A 6.25 Gbps SerDes core used in the high signed based on the OIF-CEI-02.0 standard. To speed backplane communication receiver has been decounteract the serious Inter-Syrmbol-Interference （ISI）, the core employed a h...A 6.25 Gbps SerDes core used in the high signed based on the OIF-CEI-02.0 standard. To speed backplane communication receiver has been decounteract the serious Inter-Syrmbol-Interference （ISI）, the core employed a half-rate four-tap decision feedback equalizer （DFE）. The equalizer used the Signsign least mean-squared （SS-LMS） algorithm to realize the coefficient adaptation. An automatic gain control （AGC） amplifier with the sign least mean-squared （S-LMS） algorithm has been used to compensate the transmission media loss. To recover the clock signal from the input data serial and provide for the DFE and AGC, a bang-bang clock recovery （BB-CR） is adopted. A third order phase loop loek （PLL） model was proposed to predict characteristics of the BB-CR. The core has been verified by behavioral modeling in MATLAB. The results indicate that the core can meet the specifications of the backplane receiver. The DFE recovered data over a 34＂ FR-4 backplane has a peak-to-peak jitter of 17 ps, a horizontal eye opening of 0.87 UI, and a vertical eye opening of 500 mVpp.展开更多
A new equalization method is proposed in this paper for severely nonlinear distorted channels. The structure of decision feedback is adopted for the non-singleton fuzzy regular neural network that is trained by gradie...A new equalization method is proposed in this paper for severely nonlinear distorted channels. The structure of decision feedback is adopted for the non-singleton fuzzy regular neural network that is trained by gradient-descent algorithm. The model shows a much better performance on anti-jamming and nonlinear classification, and simulation is carried out to compare this method with other nonlinear channel equalization methods. The results show the method has the least bit error rate （BER）.展开更多
A Simple and useful decision feedback equalizer used for non-linear channels with severe linear distortion and mild non-linear distortion is proposed. It is a combination of a nonlinear channel equalizer based on conn...A Simple and useful decision feedback equalizer used for non-linear channels with severe linear distortion and mild non-linear distortion is proposed. It is a combination of a nonlinear channel equalizer based on connectionist model and a common decision feedback equalizer for linear channels. For a typical non-linear channel model it is shown that the equalization performances of the proposed equalizer are improved significantly.展开更多
This work proposes an improved inertia weight update method and position update method in Particle Swarm Optimization (PSO) to enhance the convergence and mean square error of channel equalizer. The search abilities o...This work proposes an improved inertia weight update method and position update method in Particle Swarm Optimization (PSO) to enhance the convergence and mean square error of channel equalizer. The search abilities of PSO are managed by the key parameter Inertia Weight (IW). A higher value leads to global search whereas a smaller value shifts the search to local which makes convergence faster. Different approaches are reported in literature to improve PSO by modifying inertia weight. This work investigates the performance of the existing PSO variants related to time varying inertia weight methods and proposes new strategies to improve the convergence and mean square error of channel equalizer. Also the position update method in PSO is modified to achieve better convergence in channel equalization. The simulation presents the enhanced performance of the proposed techniques in transversal and decision feedback models. The simulation results also analyze the superiority in linear and nonlinear channel conditions.展开更多
Artificial Neural Network (ANN) equalizers have been successfully applied to mitigate Inter symbolic Interference (ISI) due to distortions introduced by linear or nonlinear communication channels. The ANN architecture...Artificial Neural Network (ANN) equalizers have been successfully applied to mitigate Inter symbolic Interference (ISI) due to distortions introduced by linear or nonlinear communication channels. The ANN architecture is chosen according to the type of ISI produced by fixed, fast or slow fading channels. In this work, we propose a combination of two techniques in order to minimize ISI yield by fast fading channels, i.e., pulse shape filtering and ANN equalizer. Levenberg-Marquardt algorithm is used to update the synaptic weights of an ANN comprise only by two recurrent perceptrons. The proposed system outperformed more complex structures such as those based on Kalman filtering approach.展开更多
提出了一种适用于超短距离(Very Short Reach,VSR)信道、面向112 Gb/s PAM4(Pulse Amplitude Modulation 4)接收机的自适应均衡设计方案。在该方案中,接收机前端利用3个连续时间线性均衡器(Continuous Time Linear Equalizer,CTLE)对信...提出了一种适用于超短距离(Very Short Reach,VSR)信道、面向112 Gb/s PAM4(Pulse Amplitude Modulation 4)接收机的自适应均衡设计方案。在该方案中,接收机前端利用3个连续时间线性均衡器(Continuous Time Linear Equalizer,CTLE)对信号分别在高频、中频和低频进行补偿,可变增益放大器(Variable Gain Amplifier,VGA)和饱和放大器(Saturation Amplifier,SatAmp)则用于对信号幅值的缩放。除了3个数据采样器外,引入4个辅助采样器用于进一步改善阈值自适应算法性能。同时,采用符号最小均方算法,利用接收端数据采样器和辅助采样器之间的偏移推动辅助参考电压收敛到信号星座电平,从而确保PAM4接收信号的眼图在垂直方向上3个眼睛具有相等的间隔和恒定的信噪比(Signal-to-Noise Ratio,SNR)。仿真结果表明,所提出的112 Gb/s PAM4接收机能够在损耗为15 dB的信道上实现小于10~(-12)的误码率,并且具有良好的眼图性能,其最差眼高为75 mV,眼宽为0.34 UI(Unit Interval),与传统方案相比具有显著的性能提升。展开更多
基金Supported by the High Technology Research and Development Programme of China (No. 2003AA31g030).
