针对混沌通信系统的非线性信道干扰问题,基于混沌信号重构理论和函数型连接神经网络理论,提出了一种横向滤波器与函数型连接神经网络组合(combination of transversal filter and functional link neural network,CFFLNN)的自适应非线...针对混沌通信系统的非线性信道干扰问题,基于混沌信号重构理论和函数型连接神经网络理论,提出了一种横向滤波器与函数型连接神经网络组合(combination of transversal filter and functional link neural network,CFFLNN)的自适应非线性信道均衡器,并给出基于低复杂度归一化最小均方(NLMS)的自适应算法,并对该均衡器的稳定性以及收敛条件进行了分析.该非线性自适应均衡器充分利用了横向滤波器的快速收敛,以及函数型连接神经网络通过增大输入空间提高非线性逼近能力的特点,进一步提高均衡器的收敛速度和降低稳态误差.仿真研究表明:所提出的非线性自适应均衡器能够有效地消除线性和非线性信道干扰,均衡器输出信号能反映出混沌信号的特性,具有良好的抗干扰性能;且该均衡器的结构简单,收敛稳定性较好,易于工程实现.展开更多
This Letter proposes a post-equalizer for underwater visible light communication(UVLC) systems that combines channel estimation and joint time-frequency analysis, named channel-estimation-based bandpass variable-order...This Letter proposes a post-equalizer for underwater visible light communication(UVLC) systems that combines channel estimation and joint time-frequency analysis, named channel-estimation-based bandpass variable-order time-frequency network(CBV-TFNet). By utilizing a bandpass variable-order loss function with communication prior knowledge, CBVTFNet enhances communication performance and training stability. It enables lightweight implementation and faster convergence through a channel estimation-based mask. The superior performance of the proposed equalization method over Volterra and deep neural network(DNN)-based methods has been studied experimentally. Using bit-power loading discrete multitone (DMT) modulation, the proposed method achieves a transmission bitrate of 4.956 Gbps through a 1.2 m underwater channel utilizing only 38.15% of real multiplication calculations compared to the DNN equalizer and achieving a bitrate gain of440 Mbps and a significantly larger dynamic range over the LMS-Volterra equalizer. Results highlight CBV-TFNet's potential for future post-equalization in UVLC systems.展开更多
To mitigate the linear and nonlinear distortions in communication systems, two novel nonlinear adaptive equalizers are proposed on the basis of the neural finite impulse response （FIR） filter, decision feedback arch...To mitigate the linear and nonlinear distortions in communication systems, two novel nonlinear adaptive equalizers are proposed on the basis of the neural finite impulse response （FIR） filter, decision feedback architecture and the characteristic of the Laguerre filter. They are neural FIR adaptive decision feedback equalizer （SNNDFE） and neural FIR adaptive Laguerre equalizer （LSNN）. Of these two equalizers, the latter is simple and with characteristics of both infinite impulse response （IIR） and FIR filters; it can use shorter memory length to obtain better performance. As confirmed by theoretical analysis, the novel LSNN equalizer is stable （0 〈α〈1）. Furthermore, simulation results show that the SNNDFE can get better equalized performance than SNN equalizer, while the latter exhibits better performance than others in terms of convergence speed, mean square error （MSE） and bit error rate （BER）. Therefore, it can reduce the input dimension and eliminate linear and nonlinear interference effectively. In addition, it is very suitable for hardware implementation due to its simple structure.展开更多
信道均衡器是无线传感网OFDM系统的关键部分,传统均衡器设计在信道估计精度或电路复杂度上效果不佳。为使均衡器更精确、复杂度更低,采用快速LMMSE算法进行信道估计与均衡,定制了精简的20位浮点数进行均衡器电路设计。电路经过综合、仿...信道均衡器是无线传感网OFDM系统的关键部分,传统均衡器设计在信道估计精度或电路复杂度上效果不佳。为使均衡器更精确、复杂度更低,采用快速LMMSE算法进行信道估计与均衡,定制了精简的20位浮点数进行均衡器电路设计。电路经过综合、仿真与FPGA验证,结果表明,均衡器电路复杂度低,性能显著提高。相比于传统LS算法均衡器,在资源消耗仅增加27.27%的情况下,16 d B载噪比下误码率降低了89.8%,实现了低复杂度高性能的均衡器电路。展开更多
