Signal Detection in Ambient Backscatter Systems: Fundamentals, Methods, and Trends

Shayan Zargari, Azar Hakimi, Fatemeh Rezaei, Chintha Tellambura, Amine Maaref
Computer Science, Information Theory, Information Theory (cs.IT), Signal Processing (eess.SP)
2023-12-06 00:00:00
Internet-of-Things (IoT) is rapidly growing in wireless technology, aiming to connect vast numbers of devices to gather and distribute vital information. Despite individual devices having low energy consumption, the cumulative demand results in significant energy usage. Consequently, the concept of ultra-low-power tags gains appeal. Such tags communicate by reflecting rather than generating the radio frequency (RF) signals by themselves. Thus, these backscatter tags can be low-cost and battery-free. The RF signals can be ambient sources such as wireless-fidelity (Wi-Fi), cellular, or television (TV) signals, or the system can generate them externally. Backscatter channel characteristics are different from conventional point-to-point or cooperative relay channels. These systems are also affected by a strong interference link between the RF source and the tag besides the direct and backscattering links, making signal detection challenging. This paper provides an overview of the fundamentals, challenges, and ongoing research in signal detection for AmBC networks. It delves into various detection methods, discussing their advantages and drawbacks. The paper's emphasis on signal detection sets it apart and positions it as a valuable resource for IoT and wireless communication professionals and researchers.
PDF: Signal Detection in Ambient Backscatter Systems: Fundamentals, Methods, and Trends.pdf
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