Ahmed M. Benaya;Mohamed S. Hassan;Mahmoud H. Ismail;Taha Landolsi
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We formulated a BR spectral efficiency maximization problem via optimizing the active beamforming vector at the AT, the power amplification factors of the IRS active elements, and the IRS phase shift at each active element under the constraints of a maximum power budget and the AR spectral efficiency requirements. The formulated problem is non-convex due to the coupling between different variables. Hence, we divided the main problems into three sub-problems and utilized the successive convex approximation (SCA) and the semidefinite relaxation (SDR) techniques to obtain a convex equivalent problem that can be solved using conventional optimization tools such as CVX. Simulation results show that the proposed algorithm converges in few number of iterations. 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引用次数: 0
摘要
随着下一代无线系统中物联网(IoT)的广泛部署,能效和电池寿命问题变得更加严重,这凸显了对创新解决方案的迫切需求。共生无线电(SR)被认为是新兴技术之一,旨在为无处不在的物联网应用提供节能解决方案。在本文中,我们提出了一种由双面有源智能反射面(DFA-IRS)辅助的 SR 系统。该系统由主动发射器(AT)、主动接收器(AR)、反向散射接收器(BR)、DFA-IRS 和连接到 DFA-IRS 的物联网设备组成。我们通过优化 AT 的有源波束成形向量、IRS 有源元件的功率放大系数以及每个有源元件的 IRS 相移,在最大功率预算和 AR 频谱效率要求的约束下,提出了一个 BR 频谱效率最大化问题。由于不同变量之间的耦合,所提出的问题是非凸的。因此,我们将主要问题划分为三个子问题,并利用连续凸近似(SCA)和半定量松弛(SDR)技术获得凸等效问题,该问题可使用 CVX 等传统优化工具求解。仿真结果表明,所提出的算法在较少的迭代次数内就能收敛。此外,与使用单面有源 IRS 或同时发射和反射 IRS(STAR-IRS)的情况相比,拟议方案实现了更好的 BR 频谱效率。
Double-Faced Active Intelligent Reflecting Surfaces-Assisted Symbiotic Radio Communications
With the extensive deployment of Internet-of-Things (IoT) in next generation wireless systems, the problems of energy efficiency and battery life become exacerbated, highlighting the pressing need for innovative solutions. Symbiotic radio (SR) is considered one of the emerging technologies that aims at providing an energy-efficient solution for the ubiquitous IoT applications. In this paper, we propose an SR system that is assisted with a double-faced active intelligent reflecting surface (DFA-IRS). The proposed system consists of an active transmitter (AT), an active receiver (AR), a backscatter receiver (BR), a DFA-IRS, and an IoT device that is connected to the DFA-IRS. We formulated a BR spectral efficiency maximization problem via optimizing the active beamforming vector at the AT, the power amplification factors of the IRS active elements, and the IRS phase shift at each active element under the constraints of a maximum power budget and the AR spectral efficiency requirements. The formulated problem is non-convex due to the coupling between different variables. Hence, we divided the main problems into three sub-problems and utilized the successive convex approximation (SCA) and the semidefinite relaxation (SDR) techniques to obtain a convex equivalent problem that can be solved using conventional optimization tools such as CVX. Simulation results show that the proposed algorithm converges in few number of iterations. Moreover, the proposed scheme achieves better BR spectral efficiency when compared to the case where a single-faced active IRS or a simultaneously transmitting and reflecting IRS (STAR-IRS) counterpart is used.