文章从分析MCMA算法的原理出发,研究了其在信道均衡技术上的应用,重点阐述了通过Matlab仿真和Xilinx System Generator for DSP开发软件在FPGA上实现基于MCMA算法的盲均衡器的方法。从硬件协同仿真结果可以看出,实现的盲信道均衡器能够...文章从分析MCMA算法的原理出发,研究了其在信道均衡技术上的应用,重点阐述了通过Matlab仿真和Xilinx System Generator for DSP开发软件在FPGA上实现基于MCMA算法的盲均衡器的方法。从硬件协同仿真结果可以看出,实现的盲信道均衡器能够达到消除码间干扰的效果。展开更多
文摘针对混沌通信系统的非线性信道干扰问题,基于混沌信号重构理论和函数型连接神经网络理论,提出了一种横向滤波器与函数型连接神经网络组合(combination of transversal filter and functional link neural network,CFFLNN)的自适应非线性信道均衡器,并给出基于低复杂度归一化最小均方(NLMS)的自适应算法,并对该均衡器的稳定性以及收敛条件进行了分析.该非线性自适应均衡器充分利用了横向滤波器的快速收敛,以及函数型连接神经网络通过增大输入空间提高非线性逼近能力的特点,进一步提高均衡器的收敛速度和降低稳态误差.仿真研究表明:所提出的非线性自适应均衡器能够有效地消除线性和非线性信道干扰,均衡器输出信号能反映出混沌信号的特性,具有良好的抗干扰性能;且该均衡器的结构简单,收敛稳定性较好,易于工程实现.
基金supported by the National Key Research and Development Program of China (No. 2022YFB2802803)the National Natural Science Foundation of China (Nos. 61925104, 62031011, and 62201157)。
文摘This Letter proposes a post-equalizer for underwater visible light communication(UVLC) systems that combines channel estimation and joint time-frequency analysis, named channel-estimation-based bandpass variable-order time-frequency network(CBV-TFNet). By utilizing a bandpass variable-order loss function with communication prior knowledge, CBVTFNet enhances communication performance and training stability. It enables lightweight implementation and faster convergence through a channel estimation-based mask. The superior performance of the proposed equalization method over Volterra and deep neural network(DNN)-based methods has been studied experimentally. Using bit-power loading discrete multitone (DMT) modulation, the proposed method achieves a transmission bitrate of 4.956 Gbps through a 1.2 m underwater channel utilizing only 38.15% of real multiplication calculations compared to the DNN equalizer and achieving a bitrate gain of440 Mbps and a significantly larger dynamic range over the LMS-Volterra equalizer. Results highlight CBV-TFNet's potential for future post-equalization in UVLC systems.
基金Supported partially by the National Natural Science Foundation of China (Grant No. 60971104)the Program for New Century Excellent Talents in University of China (Grant No. NCET-05-0794)the Doctoral Innovation Fund of Southwest Jiaotong University
文摘To mitigate the linear and nonlinear distortions in communication systems, two novel nonlinear adaptive equalizers are proposed on the basis of the neural finite impulse response （FIR） filter, decision feedback architecture and the characteristic of the Laguerre filter. They are neural FIR adaptive decision feedback equalizer （SNNDFE） and neural FIR adaptive Laguerre equalizer （LSNN）. Of these two equalizers, the latter is simple and with characteristics of both infinite impulse response （IIR） and FIR filters; it can use shorter memory length to obtain better performance. As confirmed by theoretical analysis, the novel LSNN equalizer is stable （0 〈α〈1）. Furthermore, simulation results show that the SNNDFE can get better equalized performance than SNN equalizer, while the latter exhibits better performance than others in terms of convergence speed, mean square error （MSE） and bit error rate （BER）. Therefore, it can reduce the input dimension and eliminate linear and nonlinear interference effectively. In addition, it is very suitable for hardware implementation due to its simple structure.
文摘信道均衡器是无线传感网OFDM系统的关键部分,传统均衡器设计在信道估计精度或电路复杂度上效果不佳。为使均衡器更精确、复杂度更低,采用快速LMMSE算法进行信道估计与均衡,定制了精简的20位浮点数进行均衡器电路设计。电路经过综合、仿真与FPGA验证,结果表明,均衡器电路复杂度低,性能显著提高。相比于传统LS算法均衡器,在资源消耗仅增加27.27%的情况下,16 d B载噪比下误码率降低了89.8%,实现了低复杂度高性能的均衡器电路。
