摘 要
随着无线通信技术的快速发展，高密度场景下的无线网络部署面临前所未有的挑战，尤其是在用户数量激增、带宽需求不断攀升的情况下，传统Wi-Fi技术已难以满足实际需求。为此，本文以Wi-Fi 6技术为核心，深入研究了其在高密度无线网络环境中的部署与优化策略。研究旨在通过分析Wi-Fi 6的关键特性，如OFDMA、MU-MIMO以及更高阶的调制技术，提出一种适用于复杂场景的网络优化框架。具体方法包括基于流量特征的信道分配算法设计、干扰管理机制改进以及动态负载均衡策略的实现。通过对典型高密度场景（如体育馆、机场和校园）的实际测试，结果表明所提出的优化方案能够显著提升网络吞吐量，降低延迟，并有效缓解拥塞问题。此外，本文创新性地引入了机器学习算法对网络性能进行预测与调整，从而实现了更智能化的资源分配。最终结论显示，基于Wi-Fi 6的优化部署不仅大幅提升了用户体验，还为未来高密度无线网络的设计提供了重要参考。本研究的主要贡献在于提出了融合多维度优化策略的技术框架，并验证了其在实际应用中的可行性和优越性，为推动下一代无线网络技术的发展奠定了基础。
关键词：Wi-Fi 6；高密度无线网络；OFDMA；MU-MIMO；机器学习优化
Abstract
With the rapid development of wireless communication technologies, the deployment of wireless networks in high-density scenarios is facing unprecedented challenges. In particular, the exponential growth in user numbers and the escalating demand for bandwidth have rendered traditional Wi-Fi technologies insufficient to meet practical requirements. To address this issue, this study focuses on Wi-Fi 6 technology and conducts an in-depth investigation into its deployment and optimization strategies within high-density wireless network environments. By analyzing the key features of Wi-Fi 6, such as OFDMA, MU-MIMO, and higher-order modulation techniques, a network optimization fr amework adaptable to complex scenarios is proposed. The specific methodologies include the design of channel allocation algorithms based on traffic characteristics, the enhancement of interference management mechanisms, and the implementation of dynamic load balancing strategies. Through practical tests conducted in typical high-density scenarios, such as stadiums, airports, and campuses, the results demonstrate that the proposed optimization approach significantly improves network throughput, reduces latency, and effectively alleviates congestion problems. Furthermore, this study innovatively incorporates machine learning algorithms for predicting and adjusting network performance, thereby achieving more intelligent resource allocation. The final conclusions indicate that the optimized deployment based on Wi-Fi 6 not only substantially enhances user experience but also provides critical references for the design of future high-density wireless networks. The primary contribution of this research lies in the proposal of a technical fr amework integrating multi-dimensional optimization strategies, whose feasibility and superiority in real-world applications have been validated, thus laying a solid foundation for the advancement of next-generation wireless network technologies.
Keywords: Wi-Fi 6; High Density Wireless Network; Ofdma; Mu-Mimo; Machine Learning Optimization
目 录
1绪论 1
1.1基于Wi-Fi 6高密度网络的研究背景 1
1.2高密度无线网络部署的意义与价值 1
1.3国内外研究现状与技术发展 1
1.4本文研究方法与技术路线 2
2Wi-Fi 6关键技术及其应用分析 2
2.1Wi-Fi 6的核心技术特点 2
2.2OFDMA在高密度场景中的作用 3
2.3MU-MIMO对网络性能的提升 3
2.4TWT机制与能耗优化研究 4
2.5Wi-Fi 6与其他技术的对比分析 4
3高密度无线网络部署策略研究 5
3.1高密度场景需求分析与挑战 5
3.2网络规划与AP布局优化方法 5
3.3频谱分配与干扰管理策略 6
3.4容量估算与带宽分配模型 6
3.5实际案例分析与部署经验总结 7
4高密度无线网络性能优化研究 7
4.1性能优化的关键指标体系 7
4.2动态信道调整与负载均衡算法 8
4.3数据传输效率的优化方案 8
4.4用户体验质量（QoE）提升策略 9
4.5安全性与稳定性保障措施 9
结论 10
参考文献 11
致 谢 12
