Enabling location and environment awareness in cognitive radios
Computer Communications
Centralized modeling of the communication space for spectral awareness in cognitive radio networks
ACM SIGMOBILE Mobile Computing and Communications Review
Fundamental limits on time delay estimation in dispersed spectrum cognitive radio systems
IEEE Transactions on Wireless Communications
Estimation of maximum interference-free power level for opportunistic spectrum access
IEEE Transactions on Wireless Communications
Automatic modulation classification for cognitive radios using cyclic feature detection
IEEE Circuits and Systems Magazine
OFDM for cognitive radio: merits and challenges
IEEE Wireless Communications
Opportunistic spectrum sharing with multiple cochannel primary transmitters
IEEE Transactions on Wireless Communications
Formation coordination for self-mobile localization: framework
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
Time-Delay estimation in dispersed spectrum cognitive radio systems
EURASIP Journal on Advances in Signal Processing - Special issue on advanced signal processing for cognitive radio networks
Wireless Personal Communications: An International Journal
| Hi-index | 0.00 |
Location awareness is an essential characteristic of cognitive radios as well as networks. In this article a location awareness engine architecture is proposed for the realization of location awareness in cognitive radios and networks. The proposed architecture consists of location estimation and/or sensing, seamless positioning and interoperability, statistical learning and tracking, security and privacy, mobility management, and location-based applications. However, the focus of this article is on location-based applications where we demonstrate the utilization of location information in cognitive wireless networks by presenting some representative location-assisted network optimization applications such as location-assisted spectrum management, network planning and expansion, and handover. Our study unveils that location information can be used in cognitive wireless networks to optimize network performance. Possible solutions to the implementation issues are proposed, and the remaining open issues are also addressed.