A Novel Wireless Communication Paradigm for Intelligent Reflecting Surface Based Symbiotic Radio Systems
arXiv:2104.09161 · doi:10.1109/TSP.2021.3135603
Abstract
This paper investigates a novel intelligent reflecting surface (IRS)-based symbiotic radio (SR) system architecture consisting of a transmitter, an IRS, and an information receiver (IR). The primary transmitter communicates with the IR and at the same time assists the IRS in forwarding information to the IR. Based on the IRS's symbol period, we distinguish two scenarios, namely, commensal SR (CSR) and parasitic SR (PSR), where two different techniques for decoding the IRS signals at the IR are employed. We formulate bit error rate (BER) minimization problems for both scenarios by jointly optimizing the active beamformer at the base station and the phase shifts at the IRS, subject to a minimum primary rate requirement. Specifically, for the CSR scenario, a penalty-based algorithm is proposed to obtain a high-quality solution, where semi-closed-form solutions for the active beamformer and the IRS phase shifts are derived based on Lagrange duality and Majorization-Minimization methods, respectively. For the PSR scenario, we apply a bisection search-based method, successive convex approximation, and difference of convex programming to develop a computationally efficient algorithm, which converges to a locally optimal solution. Simulation results demonstrate the effectiveness of the proposed algorithms and show that the proposed SR techniques are able to achieve a lower BER than benchmark schemes.
This manuscript has been submitted to IEEE journal for possible publication
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Cited by in corpus (5)
- Intelligent Reflecting Surface Enabled Multi-Target Sensing
- Reconfigurable Intelligent Surfaces for 6G -- Applications, Challenges and Solutions
- Pilot Design and Signal Detection for Symbiotic Radio over OFDM Carriers
- Revolutionizing Symbiotic Radio: Exploiting Tradeoffs in Hybrid Active-Passive Communications
- A Novel Stochastic Model for IRS-Assisted Communication Systems Based on the Sum-Product of Nakagami- Random Variables