An appropriate acquisition configuration in terms of signal quality can optimize the acquisition performance. In view of this, a new approach of acquisition assisted by the control voltage of automatic gain control(AG...An appropriate acquisition configuration in terms of signal quality can optimize the acquisition performance. In view of this, a new approach of acquisition assisted by the control voltage of automatic gain control(AGC) is proposed. This approach judges the signal power according to the AGC control voltage and switches the working modes correspondingly and adaptively. Non-coherent accumulation times and the detection threshold are reconfigured according to the working mode. Theoretical derivation and verification by simulation in typical situations are provided, and the algorithm is shown to be superior in terms of the mean acquisition time, especially in strong signal scenarios compared with the conventional algorithm.展开更多
文摘该文针对椭圆球面波(Prolate Spheroidal Wave Function,PSWF)时域正交调制信号峰均功率比过高,易受功率放大器非线性影响,造成信号失真,导致系统解调性能下降的问题,提出一种基于μ律压缩的自适应峰均比抑制方法。该方法能够根据输入信号自适应调节压缩参数,有效压缩信号峰值,降低PSWF调制信号峰均功率比(Peak-to-Average Power Ratio,PAPR),同时保证压缩前后信号平均功率不变。理论论证和仿真结果表明,该方法能够有效抑制PSWF调制信号PAPR,当压缩参数m为1且互补累计分布函数CCDF为410-时,压缩后调制信号与原调制信号相比PAPR降低约2.1 d B;有效改善经过功放后调制信号功率谱和系统在高斯白噪声信道下的误码性能。
基金supported by the National Natural Science Foundation of China(Grant No.61401026)the National High Technology Research and Development Program of China(Grant No.2014AA1070)
文摘An appropriate acquisition configuration in terms of signal quality can optimize the acquisition performance. In view of this, a new approach of acquisition assisted by the control voltage of automatic gain control(AGC) is proposed. This approach judges the signal power according to the AGC control voltage and switches the working modes correspondingly and adaptively. Non-coherent accumulation times and the detection threshold are reconfigured according to the working mode. Theoretical derivation and verification by simulation in typical situations are provided, and the algorithm is shown to be superior in terms of the mean acquisition time, especially in strong signal scenarios compared with the conventional algorithm.
