Digital Self-Interference Canceler with Joint Channel Estimator for Simultaneous Transmit and Receive System

Area of Science:

• Wireless Communications
• Signal Processing

Background:

• Simultaneous transmit and receive (STAR) wireless systems offer doubled spectral efficiency but require effective self-interference (SI) mitigation.
• Accurate estimation of both SI and remote transmission (RT) channels is crucial for signal equalization.

Purpose of the Study:

• To propose novel adaptive algorithms for linear and nonlinear self-interference cancellation (SIC).
• To enhance STAR system performance by jointly estimating channels and performing SIC.
• To improve algorithm robustness against impulsive noise.

Main Methods:

• Development of two adaptive algorithms based on a multi-layered joint channel estimator structure.
• Implementation of an M-estimate function for enhanced robustness.
• Introduction of a generalized Hammerstein polynomial basis function for nonlinear SIC.

Main Results:

• The proposed algorithms effectively estimate the RT channel during SIC.
• Improved performance observed across a range of interference-to-signal ratios.
• The nonlinear SIC algorithm demonstrated superior convergence speed and lower normalized mean squared difference compared to existing methods.
• Reduced system bit error rate achieved with the proposed approach.

Conclusions:

• The developed multi-layered joint channel estimation structure and adaptive algorithms significantly improve SIC performance in STAR systems.
• The M-estimate function provides robustness against impulsive noise.
• The nonlinear SIC algorithm offers a more efficient and effective solution for advanced wireless communication systems.