认知无线电频谱感知技术的理论边界与突破方向 -通信工程专业

摘要

认知无线电频谱感知技术作为解决频谱资源短缺问题的关键手段，近年来受到广泛关注。本文在研究背景方面，从频谱资源日益紧张的现状出发，分析了传统固定频谱分配方式的局限性，明确了动态频谱接入对提升频谱利用率的重要性。本文采用数学建模与仿真分析相结合的方法，深入探讨了能量检测、匹配滤波和协作感知等主流感知技术的性能极限及其适用场景。同时，结合机器学习算法，提出了基于深度学习的频谱感知新框架，以应对复杂电磁环境下的非理想条件。结果表明，在低信噪比条件下，所提方法较传统技术显著提升了检测精度和鲁棒性。通过理论推导验证了频谱感知性能与系统参数之间的量化关系，为优化感知策略提供了理论依据。

关键词：认知无线电；频谱感知；深度学习；能量检测；协作感知

Theoretical Boundaries and Breakthrough Directions of Spectrum Sensing Techniques in Cognitive Radio

英文人名

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Abstract

Cognitive radio spectrum sensing technology, as a key means to solve the problem of spectrum resource shortage, has been widely concerned in recent years. In terms of research background, this paper analyzes the limitations of traditional fixed spectrum allocation based on the increasingly tight spectrum resources, and clarifies the importance of dynamic spectrum access to improve spectrum utilization. In this paper, the performance limits and application scenarios of mainstream sensing technologies such as energy detection, matching filter and collaborative sensing are discussed by combining mathematical modeling with simulation analysis. At the same time, combined with machine learning algorithm, a new spectrum sensing fr amework based on deep learning is proposed to deal with the non-ideal conditions in complex electromagnetic environment. The results show that under the condition of low SNR, the proposed method significantly improves the detection accuracy and robustness compared with the traditional technique. The quantitative relationship between spectrum sensing performance and system parameters is verified by theoretical derivation, which provides a theoretical basis for optimizing sensing strategy.

Keywords: Cognitive Radio；Spectrum Sensing；Deep Learning；Energy Detection；Collaborative Sensing

引言 1

一、认知无线电频谱感知技术概述 1

(一)频谱感知技术的基本原理 1

(二)关键技术与应用场景分析 2

(三)当前研究的主要挑战 2

二、理论边界与性能限制分析 3

(一)频谱感知的数学模型构建 3

(二)性能边界与物理限制探讨 3

(三)干扰管理与检测概率权衡 4

三、核心算法与优化策略研究 4

(一)传统感知算法的局限性分析 4