# Measurement and Analysis of RSS Using Bluetooth Mesh Network for Localization Applications
## 2 Related Works  
In the past two decades, there have been tremendous efforts in research and development of wireless localization solutions due to proliferation of various mobile computing devices and ever-increasing demand for location-based services in indoor and urban environments where GPS could not provide sufficient coverage and accuracy. Many existing solutions depend on measurement of radio signal RSS, which is mainly due to the fact that RSS measurements are readily available on most of the commercial off-the-shelf wireless devices. Comprehensive surveys of localization techniques are available in many references such as [9; 10; 11; 12; 13]. Several closely related papers are reviewed briefly in the following.  
The paper [5] presented a study of location fingerprinting method using BLE beacons. Location fingerprinting does not depend on the modeling of radio propagation channels, but it requires extensive site surveys to construct the database of location signatures in the form of the RSS of available BLE beacon signals. The authors demonstrated through measurement and analysis that the use of three widely spaced but narrowband advertising channels leads to severe RSS variations if the channel number is not available. To mitigate multipath fading effects, the authors applied frame-based processing on a sequence of RSS measurements that are collected over a window of time. The authors studied the effects of beacon density, transmit power, and transmit frequency on the performance of location fingerprinting methods. The authors also presented a detailed analysis of the advantages and disadvantages of BLE and Wi-Fi for localization applications.  
The paper [14] presents RSS measurement results and path loss models in four different environments. Three BLE advertisement channels are modelled separately and the interfering effects are explained using channel spectrum masks of the Wi-Fi and BLE systems. It is concluded that the BLE channel 39 has the least possible amount of interference from Wi-Fi because it has the least amount of overlap with Wi-Fi channels. The paper [15]presents a BLE-based indoor positioning system that takes advantage of frequency diversity offered by three BLE advertisement channels. Given three RSS measurement data received in a quick succession from three advertisement channels, three diversity combining schemes are used in the paper, including max, mean, and maximum ratio combining (MRC). Effects of the combining schemes are compared using measurement data. Paper [16] presents an indoor positioning method that depends on deriving a path loss model for each of the three advertisement channels. It is shown that linear regression over one single channels results in smaller residue variance, which in turn can effectively improve positioning performance.  
The paper [17] demonstrates that averaging RSS measurements over multiple RF channels can significantly reduce random variations in the data, which can improve the RSS-based ranging accuracy. Such a multichannel averaging approach effectively exploits frequency diversity in the data to counter the effects of small-scale multipath fading. IEEE 802.15.4 transceivers are used to experimentally validate the performance. It is also shown that averaging over 6 channels has comparable performance as with 16 channels. The paper [18] presents measurement and modeling results of Wi-Fi signal path loss models in several office environments. The chi-square goodness-of-fit test is used to validate the normality assumption of the path loss and shadowing models. Empirical results are also compared with a deterministic two-ray model. It is concluded that the log-distance path loss and log-normal shadowing models fit well with the measurement data.