Nowadays, wireless communication techniques, such as WiFi, Bluetooth low energy (BLE), etc., have been pervasive in our daily lives, and not only provide convenient data transmission services, but also enable popular indoor positioning and navigation services. The placement of wireless infrastructures like WiFi access points (APs) and BLE beacons have significant influences on the performance of localization. More importantly, since APs and beacons are probably used for both network access and localization, it is necessary to take into account both coverage and localization when deploying APs and beacons. In addition, there still exist other critical challenges, including optimizing AP and beacon placement in WiFi and BLE hybrid localization and optimizing the placement of extra APs and/or beacons in an existing wireless network, which are essentially NP-complete. This paper tackles these problems of optimizing AP and beacon placement by proposing a heuristic differential evolution algorithm based on the widely used Cramer-Rao lower bound (CRLB). To be specific, the CRLB is leveraged as a metric for localization and meanwhile a coverage degree criterion is defined as a metric for coverage, both of which are incorporated into the evaluation function of the differential evolution algorithm. Furthermore, instead of using the ideal log distance path loss (LDPL) model, the more practical Motley-Keenan model is adopted to reflect the influences of obstacles that are widespread in indoor environments. On these grounds, a software is designed and implemented based on Geotools to optimize AP and beacon placement in an interactive GUI manner. Finally, extensive simulations and field experiments are conducted, and a thorough comparison confirms the efficiency and effectiveness of the proposed algorithm.

如今，诸如WiFi，低功耗蓝牙（BLE）等无线通信技术已广泛渗透到我们的日常生活中，不仅提供便捷的数据传输服务，还使流行的室内定位和导航服务成为可能。无线基础设施（如WiFi接入点（AP）和BLE信标）的位置对本地化性能有重大影响。更重要的是，由于AP和信标可能同时用于网络访问和本地化，因此在部署AP和信标时必须同时考虑覆盖范围和本地化。此外，仍然存在其他关键挑战，包括优化WiFi和BLE混合定位中的AP和信标放置以及优化现有无线网络中额外AP和/或信标的放置，基本上是NP完全的。通过提出一种基于广泛使用的Cramer-Rao下界（CRLB）的启发式差分进化算法，本文解决了优化AP和信标放置的这些问题。具体地，CRLB被用作用于定位的度量，同时覆盖度标准被定义为用于覆盖的度量，这两者都被结合到差分进化算法的评估函数中。此外，不是使用理想的对数距离路径损耗（LDPL）模型，而是采用了更实用的Motley-Keenan模型来反映在室内环境中普遍存在的障碍物的影响。基于这些理由，基于Geotools设计和实现了一种软件，以交互GUI的方式优化AP和信标放置。最后，