Name
Abstract | ||
|---|---|---|
The secondary usage of TV white spaces by cognitive devices is a widely concerned topic in recent years. Both the Federal Communications Commission (FCC) in USA and the Electronic Communications Committee (ECC) in Europe have proposed rules to enable the secondary spectrum access in TV white spaces by geolocation database method. Geolocation database in cognitive network maintains records of all authorized services in the TV frequency bands and has the capability of providing a list of available frequencies and power levels for each geographical pixel based on the interference protection requirements. Since the data in geolocation database are defined for each geographical pixel, the complexity and cost of the database is highly correlate with the size of the pixel. In this paper, a novel method to reduce the complexity and cost is proposed and explained, which compress some compressible geographic pixels and use non-uniform dimensions of pixels in populating the database. With simulation and performance evaluations, we concluded that this method can significantly reduce the computational complexity and implement cost of geolocation database. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/VTCFall.2013.6692048 | VTC Fall |
Keywords | Field | DocType |
cognitive network,geolocation database,multimedia databases,white space,compressible geographic pixel,nonuniform pixel dimension,cognitive radio,tv white space,secondary spectrum access,tv frequency band,cognitive device,computational complexity,geography,geolocation database method,interference protection requirement | White spaces,Computer science,Television channel frequencies,Geolocation,Pixel,Interference protection,Database,Cognitive radio,Computational complexity theory,Cognitive network | Conference |
Volume | Issue | ISSN |
null | null | 1090-3038 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiao Jin | 1 | 0 | 0.34 |
| Qixun Zhang | 2 | 157 | 28.59 |
| Zhiyong Feng | 3 | 794 | 167.21 |
| Yifan Zhang | 4 | 30 | 10.85 |
| Yinghua Liu | 5 | 0 | 0.34 |