Channel Estimation for Full-Duplex Multi-Antenna Ambient Backscatter Communication Systems

Abdallah, Saeed; Verboven, Zeno; Saad, Mohamed; Albreem, Mahmoud A.

doi:10.1109/tcomm.2023.3251387

Cited by 7 publications

(4 citation statements)

References 34 publications

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“…Accordingly, pilot-based and blind CE techniques have been developed [55]- [61]. Another strategy is the semi-blind estimation, which exploits both pilot and data transmissions in the estimation process [56], [58].…”

Section: Ambc Channel Estimationmentioning

confidence: 99%

“…These methods combine both pilot symbols and data for wireless CE [58]. Pilot symbols enable initial CE, while data symbols, forming a significant portion of the transmitted signal, refine the estimation.…”

Section: ) Semi-blind Channel Estimationmentioning

confidence: 99%

“…Examples include the EM technique and decision-directed (DD) estimation. The EM technique treats unknown data as hidden variables, yielding estimates with monotonically non-decreasing likelihood [58], [72]. On the other hand, the DD method initially estimates the channel using pilot transmission, then uses the decoded data as additional pilots to re-estimate the channel [58].…”

Section: ) Semi-blind Channel Estimationmentioning

confidence: 99%

“…The EM technique treats unknown data as hidden variables, yielding estimates with monotonically non-decreasing likelihood [58], [72]. On the other hand, the DD method initially estimates the channel using pilot transmission, then uses the decoded data as additional pilots to re-estimate the channel [58]. This technique achieves greater accuracy than pilot-based estimators and lower computational complexity than EM-based estimators, as it incorporates transmitted data into estimation without computing their posterior probabilities [73].…”

Section: ) Semi-blind Channel Estimationmentioning

confidence: 99%

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

Zargari,

Hakimi,

Rezaei

et al. 2023

IEEE Access

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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.

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