1-bit采样因其低成本、低功耗等优势引起了广泛关注,本文主要讨论1-bit采样下雷达的脉压性能。首先,推导了1-bit采样造成的信噪比损失,分析了1-bit采样的适用条件,进而发现1-bit采样适合于单次回波信噪比较低的应用场景。接着,通过理论...1-bit采样因其低成本、低功耗等优势引起了广泛关注,本文主要讨论1-bit采样下雷达的脉压性能。首先,推导了1-bit采样造成的信噪比损失,分析了1-bit采样的适用条件,进而发现1-bit采样适合于单次回波信噪比较低的应用场景。接着,通过理论分析可知相对于高精度脉压系数,1-bit脉压系数会带来额外的脉压信噪比损失,但实现方式更为简单。此外,分析了在高信噪比下,发射信号为线性调频(linear frequency modulation,LFM)信号时周期性假目标出现的原因,并且指出相位编码可有效避免假目标出现。仿真实验验证了以上理论推导的正确性。最后,结合某高频(high frequency,HF)地波雷达的实测数据验证了1-bit采样的可行性。展开更多
With a low resolution 1-bit ADC on its receiver(RX) side, MIMO with 1-bit ADC took a considerable step in the fulfillment of the hardware complexity constrains of the internet of things(IoT) PHY layer design. However,...With a low resolution 1-bit ADC on its receiver(RX) side, MIMO with 1-bit ADC took a considerable step in the fulfillment of the hardware complexity constrains of the internet of things(IoT) PHY layer design. However, applying 1-bit ADC at MIMO RX results in severe nonlinear quantization error. By which, almost all received signal amplitude information is completely distorted. Thus, MIMO channel estimation is considered as a major barrier towards practical realization of 1-bit ADC MIMO system. In this paper, two efficient sparsity-based channel estimation techniques are proposed for 1-bit ADC MIMO systems, namely the low complexity sparsity-based channel estimation(LCSCE), and the iterative adaptive sparsity channel estimation(IASCE). In these techniques, the sparsity of the 1-bit ADC MIMO channel is exploited to propose a new adaptive and iterative compressive sensing(CS) recovery algorithm to handle the 1-bit ADC quantization effect. The proposed algorithms are tested with the state-of-the-art 1-bit ADC MIMO constant envelope modulation(MIMO-CEM). The 1-bit ADC MIMO-CEM system is chosen as it fulfills both energy and hardware complexity constraints of the IoT PHY layer. Simulation results reveal the high effectiveness of the proposed algorithms in terms of spectral efficiency(SE) and computational complexity. The proposed LCSCE reduces the computational complexity of the 1-bit ADC MIMO-CEM channel estimation by 86%, while the IASCE reduces it by 96% compared to the recent techniques of MIMO-CEM channel estimation. Moreover, the proposed LCSCE and IASCE improve the spectrum efficiency by 76 % and 73 %, respectively, compared to the recent techniques.展开更多
This paper proposes a method to improve the spu-rious-free dynamic ranges(SFDRs)of 1-bit sampled signals greatly,which is very beneficial to multi-tone signals detection.Firstly,the relationship between the fundamenta...This paper proposes a method to improve the spu-rious-free dynamic ranges(SFDRs)of 1-bit sampled signals greatly,which is very beneficial to multi-tone signals detection.Firstly,the relationship between the fundamental component and the third harmonic component of 1-bit sampled signals is analyzed for determining four contiguous special frequency bands,which do not contain any third harmonics inside and co-ver 77.8%of the whole Nyquist sampling frequency band.Then,we present a special 4-channel monobit receiver model,where appropriate filter banks are used to obtain four desired pass bands before 1-bit quantization and each channel can sample and process sampled data independently to achieve a good in-stantaneous dynamic range without sacrificing the real-time per-formance or computing resources.The simulation results show that the proposed method effectively eliminates the effect of the most harmonics on SFDRs and the mean SFDR is increased to to 20 dB.Besides,the multi-signals simulation results indicate that the maximum amplitude separation(dynamic range)of two signals in each channel is 12 dB while the proposed monobit re-ceiver can deal with up to eight simultaneous arrival signals.In general,the designing method proposed in this paper has a po-tential engineering value.展开更多
文摘1-bit采样因其低成本、低功耗等优势引起了广泛关注,本文主要讨论1-bit采样下雷达的脉压性能。首先,推导了1-bit采样造成的信噪比损失,分析了1-bit采样的适用条件,进而发现1-bit采样适合于单次回波信噪比较低的应用场景。接着,通过理论分析可知相对于高精度脉压系数,1-bit脉压系数会带来额外的脉压信噪比损失,但实现方式更为简单。此外,分析了在高信噪比下,发射信号为线性调频(linear frequency modulation,LFM)信号时周期性假目标出现的原因,并且指出相位编码可有效避免假目标出现。仿真实验验证了以上理论推导的正确性。最后,结合某高频(high frequency,HF)地波雷达的实测数据验证了1-bit采样的可行性。
文摘With a low resolution 1-bit ADC on its receiver(RX) side, MIMO with 1-bit ADC took a considerable step in the fulfillment of the hardware complexity constrains of the internet of things(IoT) PHY layer design. However, applying 1-bit ADC at MIMO RX results in severe nonlinear quantization error. By which, almost all received signal amplitude information is completely distorted. Thus, MIMO channel estimation is considered as a major barrier towards practical realization of 1-bit ADC MIMO system. In this paper, two efficient sparsity-based channel estimation techniques are proposed for 1-bit ADC MIMO systems, namely the low complexity sparsity-based channel estimation(LCSCE), and the iterative adaptive sparsity channel estimation(IASCE). In these techniques, the sparsity of the 1-bit ADC MIMO channel is exploited to propose a new adaptive and iterative compressive sensing(CS) recovery algorithm to handle the 1-bit ADC quantization effect. The proposed algorithms are tested with the state-of-the-art 1-bit ADC MIMO constant envelope modulation(MIMO-CEM). The 1-bit ADC MIMO-CEM system is chosen as it fulfills both energy and hardware complexity constraints of the IoT PHY layer. Simulation results reveal the high effectiveness of the proposed algorithms in terms of spectral efficiency(SE) and computational complexity. The proposed LCSCE reduces the computational complexity of the 1-bit ADC MIMO-CEM channel estimation by 86%, while the IASCE reduces it by 96% compared to the recent techniques of MIMO-CEM channel estimation. Moreover, the proposed LCSCE and IASCE improve the spectrum efficiency by 76 % and 73 %, respectively, compared to the recent techniques.
文摘This paper proposes a method to improve the spu-rious-free dynamic ranges(SFDRs)of 1-bit sampled signals greatly,which is very beneficial to multi-tone signals detection.Firstly,the relationship between the fundamental component and the third harmonic component of 1-bit sampled signals is analyzed for determining four contiguous special frequency bands,which do not contain any third harmonics inside and co-ver 77.8%of the whole Nyquist sampling frequency band.Then,we present a special 4-channel monobit receiver model,where appropriate filter banks are used to obtain four desired pass bands before 1-bit quantization and each channel can sample and process sampled data independently to achieve a good in-stantaneous dynamic range without sacrificing the real-time per-formance or computing resources.The simulation results show that the proposed method effectively eliminates the effect of the most harmonics on SFDRs and the mean SFDR is increased to to 20 dB.Besides,the multi-signals simulation results indicate that the maximum amplitude separation(dynamic range)of two signals in each channel is 12 dB while the proposed monobit re-ceiver can deal with up to eight simultaneous arrival signals.In general,the designing method proposed in this paper has a po-tential engineering value.
