# Hybrid Approach for Indoor Localization Using Received Signal Strength of Dual-Band Wi-Fi
## 2 Related Works  
For indoor environments, in which it is difficult to use GNSS, there have been studies that have used various alternative systems to find the locations of devices. There are infrastructure-less methods that avoid dependence on a specific infrastructure by measuring a passive signal with a magnetometer, an inertial sensor, a microphone, or a light sensor [11; 12; 13; 14]. On the other hand, some localization methods depend on the infrastructure, which takes over the role of the satellites in the GNSS. Some studies used an ultra-wide-band tag [15], Bluetooth beacon [16; 17], or radio frequency identification tag [18]. Because these methods have weaker signal strength and smaller coverage than Wi-Fi systems in indoor environment with many walls. In addition, they require a deployment of the infrastructure. Although localization methods that use Wi-Fi also require the placement of Wi-Fi APs, many Wi-Fi APs are already currently deployed. Therefore, localization methods that use Wi-Fi have the advantage of being used without the installation of additional infrastructure compared to other infrastructure-based methods. Especially for smartphones, studies combining Wi-Fi and the other infrastructure-less methods have been conducted. Several state-of-art approaches used a fine timing measurement (FTM) protocol supported by a Wi-Fi system, which is a method of using a measurement of the distance based on the round-trip time by exchanging packets when both the AP and the device support the FTM protocol [19]. In particular, such approaches showed high ranging accuracy under LOS conditions [20; 21], and these studies using a fusion of FTM and other sensors showed high accuracy in tracking the path of a pedestrian [22; 23; 24]. To reduce the dependency on infrastructure as much as possible, there are methods that use the RSS of a Wi-Fi beacon's signal. Wi-Fi RSS depends on the indoor wave propagation characteristics, and especially the path-loss properties with respect to the distance. Many studies have been conducted on indoor path loss, which has been integrated into statistical models [6; 25; 26]. The ITU-1238 model in [25] assumes the PLM in the indoor environment as a 1-slope model, and presents path loss parameters for several open space and NLOS environments. The models introduced in [6; 26] are based on 2-slope model, considering the complex indoor environment. However, these channel models were used to analyze the quality of service in communication. Range-based localization requires site-specific channel information. In particular, a detailed model of the shadowing effect caused by walls is necessary. In [27], the propagation loss for a common building material in the 2.4 and 5.2 GHz bands was analyzed. In [28], the effects of walls on the propagation loss in complex indoor environments were analyzed, and an effective wall loss model was proposed. Meanwhile, most indoor localization studies that use RSS rely on a fingerprint-based method. Existing single-band based fingerprinting techniques [3; 29; 30; 31] demonstrate good localization accuracy, but require a thorough site survey of the target space. Channel state information (CSI) was also measured in [29; 30; 31]. Fingerprinting methods that use CSI provide high accuracy. However, there is a risk that they may not be robust to AP location changes after a site survey because CSI is sensitive to spatial configurations. In addition, CSI has a high data overhead and can only be acquired with specific devices. Some studies used dual-band RSS for fingerprint-based positioning [32; 33; 34; 35; 36; 37]. Consequently, the accuracy of these methods depends on site surveys, and vulnerable to environmental changes. In [34], rule-based localization was exploited by using dual-band RSS with consideration of NLOS conditions. The channel conditions were evaluated by comparing the RSS attenuation between the two bands, and different ranging functions were applied according to the channel conditions.