Research on Non-cooperative Interference Suppression Technology for Dual Antennas without Channel Prior Information

YAN Cheng; LI Tong; PAN Wensheng; DUAN Baiyu; SHAO Shihai

doi:10.11999/JEIT250378

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YAN Cheng, LI Tong, PAN Wensheng, DUAN Baiyu, SHAO Shihai. Research on Non-cooperative Interference Suppression Technology for Dual Antennas without Channel Prior Information[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250378

Citation:

YAN Cheng, LI Tong, PAN Wensheng, DUAN Baiyu, SHAO Shihai. Research on Non-cooperative Interference Suppression Technology for Dual Antennas without Channel Prior Information[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250378

Citation:

YAN Cheng, LI Tong, PAN Wensheng, DUAN Baiyu, SHAO Shihai. Research on Non-cooperative Interference Suppression Technology for Dual Antennas without Channel Prior Information[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250378

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Research on Non-cooperative Interference Suppression Technology for Dual Antennas without Channel Prior Information

doi: 10.11999/JEIT250378 cstr: 32379.14.JEIT250378

National Key Laboratory of Wireless Communications, University of Electronic Science and Technology of China, Chengdu 611731, China

Funds: Item1, Item2, Item3

Received Date: 2025-05-07
Accepted Date: 2025-11-03
Rev Recd Date: 2025-11-03

Available Online: 2025-11-13

Abstract

Abstract

Objective In electronic countermeasures, friendly communication links are highly susceptible to interference from adversaries. To suppress non-cooperative interference signals, the auxiliary antenna scheme is commonly employed to extract reference signals for interference cancellation, thereby enhancing communication quality. However, the auxiliary antenna typically receives both interference and communication signals simultaneously, which can degrade the interference suppression capability. Typical methods for non-cooperative interference suppression include interference rejection combining and spatial domain adaptive filtering. These techniques leverage the uncorrelated nature of the interference and desired signals to achieve non-cooperative interference suppression. They also require channel information and interference noise information to support the suppression process, which can limit their applicability in certain scenarios. Methods This paper proposes the Fast ICA-based Simulated Annealing Algorithm for SINR Maximization (FSA) to address non-cooperative interference suppression in communication systems. Designed for scenarios where prior channel information is unavailable, FSA employs a weighted reconstruction cancellation technique implemented through a Finite Impulse Response (FIR) filter structure. The method operates in a dual-antenna system where one antenna handles communication while the other serves as an auxiliary antenna for interference reference. The core innovation lies in optimizing the weighted reconstruction coefficients using the Simulated Annealing algorithm while employing Fast Independent Component Analysis (Fast ICA) for SINR estimation. The FIR filter reconstructs interference from the auxiliary antenna signal using these optimized coefficients, then subtracts the reconstructed interference from the main received signal to enhance communication quality. Accurate SINR estimation in non-cooperative environments presents significant challenges due to mixed signal components. FSA addresses this through blind source separation principles inspired by Fast ICA, extracting sample signals of both communication and interference components. The SINR is calculated based on cross-correlation results between these separated signals and the signals after interference suppression. The Simulated Annealing algorithm serves as a probabilistic optimization technique that iteratively adjusts reconstruction coefficients to maximize output SINR. Starting with initial coefficients, the algorithm perturbs them while evaluating resulting SINR improvements. Using the Monte Carlo criterion, it accepts or rejects perturbations, enabling escape from local optima and convergence toward global optimum solutions. This continuous optimization cycle identifies optimal filter coefficients within the search range to maximize SINR performance. The integrated approach of FSA enables effective interference suppression without requiring prior channel knowledge. By combining Fast ICA's blind estimation capabilities with Simulated Annealing's robust optimization, the method achieves reliable performance in dynamic interference environments. The FIR-based implementation provides a practical framework for real-time interference cancellation, making FSA particularly suitable for electronic countermeasure applications where channel conditions are unknown and rapidly changing. This methodology represents a significant advancement over conventional techniques that depend on channel state information, offering improved adaptability in non-cooperative scenarios while maintaining computational efficiency through the synergistic combination of blind source separation and intelligent optimization algorithms. Results and Discussions The performance of the proposed Fast ICA-based Simulated Annealing Algorithm for SINR Maximization (FSA) was evaluated through simulations and experiments. Results show that FSA significantly improves the output SINR under various conditions. In simulations, the method achieved up to 27.2 dB SINR improvement when the communication and auxiliary antennas had a large SINR difference and were placed farther apart (Fig. 5). However, performance degraded with increased channel correlation between the antennas. Experiments validated these findings, with an SINR improvement of 19.6 dB observed at a 2 m antenna separation (Fig. 7). The study concludes that FSA is highly effective for non-cooperative interference suppression without prior channel information, but its performance is sensitive to antenna configuration and channel correlation. Conclusions The proposed Fast ICA-based Simulated Annealing Algorithm for SINR Maximization (FSA) method provides an effective solution for non-cooperative interference suppression in communication systems. The method leverages weighted reconstruction cancellation, optimized by the Simulated Annealing algorithm, and Fast ICA-based SINR estimation to achieve significant improvements in communication quality without requiring prior channel information. The results from both simulations and experiments demonstrate the method's effectiveness across a range of conditions, highlighting its potential for practical applications in electronic warfare environments. The study concludes that the performance of the FSA method is highly dependent on the SINR difference and channel correlation between the communication and auxiliary antennas. Future research will focus on optimizing the algorithm for more complex scenarios and exploring the impact of various system parameters on its performance. The findings of this research contribute to the development of robust communication systems capable of operating effectively in challenging interference environments.
- Non-cooperative interference,
- Interference suppression,
- Electronic countermeasures,
- Auxiliary antenna

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References(16)

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