The achievable bit error rate of a linear equalizer is crucially determined by the choice of a decision delay parameter. This brief paper presents a simple method for the efficient determination of the optimal decisio...The achievable bit error rate of a linear equalizer is crucially determined by the choice of a decision delay parameter. This brief paper presents a simple method for the efficient determination of the optimal decision delay parameter that results in the best bit error rate performance for a linear equalizer. Keywords Linear equalizer - decision delay - bit error rate Eng Siong Chng received his university education at the University of Edinburgh, Edinburgh, Scotland (BEng 1991, PhD 1995). After his PhD, he spent 6 months in Japan, working as a researcher for Riken. After working in industry in Singapore for 7 years, he joined the School of Computer Engineering, Nanyang Technological University in 2003. His research interests are in digital signal processing for communication applications, speech and handwriting recognition and noise reduction.Sheng Chen obtained a BEng degree in control engineering from the East China Petroleum Institute, Dongying, China, in 1982, and a PhD degree in control engineering from the City University at London in 1986. He joined the School of Electronics and Computer Science at the University of Southampton in September 1999. He previously held research and academic appointments at the Universities of Sheffield, Edinburgh and Portsmouth. Dr Chen is a Senior Member of the IEEE in the USA. His recent research works include adaptive nonlinear signal processing, modeling and identification of nonlinear systems, neural networks and machine learning, finite-precision digital controller design, evolutionary computation methods and optimization. He has published over 200 research papers. In the database of the world’s most highly cited researchers in various disciplines, compiled by the Institute for Scientific Information (ISI) of the USA, Dr Chen is on the list of highly cited researchers in the category that covers all branches of engineering subject, see www.ISIHighlyCited.com.展开更多
研究了水声图像高速传输信号处理方法,它包括两个方面,一方面是水声相干通信信号处理方法,其中:(1)多普勒频移补偿,在数据包的前后两端插入已知线性调频(Chirp)信号,拷贝相关后求互相关,估计相对多普勒平均频移。在自适应判决反馈均衡...研究了水声图像高速传输信号处理方法,它包括两个方面,一方面是水声相干通信信号处理方法,其中:(1)多普勒频移补偿,在数据包的前后两端插入已知线性调频(Chirp)信号,拷贝相关后求互相关,估计相对多普勒平均频移。在自适应判决反馈均衡器中加上自适应相位补偿器,采用快速自优化最小均方(LMS)算法,与其对应的速度容限优于常用的二阶锁相环相位补偿器的。两种补偿方法联合工作时,性能优良。(2)带有分集合并器的自适应判决反馈均衡器的算法是快速自优化的LMS算法,计算量小,性能优良。(3)自适应判决反馈均衡器与Turbo-网格编码调制(TCM)译码器级连、迭代算法。研究了基于软输出维特比(SOVA)方法的新型的比特-符号转换器,用它时误比特率(BER)比常规编码、映射方法的近似小2个数量级。另一方面是抗误码的图像压缩方法。本文基于数字小波变换和定长编码方法,研究了声图像的压缩。它包括:(1)选用CDF9/7小波进行小波变换。(2)对小波系数子带能量进行统计分析,三层小波分解是合适的。(3)对不同能量的子带采用不同的量化步长。(4)采用定长编码算法。结果表明声图像压缩比特率为0.85。当BER小于10^(-3)时,图像质量完好。当BER小于10^(-2)时,图像中出现少量小黑白点。在上述基础上研制了水声通信机,频带为(7.5～12.5)kHz,接收声呐阵为8基元等距线阵,信号为QPSK和8PSK。在中国千岛湖进行了湖试,采用SOVA硬迭代算法,达到了低BER。传输一幅256×256×8的声图需时约7s。传输距离与传输速率之积为55 km kbps。展开更多
文摘The achievable bit error rate of a linear equalizer is crucially determined by the choice of a decision delay parameter. This brief paper presents a simple method for the efficient determination of the optimal decision delay parameter that results in the best bit error rate performance for a linear equalizer. Keywords Linear equalizer - decision delay - bit error rate Eng Siong Chng received his university education at the University of Edinburgh, Edinburgh, Scotland (BEng 1991, PhD 1995). After his PhD, he spent 6 months in Japan, working as a researcher for Riken. After working in industry in Singapore for 7 years, he joined the School of Computer Engineering, Nanyang Technological University in 2003. His research interests are in digital signal processing for communication applications, speech and handwriting recognition and noise reduction.Sheng Chen obtained a BEng degree in control engineering from the East China Petroleum Institute, Dongying, China, in 1982, and a PhD degree in control engineering from the City University at London in 1986. He joined the School of Electronics and Computer Science at the University of Southampton in September 1999. He previously held research and academic appointments at the Universities of Sheffield, Edinburgh and Portsmouth. Dr Chen is a Senior Member of the IEEE in the USA. His recent research works include adaptive nonlinear signal processing, modeling and identification of nonlinear systems, neural networks and machine learning, finite-precision digital controller design, evolutionary computation methods and optimization. He has published over 200 research papers. In the database of the world’s most highly cited researchers in various disciplines, compiled by the Institute for Scientific Information (ISI) of the USA, Dr Chen is on the list of highly cited researchers in the category that covers all branches of engineering subject, see www.ISIHighlyCited.com.
文摘研究了水声图像高速传输信号处理方法,它包括两个方面,一方面是水声相干通信信号处理方法,其中:(1)多普勒频移补偿,在数据包的前后两端插入已知线性调频(Chirp)信号,拷贝相关后求互相关,估计相对多普勒平均频移。在自适应判决反馈均衡器中加上自适应相位补偿器,采用快速自优化最小均方(LMS)算法,与其对应的速度容限优于常用的二阶锁相环相位补偿器的。两种补偿方法联合工作时,性能优良。(2)带有分集合并器的自适应判决反馈均衡器的算法是快速自优化的LMS算法,计算量小,性能优良。(3)自适应判决反馈均衡器与Turbo-网格编码调制(TCM)译码器级连、迭代算法。研究了基于软输出维特比(SOVA)方法的新型的比特-符号转换器,用它时误比特率(BER)比常规编码、映射方法的近似小2个数量级。另一方面是抗误码的图像压缩方法。本文基于数字小波变换和定长编码方法,研究了声图像的压缩。它包括:(1)选用CDF9/7小波进行小波变换。(2)对小波系数子带能量进行统计分析,三层小波分解是合适的。(3)对不同能量的子带采用不同的量化步长。(4)采用定长编码算法。结果表明声图像压缩比特率为0.85。当BER小于10^(-3)时,图像质量完好。当BER小于10^(-2)时,图像中出现少量小黑白点。在上述基础上研制了水声通信机,频带为(7.5～12.5)kHz,接收声呐阵为8基元等距线阵,信号为QPSK和8PSK。在中国千岛湖进行了湖试,采用SOVA硬迭代算法,达到了低BER。传输一幅256×256×8的声图需时约7s。传输距离与传输速率之积为55 km kbps。
