Improving Digital Interference Cancellation in LTE-A/5G-Transceivers by Statistical Modeling

Mobile communication radio frequency transceivers can suffer from self-interference problems which degrade performance in carrier aggregation operation. Digital interference mitigation is a measure studied in literature to overcome this issue. However, preferred low-cost algorithms, like the least-mean squares (LMS) filter have difficulties with the adaptation performance due to the involved Long-Term Evolution signal statistics. In this work, we derive analytical expressions for the relevant statistical properties and present a novel algorithm which improves the adaptation speed over the classical LMS filter while maintaining a feasible computational complexity. The effectiveness of the new algorithm compared to state-of-the-art methods is demonstrated by means of simulations.