研究目的
To analyze the characteristics of wireless single cellular coverage boundary based on real measured data and propose alpha-stable processes to model it.
研究成果
The alpha-stable processes can be used to model the wireless single cellular coverage boundary with 95% confidence interval based on the measured data. This provides a basis for cooperative communications considering the anisotropic fading characteristic of wireless signal propagation.
研究不足
The study is limited to the urban and suburban areas of Shanghai, China, and the measurement is based on a specific transmission frequency and power. The anisotropic fading characteristic of wireless signal propagation is considered, but other factors may also influence the wireless single cellular coverage boundary.
1：Experimental Design and Method Selection:
The study uses a continuous wave (CW) test signal method to evaluate wireless environments and measures the wireless single cellular coverage boundary based on real data from urban and suburban areas of Shanghai, China.
2：Sample Selection and Data Sources:
Two measured BSs equipped with an omnidirectional antenna are located at urban and suburban areas of Shanghai. The transmission frequency of BSs is
3：6 GHz and the transmission power is 38 dBm. List of Experimental Equipment and Materials:
The transmitting equipment includes a base station equipped with an omnidirectional antenna, R&S SMB-100A signal resource, and BONN power amplifier. The mobile user terminal includes R&S TSML-CW receiver and R&S ROMES software.
4：Experimental Procedures and Operational Workflow:
The measurement equipment is picked up by a car driven around the BS to record received wireless signal strength and corresponding location information. A zonal statistic method is used to average the original data in every 100 m
5：Data Analysis Methods:
The alpha-stable processes are proposed to model the distribution of wireless single cellular coverage boundary. The fitting results between the real data and alpha-stable processes are analyzed with 95% confidence interval.
独家科研数据包，助您复现前沿成果，加速创新突破
获取完整内容
