Name
Title | ||
|---|---|---|
Kriging-based RSSI prediction for cell coverage discovery using spectrum database in 5G multi-band cellular networks. |
Abstract | ||
|---|---|---|
5G systems are expected to employ C/U (ControUUser)-plane split and massive deployment of small cells for high frequency reuse at SHF bands such as 28GHz band in conjunction with a macro cell using traditional UHF bands to meet increasing demand for higher capacity. In 5G multi-band cellular networks, an energy efficient SHF band cell discovery technique is required since SHF band cells will be deployed on a hot-spot basis. This paper proposes Kriging-based RSSI (Received signal strength indication) prediction for cell coverage discovery using spectrum database in 5G multi-band cellular networks. This paper also describes performance evaluation results of the Kriging-based RSSI prediction using ray-tracing simulation and demonstrates the feasibility of the proposed RSSI prediction method. |
Year | Venue | Keywords |
|---|---|---|
2017 | Asia-Pacific Conference on Communications | 5G,multi-band,RSSI prediction,cell discovery,Kriging,spectrum database |
Field | DocType | ISSN |
Kriging,Super high frequency,Data modeling,Base station,Received signal strength indication,Efficient energy use,Computer science,Real-time computing,Cellular network,Ultra high frequency,Database | Conference | 2163-0771 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuto Ogawa | 1 | 0 | 0.34 |
| masahiro umehira | 2 | 71 | 25.98 |
| Xiaoyan Wang | 3 | 89 | 21.21 |