Localizing noncooperative receiver through full-duplex amplify-and-forward relay

Localizing noncooperative transmitter (Tx) and receiver (Rx) that belong to another system is important in many scenarios, e.g., interference management in cognitive radio systems and user behavior learning in ad hoc wireless networks. However, obtaining the locations of these nodes in particular in frequency-division duplex systems is challenging, since the localization network usually does not know the spectrum that the Rx uses for backward transmission. In this paper, we propose to use the full-duplex relay technique to localize a noncooperative Rx, which does not require the knowledge of the Rx’s backward transmission spectrum. In the proposed method, localization sensors alternatively act as a full-duplex amplify-and-forward relay to trigger the power control of the Tx–Rx link. Then, by detecting the power adjustment of the Tx, each localization sensor can estimate the time difference of arrival between the direct and relay signals. Finally, the Rx location can be calculated from triangulation. Simulation results show that the proposed method can effectively localize the Rx, which validates its potential for receiver-aware applications and services

Third-Party Receiver Positioning in Wireless Sensor Networks

Even though the wireless positioning in sensor networks has been extensively studied in the past decades, there is no contribution discussing positioning the receiver that belongs to another system, i.e., the third-party receiver. In this paper, we propose a new scheme to solve the problem by full-duplex relay technique. In our scheme, we let the sensors conduct the full-duplex relay for the target receiver. By measuring the power variation of the corresponding transmitter, the sensors are able to position the receiver. Under the proposed scheme, we develop two methods. The first one is based on angle estimation, which requires multiple sensors. The second one is based on angle and time-difference-of-arrival (TDOA) estimations, which requires only one sensor. The simulation results demonstrate the performance of the proposed methods