The bits and flops of the n-hop multilateration primitive for node localization problems
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Robust Positioning Algorithms for Distributed Ad-Hoc Wireless Sensor Networks
ATEC '02 Proceedings of the General Track of the annual conference on USENIX Annual Technical Conference
Localization from mere connectivity
Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing
Range-free localization schemes for large scale sensor networks
Proceedings of the 9th annual international conference on Mobile computing and networking
Distributed localization in wireless sensor networks: a quantitative comparison
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Wireless sensor networks
Range-free localization and its impact on large scale sensor networks
ACM Transactions on Embedded Computing Systems (TECS)
The robustness of localization algorithms to signal strength attacks: a comparative study
DCOSS'06 Proceedings of the Second IEEE international conference on Distributed Computing in Sensor Systems
IEEE Transactions on Signal Processing
Sensor-assisted localization in cellular systems
IEEE Transactions on Wireless Communications
An empirically based path loss model for wireless channels in suburban environments
IEEE Journal on Selected Areas in Communications
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The openness of the lower-layer protocol stacks in cognitive radios increases the flexibility of dynamic spectrum access and promotes spectrally-efficient communications. To ensure the effectiveness of spectrum sharing, it is desirable to locate primary users, secondary users, and unauthorized users in a non-interactive fashion based on limited measurement data at receivers. In this work, we present two range-free localization algorithms based on dynamic mapping of received signal strength (RSS) to perform non-interactive localization that does not require the cooperation from the cognitive device to be located. A fine-grained signal strength map across the surveillance area is constructed dynamically through interpolation. By making use of this signal map, the proposed schemes can achieve higher accuracy of location estimation than existing noninteractive and RSS based methods in most channel variation conditions. Both our simulation results as well as testbed evaluations have demonstrated the feasibility of the proposed algorithms.