Control algorithm of adaptive antenna arrays for signal and interference separation

Giniatullin, N.F.; Glushankov, E. I.; Marchuk, L. A.

doi:10.1109/icsigp.1996.567304

Cited by 1 publication

(1 citation statement)

References 3 publications

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“…To realize the RF fingerprint, an RF signal fluctuation unique to each sensor is required; however, the detection of stable signals is challenging owing to the uncertainty of the RF signal. The arrival wave estimation method based on null beam formation in an adaptive array antenna enables the individual separation of simultaneously accessed signals [ 27 ]. However, the number of antennas required increases in the case of many signals, resulting in a considerable increase in the complexity of the receiver.…”

Section: Related Studiesmentioning

confidence: 99%

Three Level Recognition Based on the Average of the Phase Differences in Physical Wireless Parameter Conversion Sensor Networks and Its Effect to Localization with RSSI

Ito

Oda

Takyu

et al. 2023

Sensors

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In recent years, there have been increased demands for aggregating sensor information from several sensors owing to the spread of the Internet of Things (IoT). However, packet communication, which is a conventional multiple-access technology, is hindered by packet collisions owing to simultaneous access by sensors and waiting time to avoid packet collisions; this increases the aggregation time. The physical wireless parameter conversion sensor network (PhyC-SN) method, which transmits sensor information corresponding to the carrier wave frequency, facilitates the bulk collection of sensor information, thereby reducing the communication time and achieving a high aggregation success rate. However, when more than one sensor transmits the same frequency simultaneously, the estimation accuracy of the number of accessed sensors deteriorates significantly because of multipath fading. Thus, this study focuses on the phase fluctuation of the received signal caused by the frequency offset inherent to the sensor terminals. Consequently, a new feature for detecting collisions is proposed, which is a case in which two or more sensors transmit simultaneously. Furthermore, a method to identify the existence of 0, 1, 2, or more sensors is established. In addition, we demonstrate the effectiveness of PhyC-SNs in estimating the location of radio transmission sources by utilizing three patterns of 0, 1, and 2 or more transmitting sensors.

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Section: Related Studiesmentioning

confidence: 99%