Abstract:
Passive intermodulation (PIM) often limits the performance of satellite communication systems with multicarriers. The PIM interference has a peculiarity of timevarying an...Show MoreMetadata
Abstract:
Passive intermodulation (PIM) often limits the performance of satellite communication systems with multicarriers. The PIM interference has a peculiarity of timevarying and non-Markov. While the existing digital signal processing methods have limited effects, we propose a novel adaptive real-time recursion learning neural network (RTRLNN) which is suitable for dynamic PIM in satellite communications. The proposed novel RTRLNN method has fast convergence with its adaptive learning rate and accurate approximation ability. In this paper, a cancellation system with RTRLNN algorithm is designed for the PIM interference in satellite communications. The system has two processing sections which are pilot slot and data transmission slot. The system extracts the feature of PIM interference and trains itself in the pilot slot while achieves cancellation of PIM interference in the data transmission slot. Simulation results are presented on time and frequency domain illustrating the effectiveness of PIM interference cancellation. Compared with the modified least mean square(LMS) method, the proposed novel RTRLNN method significantly decreases the bit error rate(BER) of PIM interference. Furthermore, the proposed novel RTRLNN method shows an enhancement of 10dB in SIR gain while the Eb/N0 fixed 10dB.
Date of Conference: 25-29 June 2018
Date Added to IEEE Xplore: 30 August 2018
ISBN Information:
Electronic ISSN: 2376-6506