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Related Experiment Video

Updated: Jun 27, 2025

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements
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Digital Self-Interference Canceler with Joint Channel Estimator for Simultaneous Transmit and Receive System.

Shiyu Song1, Yanqun Tang1, Xianjie Lu1

  • 1School of Electronics and Communication Engineering, Sun Yat-sen University, Shenzhen 518107, China.

Sensors (Basel, Switzerland)
|April 27, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces adaptive algorithms for self-interference cancellation (SIC) in simultaneous transmit and receive wireless systems. These methods improve channel estimation and reduce bit error rates, enhancing spectral efficiency.

Keywords:
adaptive filteringdigital cancellationjoint channel estimatorself-interference cancellationsimultaneous transmit and receive

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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.