Nonlinear digital self-interference cancellation with SVR for full duplex communication

Official URL: http://dx.doi.org/10.1109/WCNC45663.2020.9120721

Full duplex (FD) communication has attracted significant attention due to its potential for increasing the wireless link rate twofold without increasing the occupied bandwidth. For enabling FD communication, the self-interference (SI) signal at the transmitting radio should be suppressed down to the noise level. Despite SI cancellation applied at different stages via passive, analog and digital techniques, the current methods cannot sufficiently suppress SI at all power levels. Specifically at high power levels, the nonlinear behavior of the radio should be modeled within SI cancellation. In this paper, we propose a novel nonlinear digital cancellation approach by adapting support vector regression (SVR) for FD communication. The proposed SVR based nonlinear cancellation is integrated with linear cancellation and the digital SI cancellation algorithms are implemented and tested on a software defined radio set-up integrated with a monostatic antenna. With the proposed SVR based solution, up to 5 dB enhancement in total SI suppression is observed as compared to only linear digital cancellation, for the transmit power levels higher than 20 dBm. Moreover, for the same transmit power levels, up to 3 dB higher cancellation is achieved in comparison to the memory polynomial based nonlinear digital cancellation. Incorporating the proposed solution in the FD radio design only requires changes at the algorithmic level, which is implemented in software, hence there is no need for any hardware or circuitry modification. Additionally, the proposed nonlinear solution does not cause any extra communication overhead, since SVR models are to be learned only once for each transmit power level, then stored and re-used for the later transmissions.