TY - JOUR
T1 - A Novel Wireless Communication Paradigm for Intelligent Reflecting Surface Based Symbiotic Radio Systems
AU - Hua, Meng
AU - Wu, Qingqing
AU - Schober, Robert
AU - Poor, H. Vincent
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - Array signal processing
KW - Bit error rate
KW - Optimization
KW - Radio transmitters
KW - Receivers
KW - Relays
KW - Symbiosis
UR - http://www.scopus.com/inward/record.url?scp=85124400675&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85124400675&partnerID=8YFLogxK
U2 - 10.1109/TSP.2021.3135603
DO - 10.1109/TSP.2021.3135603
M3 - Article
AN - SCOPUS:85124400675
SN - 1053-587X
VL - 70
SP - 550
EP - 565
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
ER -