# User-BS Selection Strategy Optimization with RSSI-Based Reliability in 5G Wireless Networks
## 2 Related Work
### RSSI-Based Optimization Model  
In wireless communication networks, signal quality is an important indicator that affects communication reliability, and received signal strength (RSS) is its most important part. The majority of existing work for RSS focused on large-scale cooperative sensor network localization subject to communication constraints. To the best of our knowledge, RSS was first considered for cooperative localization in [25], where a single RSS was optimized so as to limit the number of neighboring sensors. In a recent work [26], RSS was considered for noncooperative infrastructure-based indoor positioning. However, the focus of the above study lay on the overall positioning performance in a given service area and thorough treatment on the measurement campaign, RSS modeling, model fitting and parameter calibration, signaling, and performance evaluation using real data measured from a live network.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{Metrics} & \multicolumn{2}{c}{Spectral efficiency} & [17] \\ \cline{2-3}  & Energy efficiency & [18; 19] \\ \cline{2-3}  & QoS & [20] \\ \hline \multirow{3}{*}{Models} & Game theory & [22] \\ \cline{2-3}  & Combinatorial optimization & [23] \\ \cline{2-3}  & Random geometry & [24] \\ \hline \hline \end{tabular}
\end{table}
Table 1: Common metrics and models for user-BS selection strategy problems.  
In order to measure RSS, we have RSSI, an optional part of the transmission layer, which is one of the most important indicators used to determine the link quality and whether to increase the broadcast transmission strength [27]. PredominatingRSSI models can be divided into three types: the spatial-propagation, ShadowWing, and distance-loss models. Considering the influence of complex factors such as reflection, blocking, and diffraction, the distance-loss model is more capable of reflecting the actual application environment and the closest to the true value of the distance [28].  
RSSI indicates the strength of the received wireless signal, which is easily affected by the environment and has unstable characteristics. Its value gradually decreases as the distance between the terminal and the access point increases. The larger the RSSI is, the higher the signal reception strength and the better the data transmission channel are. On the other hand, the lower the RSSI is, the weaker the received signal and the worse the quality of the physical channel for data transmission are, and the probability of packet loss and bit errors during data transmission obviously increases.  
RSSI calculates propagation loss by measuring the transmission power and the received power, and then uses the signal attenuation model to convert propagation loss into transmission node distance [29]. This is a low-power, low-cost ranging technology with the characteristics of low cost, less equipment, long distance, and easy access.  
Due to the above advantages, RSSI is often used to solve optimization problems in wireless communication. In [30] RSSI was used to resolve the optimization problem of Bluetooth low-energy (BLE) beacon density, and the authors in [31] used RSSI to help in person tracking and monitoring in industrial environments. However, most of the existing RSSI-based optimization models mainly focused on indoor localization and rarely applied it to other scenarios.  
In this paper, we define the overall reliability of the wireless network by the RSSI, which can easily be obtained in the real-world scenario, together with the failure probability of the BS, and model the problem as a selection strategy optimization problem with reliability as the optimization goal.