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Symbiotic Radio Massive MIMO IoT Network With Wireless Powered RIS Backscatter Communications
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DOI：10.1109/tgcn.2026.3690679.png)
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Abstract
En 中文
This paper investigates energy efficiency (EE) maximization in a reconfigurable intelligent surface (RIS)-assisted massive multiple-input multiple-output (mMIMO) symbiotic radio (SR) network for green Internet-of-Things (IoT) applications. The primary network (PN) employs an mMIMO base station (BS) with non-orthogonal multiple access (NOMA) to serve multiple multi-antenna user equipment, while multiple semi-passive RISs form the secondary network (SN) and perform wireless-powered backscatter communication (BackCom) toward a multi-antenna reader. For this setup, we consider a fully coupled multi-antenna SR system with a practical multi-stage nonlinear energy harvesting (EH) model, where the harvested energy determines the circuit operation and activation of each RIS. We formulate a network-wide nonconvex fractional EE maximization problem subject to resource allocation and harvested-energy constraints. By combining the Dinkelbach transformation with the weighted minimum mean-square error (WMMSE) approach, an efficient alternating optimization algorithm with closed-form updates is developed. An expectation-based analysis is first presented to reveal the impact of the BS antenna dimension, transmit power, and RIS density on the symbiotic operation, showing EE saturation and interference-limited regimes. Simulation results demonstrate the effectiveness of the proposed scheme and significant EE gains over benchmarks.
Keywords:
Symbiotic radio
reconfigurable intelligent surfaces (RIS)
massive multiple-input-multiple-output (mMIMO)
energy-efficiency (EE)
energy harvesting (EH)
Journal
I
IF:
6.7
Papers:
1.3K
Citations:
4.3K
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