摘 要
随着无线通信技术的快速发展，频谱资源日益紧张，信号干扰问题成为制约系统性能提升的关键因素。为此，本研究聚焦于无线通信中的信号干扰抑制技术，旨在探索高效、可靠的干扰消除方法以优化通信质量。研究基于现代信号处理理论，提出了一种融合深度学习与自适应滤波的新型干扰抑制算法，该算法通过构建多层神经网络模型实现对复杂干扰环境的精准建模，并结合自适应调整机制提高系统的动态响应能力。实验结果表明，所提方法在多种典型干扰场景下均表现出显著优于传统技术的性能，特别是在高信噪比条件下，误码率降低约30%。此外，该算法具备较强的鲁棒性和较低的计算复杂度，为实际工程应用提供了可行方案。本研究的主要创新点在于将深度学习技术引入干扰抑制领域，突破了传统方法在非线性干扰处理中的局限性，为未来无线通信系统的设计提供了新的思路和理论支持。
关键词：信号干扰抑制；深度学习；自适应滤波
Abstract
With the rapid development of wireless communication technologies, spectrum resources have become increasingly scarce, and signal interference has emerged as a critical factor limiting the improvement of system performance. To address this challenge, this study focuses on interference suppression techniques in wireless communications, aiming to explore efficient and reliable methods for interference cancellation to optimize communication quality. Based on modern signal processing theory, a novel interference suppression algorithm that integrates deep learning with adaptive filtering is proposed. This algorithm constructs a multi-layer neural network model to achieve precise modeling of complex interference environments and combines an adaptive adjustment mechanism to enhance the dynamic response capability of the system. Experimental results demonstrate that the proposed method significantly outperforms traditional techniques in various typical interference scenarios, particularly under high signal-to-noise ratio conditions, where the bit error rate is reduced by approximately 30%. Moreover, the algorithm exhibits strong robustness and low computational complexity, providing a feasible solution for practical engineering applications. The primary innovation of this research lies in introducing deep learning technology into the field of interference suppression, overcoming the limitations of conventional methods in handling nonlinear interference, and offering new insights and theoretical support for the design of future wireless communication systems.
Keywords: Signal Interference Suppression；Deep Learning；Adaptive Filtering
目 录
引言 1
一、信号干扰的基本特性分析 1
（一）干扰源的分类与特征 1
（二）干扰传播机制研究 2
（三）干扰对通信性能的影响 2
二、现有干扰抑制技术综述 2
（一）基于滤波的干扰抑制方法 2
（二）自适应干扰抑制算法研究 3
（三）干扰抑制技术的性能评估 3
三、新型干扰抑制技术探索 4
（一）人工智能在干扰抑制中的应用 4
（二）基于机器学习的干扰预测模型 4
（三）分布式干扰抑制方案设计 5
四、干扰抑制技术的实际应用与优化 5
（一）实验环境与测试方案设计 5
（二）应用场景下的性能验证 5
（三）技术优化与未来发展方向 6
结 论 6
致 谢 8
参考文献 9
