An Improved SRS Noise Estimation Algorithm Based on Interference Cancellation

This thesis studies SRS noise estimation method with multi-users in the Long Term Evolution(LTE), and proposes a Discrete Fourier Transform (DFT) time-domain filtering algorithm based on interference cancellation. By calculating signal power in the system protecting band, decision threshold of time domain filtering can be denoted. Therefore, one can reduce the impact of noise on the useful signal within the window, and also obtain a more accurate noise estimation. Simulation results show that either in the case of single-user or multi-user, the proposed algorithm can get good performance. At the same time, the algorithm can accurately reflect the impact in neighborhood interference on each band channel quality, so as to achieve the frequency domain resource selective scheduling effectively.