# A Review of Wireless Positioning Techniques and Technologies: From Smart Sensors to 6G
## 3 Wireless Technologies
### Wireless Fidelity (Wi-Fi)  
The Wi-Fi, also referred to as WLAN, has experienced a rapid growth and increasing popularity over the last few decades. Its wide availability, flexibility, and mobility, with free public Wi-Fi hotspots available almost everywhere with no additional hardware requirements, made Wi-Fi one of the most popular and well-known wireless technologies today [2; 12]. This ubiquitous availability also made Wi-Fi the mainstream technology reported in the related literature for indoor localization. It operates on the 2.4 GHz and 5 GHz in the unlicensed ISM band, with up to 1 km coverage, which can be extended through hotspots. Although it was initially intended for computer-to-computer interconnection, nowadays it provides Internet connectivity at broadband speeds. It is based on the IEEE 802.11 standard, which specifies the set of MAC and physical layer (PHY) protocols for implementing WLAN communication, as well as the compatible interconnection of data communication, using the carrier sense multiple access protocol with collision avoidance (CSMA/CA). Numerous amendments, such as 802.11 g and 802.11 n, have been introduced, which mainly define the frequency band, bandwidth, and transmission rates. Although it is capable of operating in NLoS and not sensitive to lighting conditions, it suffers from high power consumption, compared to other WLAN technologies. The RSS measurements are the most commonly used measurements for localization, and they are affected by the free-space loss and large-scale attenuation caused by obstacles, even for small wavelengths, i.e., \(\lambda\) = 12.5 cm [95]. While, the time-based measurements are less commonly used due to the complexity of measuring the time delays and angular information [20]. Moreover, fingerprinting is the most commonly used localization technique, due to its wide availability and ability for building self-constructed databases. For instance, the \"Locate me\" [96] contains databases that are calibrated by adding users' personal places and mobile calls. It combines the Wi-Fi and GPS technologies for providing an indoor/outdoor localization system. The algorithm requires at least three Wi-Fi APs, which are matched with the location database, and the output is provided on a website to be used by the users. Moreover, \"Chronos\" [97] utilizes a single Wi-Fi AP and combines the information across different Wi-Fi channels for achieving fine grain resolution, similar to UWB. Another Wi-Fi localization approach is by \"network sniffing\", with the utilization of the packet information, such as the probe requests and probe responses. More specifically, the packets exchanged during discovery, i.e., while a receiving node (station) is searching for the available transmitting nodes (APs) within its range, contain probe requests from the station to the APs, and probe responses from the APs to the station. The additional information exchanged include the device's unique MAC address and timestamp. This method can only be used with older smart devices, since the newly released operating systems (OS) adapted the randomized MAC addresses feature; therefore, the tracking and localization is more difficult and sometimes impossible. Nevertheless, this technique was also used maliciously for stealing sensitive information, such as passwords. The \"HuMAn\" system [98] utilized the network sniffing method by combining the RSS measurements, together with the fingerprinting localization technique. The RSS measurements were collected and processed for training, aiming to make localization predictions. Furthermore, some Wi-Fi amendments support the FTM protocol, which provides fine-time measurements, so time-based, i.e., RTT measurements, localization techniques can be used. For example, in [99], the FTM protocol measurements and the trilateration technique are used. Although the system achieved meter-level accuracy, it was significantly affected by the NLoS conditions.