频谱聚合中非数据辅助的幅频相估计与补偿

认知无线电中宽带信号需采用频谱分割与聚合滤波器组技术实现对频谱空穴的高效利用.由于不同子频谱的幅频相受到无线信道的干扰，在接收端子谱聚合时，幅、频、相误差对聚合信号会产生畸变，导致检测性能恶化.对此，提出了基于非数据辅助的幅、频、相失真估计补偿算法，利用相邻子频谱在过渡带内的幅频相一致性特点，在频域进行过渡带内信号的对齐处理，从而在子频谱聚合之前修正幅度、频率和相位，以恢复原信号谱.仿真结果表明，该算法能够有效地解决因分割子频谱在信道传输过程中造成的幅频相失真问题，系统解调的误码率性能接近相同系统参数下常规的导频估计算法，所提算法具有较高的估计精度和高效的频谱利用率.

Non-Data-Aided Estimation and Compensation of Amplitude,Frequency and Phase for Spectrum Combination

In cognitive radios,broadband signals need to be applied with spectrum division and combination filter banks to efficiently utilize spectrum holes. As the amplitude,frequency and phase of different sub-spectra are interfered by the wireless channel,when the sub-spectra are combined,the amplitude,frequency and phase errors distort the recombination signal,leading to the degradation of detection perfor-mance. A non-data-aided estimation and compensation algorithm is proposed. By utilizing the amplitude-frequency-phase consistency between adjacent sub-spectra in the transition band and performing the alignment process in the frequency domain,the amplitude,frequency and phase are modified before sub-spectra combination to recover the original signal. Simulation results show that the proposed algorithm can effectively solve the amplitude-frequency-phase distortion caused by sub-spectra segmentation. The bit error rate performance of the proposed algorithm is close to that of the pilot estimation algorithm with the same system parameters. The proposed algorithm can not only obtain high-precision amplitude-frequency-phase estimation and compensation,but also utilize spectrum efficiently.