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Efficient LTE Backscatter with Universality
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DOI：10.1109/tmc.2026.3723673.png)
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Abstract
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Ambient Long Term Evolution (LTE) backscatter offers a compelling approach for enabling ultra-low-power communication in Internet of Things (IoT) applications. However, current LTE backscatter systems face limitations due to their reliance on raw data (content), inefficient utilization of Physical Layer (PHY) resources, and insufficient flexibility across different configurations. This paper introduces CABLTE, a content-agnostic and efficient LTE backscatter design with a path toward universality across configurations. CABLTE optimally leverages LTE PHY resources through a checksum-based codeword translation method, enabling precise demodulation of tag data without the need for prior knowledge of the original signal content. CABLTE is further analyzed under Multiple-Input Multiple-Output (MIMO) LTE and sub-6 GHz 5G New Radio (NR) configurations, showing its potential to extend beyond Single-Input Single-Output (SISO) LTE. Our experiments show that CABLTE achieves a peak tag throughput of 22 kbps, outperforming existing content-agnostic system CAB by 3.67 times and surpassing content-based system SyncLTE by 1.38 times. These findings establish CABLTE as a practical step toward content-agnostic cellular backscatter across multiple configurations.
Keywords:
Internet of Things
ambient backscatter
LTE
5G NR
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