逐次逼近寄存器模数转换器(SAR ADC)在逐次逼近的过程中,电容的切换会使参考电压上出现参考纹波噪声,该噪声会影响比较器的判定,进而输出错误的比较结果。针对该问题,基于CMOS 0.5μm工艺,设计了一种具有纹波消除技术的10 bit SAR ADC...逐次逼近寄存器模数转换器(SAR ADC)在逐次逼近的过程中,电容的切换会使参考电压上出现参考纹波噪声,该噪声会影响比较器的判定,进而输出错误的比较结果。针对该问题,基于CMOS 0.5μm工艺,设计了一种具有纹波消除技术的10 bit SAR ADC。通过增加纹波至比较器输入端的额外路径,将参考纹波满摆幅输入至比较器中;同时设计了消除数模转换器(DAC)模块,对参考纹波进行采样和输入,通过反转纹波噪声的极性,消除参考纹波对ADC输出的影响。该设计将信噪比(SNR)提高到56.75 dB,将有效位数(ENOB)提升到9.14 bit,将积分非线性(INL)从-1~5 LSB降低到-0.2~0.3 LSB,将微分非线性(DNL)从-3~4 LSB降低到-0.5~0.5 LSB。展开更多
In this paper, we analyze the physical layer abstraction for bit interleaved coded orthogonal frequency division multiplexing(BIC-OFDM) system from a parallel bit channel perspective. By combining the exponential effe...In this paper, we analyze the physical layer abstraction for bit interleaved coded orthogonal frequency division multiplexing(BIC-OFDM) system from a parallel bit channel perspective. By combining the exponential effective SNR(signal-to-noise ratio) mapping(EESM) with the maximum a posteriori(MAP) algorithm, a bit LLR(log-likelihood ratio) wise EESM(BL-EESM) method is proposed. This method can abstract the link performance with high accuracy, especially for the case when channel estimation is imperfect. Afterward, the BL-EESM method is simplified by utilizing the non-linear quantization idea, which can reduce the times of exponential operation by two orders of magnitude at wide system bandwidth, yet shows little loss in accuracy. Our proposal can be applied to both system level simulations to save the time consumption and to practical terminals to facilitate the adaptive modulation and coding(AMC) procedure, bringing about throughput improvement at low hardware cost.展开更多
This Letter presents a simple and effective method to improve the signal-to-noise ratio（SNR） of compressing imaging. The main principles of the proposed method are the correlation of the image signals and the random...This Letter presents a simple and effective method to improve the signal-to-noise ratio（SNR） of compressing imaging. The main principles of the proposed method are the correlation of the image signals and the randomness of the noise. Multiple low SNR images are reconstructed firstly by the compressed sensing reconstruction algorithm, and then two-dimensional time delay integration technology is adopted to improve the SNR. Results show that the proposed method can improve the SNR performance efficiently and it is easy to apply the a lgorithm to the real project.展开更多
Stochastic resonance （SR） has been proved to be an effective approach to extract weak signals overwhelmed in noise. However, the detection effect of current SR models is still unsatisfactory. Here, a coupled tri-sta...Stochastic resonance （SR） has been proved to be an effective approach to extract weak signals overwhelmed in noise. However, the detection effect of current SR models is still unsatisfactory. Here, a coupled tri-stable stochastic resonance （CTSSR） model is proposed to further increase the output signal-to-noise ratio （SNR） and improve the detection effect of SR. The effects of parameters a, b, c, and r in the proposed resonance system on the SNR are studied, by which we determine a set of parameters that is relatively optimal to implement a comparison with other classical SR models. Numerical experiment results indicate that this proposed model performs better in weak signal detection applications than the classical ones with merits of higher output SNR and better anti-noise capability.展开更多
In the exploration,tracking and positioning of underwater targets,it is necessary to perform frequency domain analysis and correlation calculation on the underwater acoustic signals of the target radiation.In a strong...In the exploration,tracking and positioning of underwater targets,it is necessary to perform frequency domain analysis and correlation calculation on the underwater acoustic signals of the target radiation.In a strong noise environment,the target signal may be overwhelmed by noise,resulting in an inability to effectively identify the target.Aiming at this problem,this paper presents a method of signal-noise separation by combining Fourier denoising with wavelet transform to realize underwater acoustic signal extraction in a strong noise environment.The combination algorithm of Fourier coefficient threshold adjustment and wavelet threshold transform is designed,and performance of the algorithm is tested.Simulation results show that the combination algorithm can effectively extract underwater acoustic signals when signal-to-noise ratio(SNR)is-15 dB,which can improve the SNR to 8.2 dB.展开更多
