Time-Frequency Energy Sensing of Communication Signals and Its Application in Co-Channel Interference Suppression

Abstract

As the number of mobile users and video traffics grow explosively, the data rate demands increase tremendously. To improve the spectral efficiency, the spectrum are reused inter cell or intra cell, such as the ultra dense network with multi-cell or the cellular network with Device-to-Device communications, where the co-channel interferences are brought and needs to be suppressed. According to the time-frequency energy sensing to the communication signals, the desired signal and the interference signal have different energy concentration areas on the time frequency plane, which provide opportunities to suppress the co-channel interference with time varying filter. This paper analyzes the time-frequency distributions of the Gaussian pulse shaping signals, discusses the effect of the analyzing window length on the time-frequency resolution, exploits the equivalence between the time frequency analysis at the baseband and at the radio front end, and finally reveals the advantages of the proposed masking threshold constrained time varying filter based co-channel interference mitigation method. The pass region for the linear time varying filter is generated according to the time-varying energy characteristics of the I/Q separated 4-QAM pulse shaping signals, where the optimum masking threshold is obtained by the optimum-BER criterion. The proposed co-channel interference suppression method is evaluated in aspect of BER performance, and simulation results show that the proposed method outperforms existing methods with low-pass or band-pass filters.

Time-Varying SAR Interference Suppression Based on Delay-Doppler Iterative Decomposition Algorithm

“…( ) mean  denotes the mean value of the signal. From Equation (35), the greater the contrast D is, the better the image quality well be.…”

“…In this paper, we mainly focus on the linear frequency modulated (LFM) WBI (LFM-WBI), since some complex signal can be modeled as an LFM signal within a short time. Due to its good concentration at each time slice, short time Fourier transform (STFT) [34][35][36][37][38][39][40][41] has been shown as an effective tool for time-varying WBI suppression. The energy of interference concentrates in a few frequency bins in the instantaneous frequency spectrum at each time slice.…”

“…2 mean z p,n 2(35) where z p,n represents the (p-th, n-th) pixel in the SAR image; mean() denotes the mean value of the signal. From Equation(35), the greater the contrast D is, the better the image quality well be.Remote Sens. 2018,10, 1491 …”