标题： 基于众包数据的移动覆盖分析 显示英文标题

标题： Mobile Coverage Analysis using Crowdsourced Data

摘要： 有效评估移动网络覆盖范围并精确识别服务薄弱区域对于致力于提升用户体验（QoE）的网络运营商至关重要。 本文提出了一种利用众包QoE数据进行移动覆盖和薄弱区域分析的新框架。 我们方法的核心在于在单个基站（天线）层面进行覆盖分析，随后使用实证地理定位数据将其汇总到站点层面。 本研究的一个关键贡献是应用了单类支持向量机（OC-SVM）算法来计算移动网络覆盖范围。 这种方法将决策超平面建模为有效覆盖轮廓，从而实现对单个基站和整个站点覆盖区域的稳健计算。 同样的方法被扩展用于分析众包的服务损失报告，从而识别和量化地理上局部的薄弱区域。 我们的研究结果表明，这种新框架在准确绘制移动覆盖范围方面效果显著，并且特别在复杂的城市环境中突出显示了信号不足的细粒度区域。 显示英文摘要

摘要： Effective assessment of mobile network coverage and the precise identification of service weak spots are paramount for network operators striving to enhance user Quality of Experience (QoE). This paper presents a novel framework for mobile coverage and weak spot analysis utilising crowdsourced QoE data. The core of our methodology involves coverage analysis at the individual cell (antenna) level, subsequently aggregated to the site level, using empirical geolocation data. A key contribution of this research is the application of One-Class Support Vector Machine (OC-SVM) algorithm for calculating mobile network coverage. This approach models the decision hyperplane as the effective coverage contour, facilitating robust calculation of coverage areas for individual cells and entire sites. The same methodology is extended to analyse crowdsourced service loss reports, thereby identifying and quantifying geographically localised weak spots. Our findings demonstrate the efficacy of this novel framework in accurately mapping mobile coverage and, crucially, in highlighting granular areas of signal deficiency, particularly within complex urban environments.