基金the Shanghai Basic Research KeyProject(No.11DZ1500206)the NationalScience and Technology Major Project of China(No.2012ZX03001013-003)
文摘In this paper, we analyze the physical layer abstraction for bit interleaved coded orthogonal frequency division multiplexing(BIC-OFDM) system from a parallel bit channel perspective. By combining the exponential effective SNR(signal-to-noise ratio) mapping(EESM) with the maximum a posteriori(MAP) algorithm, a bit LLR(log-likelihood ratio) wise EESM(BL-EESM) method is proposed. This method can abstract the link performance with high accuracy, especially for the case when channel estimation is imperfect. Afterward, the BL-EESM method is simplified by utilizing the non-linear quantization idea, which can reduce the times of exponential operation by two orders of magnitude at wide system bandwidth, yet shows little loss in accuracy. Our proposal can be applied to both system level simulations to save the time consumption and to practical terminals to facilitate the adaptive modulation and coding(AMC) procedure, bringing about throughput improvement at low hardware cost.
基金supported by the National Natural Science Foundation of China(No.11503010)the Fundamental Research Funds for the Central Universities(No.30916015103)
文摘This Letter presents a simple and effective method to improve the signal-to-noise ratio（SNR） of compressing imaging. The main principles of the proposed method are the correlation of the image signals and the randomness of the noise. Multiple low SNR images are reconstructed firstly by the compressed sensing reconstruction algorithm, and then two-dimensional time delay integration technology is adopted to improve the SNR. Results show that the proposed method can improve the SNR performance efficiently and it is easy to apply the a lgorithm to the real project.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61071025 and 61502538)
文摘Stochastic resonance （SR） has been proved to be an effective approach to extract weak signals overwhelmed in noise. However, the detection effect of current SR models is still unsatisfactory. Here, a coupled tri-stable stochastic resonance （CTSSR） model is proposed to further increase the output signal-to-noise ratio （SNR） and improve the detection effect of SR. The effects of parameters a, b, c, and r in the proposed resonance system on the SNR are studied, by which we determine a set of parameters that is relatively optimal to implement a comparison with other classical SR models. Numerical experiment results indicate that this proposed model performs better in weak signal detection applications than the classical ones with merits of higher output SNR and better anti-noise capability.
基金Applied Basic Research Project of Shanxi Province(Nos.201601D011035,201701D121067)Higher Education Technology Innovation Project of Shanxi Province(No.201804011)。
文摘In the exploration,tracking and positioning of underwater targets,it is necessary to perform frequency domain analysis and correlation calculation on the underwater acoustic signals of the target radiation.In a strong noise environment,the target signal may be overwhelmed by noise,resulting in an inability to effectively identify the target.Aiming at this problem,this paper presents a method of signal-noise separation by combining Fourier denoising with wavelet transform to realize underwater acoustic signal extraction in a strong noise environment.The combination algorithm of Fourier coefficient threshold adjustment and wavelet threshold transform is designed,and performance of the algorithm is tested.Simulation results show that the combination algorithm can effectively extract underwater acoustic signals when signal-to-noise ratio(SNR)is-15 dB,which can improve the SNR to 8.2 dB.
