- The paper demonstrates that using both the original and complex-conjugate signals in widely-linear models effectively cancels SI caused by IQ imbalance and PA nonlinearity.
- The method applies efficient least-squares parameter estimation to compute optimal cancellation coefficients, outperforming traditional linear approaches.
- Simulation results validate significant improvements in SI suppression, suggesting potential for more compact, cost-efficient full-duplex transceiver designs.
Widely-Linear Digital Self-Interference Cancellation in Direct-Conversion Full-Duplex Transceivers
The field of full-duplex (FD) radio communication is continuously expanding to enhance radio frequency (RF) spectrum efficiency. One major challenge that persists in the deployment of FD transceivers is the cancellation of self-interference (SI). In this paper, the authors address significant impairments that occur in direct-conversion FD transceivers, namely transmitter power amplifier (PA) nonlinear distortion and the imbalanced operation of transmitter and receiver IQ mixers, and propose a novel widely-linear digital self-interference cancellation method.
The paper begins by highlighting RF imperfections that impose constraints on classical linear SI cancellation methods, demonstrating that the SI waveform stemming from the transmitter and receiver IQ imaging calls for widely-linear processing. Widely-linear models leverage both the original and complex-conjugate transmit data, thereby addressing the SI more effectively than purely linear models which only exploit the original data. The cancellation of these widely-linear SI components necessitates a new digital baseband signal processing strategy.
The authors propose a widely-linear digital SI canceller developed to jointly suppress both the linear and conjugate components stemming from the SI signal. The method involves the application of a widely-linear transformation on the original and complex-conjugate transmit signals to form an estimation of the SI signal, thereby capitalizing on both signal and image components of the self-interference. By integrating efficient least-squares parameter estimation schemes, the technique ensures that the cancellation parameters of this new widely-linear structure are accurately estimated.
Highlighted in the simulations are clear numerical advantages. The widely-linear digital SI cancellation technique is shown to outperform traditional linear cancellation approaches significantly, achieving better SI suppression even in the presence of practical RF imperfections such as IQ imaging and PA nonlinearity. This performance gain is more pronounced at increased transmit powers, where nonlinear distortions are typically more challenging to mitigate. For a typical low-cost mobile setup with mass-market RF components, the additional IQ imaging leads to significant SI at the receiver path, necessitating consideration of these components for accurate SI cancellation.
Simulation results validate the effectiveness of the proposed method. With SI waveform suppression improving considerably when using the widely-linear canceller in varied RF environments, the paper concludes that such techniques can effectively compensate for practical IQ imbalance levels in FD transceivers, thereby enabling enhanced communication through this improved interference management.
From a practical perspective, implementing widely-linear digital SI cancellation holds implications for design and deployment of FD transceivers, indicating a potential reduction in the need for extensive RF isolation and analog SI cancellation hardware. This approach can contribute to more compact and cost-efficient RF systems. Theoretically, it enriches the understanding of SI cancellation by emphasizing the necessity of nonlinear and widely-linear modeling in modern communication systems subject to RF distortions.
Future work is set to explore joint augmentation of the widely-linear framework to tackle nonlinear SI from PA together with the linear and conjugate signal components, deepening research into interference cancellation processes in cognitive radio networks and full-duplex communications at large.