# A Review of Wireless Positioning Techniques and Technologies: From Smart Sensors to 6G
## 2 Localization Techniques
### Round Trip Time (RTT)
#### 2.1.3 Channel-Based Measurements  
The channel-based measurements include the link quality indicator (LQI), received signal strength (RSS), and the channel state information (CSI). The LQI is used for evaluating the link quality and the RSS is the actual signal power strength measured at the receiving node. The CSI is an advanced ranging technique used to provide accurate received signal parameters over the entire signal bandwidth [27]. Link Quality Indicator (LQI)  
The LQI is a metric of the link quality by measuring the error in the received signal, introduced in the IEEE 802.15.4 (ZigBee), which measures the error in the incoming modulation of the successfully received packets. It is a quality indicator included in all received packets expressed in a range from 0 to 255 that can be used to estimate distance. It can also be used as an assistant indicator of RSS, since it provides a correlation with packet loss (good link quality indicator) [38]. Furthermore, in [39], the LQI was used in an attempt of improving the AoA estimation using the RSSI parameter, with no positive results. Received Signal Strength (RSS)  
RSS indicates the actual power strength measured at the receiving node and is usually provided in decibel milliwatts (dBm) or milliWatts (mW). It is commonly referred as the received signal strength indicator (RSSI) and is usually defined by the chip vendors [6] in a range from 0 to 255. It can be used as an indicator of the distance (link's strength indicator), while each vendor can define its own maximum value. It provides an understanding of location-dependent RSS patterns and underlying location features. The RSS, however, can only provide information about the strength of the signal, while more fine-grained physical layer information can be obtained from the CSI [40]. The RSS measurements are supported by most transceivers, due to their simplicity, and thus, can easily scale to larger areas and multiple users. The distance between the transmitting and receiving nodes is estimated by the signal attenuation of the emitted signal strength by calculating the signal path loss. The path loss is the reduction in power density of an electromagnetic wave as it propagates through space, caused by numerous effects, such as refraction and reflection, as well as the environment and propagation medium. Since the free space propagation model cannot be used for real environments, various distance path loss models are used for estimating the distance. The signal strength is inversely proportional to the distance \(d\) and can be estimated by the following formula:  
\[P(d)[dBm]=P(d_{0})[dBm]-10n\log\left(\frac{d}{d_{0}}\right), \tag{7}\]  
where \(n\) is the path loss attenuation factor, \(P(d_{0})\) is the signal power at some reference distance \(d_{0}\), measured in dBm, and \(d\) is the distance between the transmitting and receiving nodes. These parameters are usually obtained using statistical evaluation methods based on the collection of field measurements of RSS at predefined positions with known distances to the transmitting nodes. Commonly, the effect of distance on RSS can be measured by the packet success rate provided by the radio. For instance, the RADAR system [41] utilizes the wall attenuation factor (WAF) propagation model (7) for indoors, which includes an attenuation factor for building floors and considers the effects of obstacles, such as walls. Although RSS is one of the simplest and most widely used metrics, its accuracy is heavily affected by the existence of obstacles and multipath propagation. In [42], real-environment experiments were carried out using smartphones for sensing RSS at various rain rates. The data from the weather stations, including four databases of dry climate and various rain rate conditions, were used for the evaluation. The results confirmed the impact of rain on RSS and that the rain attenuation should be taken into consideration for estimating the distance based on RSS.