Robust Transmission for Multi-User Ofdm-Based Irs-Assisted Cognitive Radio Networks
DOI:
10.2139/ssrn.4535853
Publication Date:
2023-08-09T06:19:49Z
AUTHORS (6)
ABSTRACT
In cognitive radio networks (CRNs) employing underlay multi-user scenarios, intelligent reflecting surface (IRS) plays a crucial function in augmenting total transmission rate for (CR) users, while adhering to restrictions caused by the interference from secondary users (SUs) primary (PUs). However, due passive characteristics of IRS, it operates non-cooperative relationship with both PU and SU network, resulting delayed information acquisition channel errors. Therefore, this research, considering uncertainties, limited interference, among SUs, we put forward robust power subcarrier allocation strategy orthogonal frequency division multiplexing (OFDM) IRS-assisted CRNs scenario. Formulated asa resource (RA) problem an spectrum sharing mode CR, joint optimization encompasses phase shift matrix minimum constraints. We transform using worst-case criterion into deterministic convex handle constraints bounded uncertainties. By utilizing matching theory, variable substitution, scaling methods, convex-concave programming (CCP), alternating techniques, converted non-convex is transformed one. Simulation results showcase that proposed algorithm achieves significant gains exhibits robustness.
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