文摘A 6.25 Gbps SerDes core used in the high signed based on the OIF-CEI-02.0 standard. To speed backplane communication receiver has been decounteract the serious Inter-Syrmbol-Interference （ISI）, the core employed a half-rate four-tap decision feedback equalizer （DFE）. The equalizer used the Signsign least mean-squared （SS-LMS） algorithm to realize the coefficient adaptation. An automatic gain control （AGC） amplifier with the sign least mean-squared （S-LMS） algorithm has been used to compensate the transmission media loss. To recover the clock signal from the input data serial and provide for the DFE and AGC, a bang-bang clock recovery （BB-CR） is adopted. A third order phase loop loek （PLL） model was proposed to predict characteristics of the BB-CR. The core has been verified by behavioral modeling in MATLAB. The results indicate that the core can meet the specifications of the backplane receiver. The DFE recovered data over a 34＂ FR-4 backplane has a peak-to-peak jitter of 17 ps, a horizontal eye opening of 0.87 UI, and a vertical eye opening of 500 mVpp.
文摘A new equalization method is proposed in this paper for severely nonlinear distorted channels. The structure of decision feedback is adopted for the non-singleton fuzzy regular neural network that is trained by gradient-descent algorithm. The model shows a much better performance on anti-jamming and nonlinear classification, and simulation is carried out to compare this method with other nonlinear channel equalization methods. The results show the method has the least bit error rate （BER）.
基金Supported by the National Natural Science Foundation of China
文摘A Simple and useful decision feedback equalizer used for non-linear channels with severe linear distortion and mild non-linear distortion is proposed. It is a combination of a nonlinear channel equalizer based on connectionist model and a common decision feedback equalizer for linear channels. For a typical non-linear channel model it is shown that the equalization performances of the proposed equalizer are improved significantly.
文摘This work proposes an improved inertia weight update method and position update method in Particle Swarm Optimization (PSO) to enhance the convergence and mean square error of channel equalizer. The search abilities of PSO are managed by the key parameter Inertia Weight (IW). A higher value leads to global search whereas a smaller value shifts the search to local which makes convergence faster. Different approaches are reported in literature to improve PSO by modifying inertia weight. This work investigates the performance of the existing PSO variants related to time varying inertia weight methods and proposes new strategies to improve the convergence and mean square error of channel equalizer. Also the position update method in PSO is modified to achieve better convergence in channel equalization. The simulation presents the enhanced performance of the proposed techniques in transversal and decision feedback models. The simulation results also analyze the superiority in linear and nonlinear channel conditions.
文摘Artificial Neural Network (ANN) equalizers have been successfully applied to mitigate Inter symbolic Interference (ISI) due to distortions introduced by linear or nonlinear communication channels. The ANN architecture is chosen according to the type of ISI produced by fixed, fast or slow fading channels. In this work, we propose a combination of two techniques in order to minimize ISI yield by fast fading channels, i.e., pulse shape filtering and ANN equalizer. Levenberg-Marquardt algorithm is used to update the synaptic weights of an ANN comprise only by two recurrent perceptrons. The proposed system outperformed more complex structures such as those based on Kalman filtering approach.
