浆脉冲传输技术传输速率较慢.本文提出了一种正交频分复用(OFDM)随钻无线传输系统可以实现高效的井下数据传输.但该系统存在其发射信号中固有的高峰均功率比(PAPR)问题.本文基于 OFDM随钻无线传输系统,提出了一种分级的基-4 IFFT 改进 SLM算法降低其 PAPR.该算法将 N =4n 点的基-4 IFFT 运算分为前 k 级和后 n-k 级的蝶形运算,信号在两级 IFFT 之间乘以相位序列.理论分析表明:该法较传统 SLM算法 IFFT 复杂度可降低近60%.
目前隨鑽測井信號無法實現高速傳輸,現有的井下泥漿脈遲傳輸技術傳輸速率較慢.本文提齣瞭一種正交頻分複用(OFDM)隨鑽無線傳輸繫統可以實現高效的井下數據傳輸.但該繫統存在其髮射信號中固有的高峰均功率比(PAPR)問題.本文基于 OFDM隨鑽無線傳輸繫統,提齣瞭一種分級的基-4 IFFT 改進 SLM算法降低其 PAPR.該算法將 N =4n 點的基-4 IFFT 運算分為前 k 級和後 n-k 級的蝶形運算,信號在兩級 IFFT 之間乘以相位序列.理論分析錶明:該法較傳統 SLM算法 IFFT 複雜度可降低近60%.
목전수찬측정신호무법실현고속전수,현유적정하니장맥충전수기술전수속솔교만.본문제출료일충정교빈분복용(OFDM)수찬무선전수계통가이실현고효적정하수거전수.단해계통존재기발사신호중고유적고봉균공솔비(PAPR)문제.본문기우 OFDM수찬무선전수계통,제출료일충분급적기-4 IFFT 개진 SLM산법강저기 PAPR.해산법장 N =4n 점적기-4 IFFT 운산분위전 k 급화후 n-k 급적접형운산,신호재량급 IFFT 지간승이상위서렬.이론분석표명:해법교전통 SLM산법 IFFT 복잡도가강저근60%.
High-speed transmission of LWD signals is difficult to achieve by current technology.The existing downhole mud pulse transmission technology cannot meet the requirements due to its low transmission rate.To cope with this problem,this paper improves while-drilling wireless transmission system with orthogonal frequency division multiplexing (OFDM),which will result in more efficient data transmission.However,the high peak-to-average power ratio (PAPR)of the logging signals in the OFDM will gravely impact its performance.To further improve OFDM drilling wireless transmission system,we propose an SLM algorithm us-ing radix-4 inverse fast Fourier transform (IFFT)to reduce PAPR.In this method,the radix-4-based IFFT performance at point N =4n is partitioned into two stages:transform before k and transform after n-k,between which the phase sequences are multiplied by an input signal.Theoretical analysis shows that,compared with the traditional SLM algorithm,the new SLM reduces the computational complexity almost by 60%.