User-BS Selection Strategy Optimization with RSSI-Based Reliability in 5G Wireless Networks

Although fifth-generation (5G) wireless communication can ] support well a high data rate of transmission, issues such as base station (BS) failure and poor BS signals may cause serious interruption problems. This paper studies the user-BS selection strategy with received signal strength indication...

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Bibliographic Details
Published in:Applied sciences 2022-06, Vol.12 (12), p.6082
Main Authors: Shen, Jie, Hao, Yijun, Yang, Yuqian, Zhao, Cong
Format: Article
Language:English
Subjects:
5G mobile communication
Algorithms
Communications networks
Dynamic programming
Energy efficiency
Localization
Network reliability
Optimization
Quality of service
Resource allocation
RSSI
selection-strategy optimization
Signal quality
Signal strength
Simulation
space–time density estimation
Statistical analysis
Utility functions
Wireless communications
wireless network
Wireless networks
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Summary:Although fifth-generation (5G) wireless communication can ] support well a high data rate of transmission, issues such as base station (BS) failure and poor BS signals may cause serious interruption problems. This paper studies the user-BS selection strategy with received signal strength indication (RSSI)-based reliability in 5G wireless networks. First, reliability is defined on the basis of the RSSI and failure probability of the BS. The problem is modeled as a selection strategy optimization problem with BS capacity and receiving sensitivity as constraints. Second, the original problem can be transformed into a resource allocation problem with probabilistic constraints. For the situation where user distribution is known, we used dynamic programming to obtain the optimal BS selection strategy. For the situation where user distribution is unknown, starting from user trajectory data, we used the space–time density estimation method based on the Epanechnikov kernel to estimate user density and bring it into dynamic programming to obtain the optimal selection strategy. Simulation results show that our density estimation algorithm is more accurate than the commonly used density estimation algorithm. Compared with the distance-based optimization method, our RSSI-based optimization method also improved the communication signal quality under different scenarios.
ISSN:2076-3417
2076-3417
DOI:10.3390/app12126082