论文标题

智能反射表面辅助无线网络的反射资源管理

Reflection Resource Management for Intelligent Reflecting Surface Aided Wireless Networks

论文作者

Gao, Yulan, Yong, Chao, Xiong, Zehui, Zhao, Jun, Xiao, Yue, Niyato, Dusit

论文摘要

在本文中,研究了在两跳网络中的多个单人源源终端(ST)-DT对的智能反射表面(IRS)。与以前对IRS的研究不同,这些研究仅着重于调整IRS所有反射元素的反射系数,在本文中,我们考虑了真正的反思资源管理。具体而言,可以根据我们提出的IRS体系结构通过触发模块选择来实现真正的反射资源管理,即所有反射元素均由控制器的多个并行开关部分控制。随着反射元素的数量的增加,在这种情况下,真正的反思资源管理将迫切需要,这是由于不可忽视的能源消耗所致。此外,提议的IRS模块化体系结构旨在使反射元素部分独立且可控。因此,我们的目标是通过连接触发模块子集选择,STS的传输功率分配以及触发模块的相应的被动横向形成,最大化DTS处的最小信号与互助 - 加上噪声比率(SINR),约为每个ST发电预算和模块尺寸约束。尽管由于模块大小约束,因此该问题是NP-HARD,但我们通过引入混合行块标准将硬模块大小约束转换为组稀疏约束,从而产生合适的半决赛松弛。此外,提出了乘数(PADMM)的并行交替方向方法来识别触发模块子集,然后可以通过解决原始的最小SINR最大化问题来获得发射功率分配和被动式光束形成,而无需通过部分通过部分线性来解决一般分数程序的稀疏稀疏约束。

In this paper, the adoption of an intelligent reflecting surface (IRS) for multiple single-antenna source terminal (ST)-DT pairs in two-hop networks is investigated. Different from the previous studies on IRS that merely focused on tuning the reflection coefficient of all the reflection elements at IRS, in this paper, we consider the true reflection resource management. Specifically, the true reflection resource management can be realized via trigger module selection based on our proposed IRS architecture that all the reflection elements are partially controlled by multiple parallel switches of controller. As the number of reflection elements increases, the true reflection resource management will become urgently needed in this context, which is due to the non-ignorable energy consumption. Moreover, the proposed modular architecture of IRS is designed to make the reflection elements part independent and controllable. As such, our goal is to maximize the minimum signal-to-interference-plus-noise ratio (SINR) at DTs via a joint trigger module subset selection, transmit power allocation of STs, and the corresponding passive beamforming of the trigger modules, subject to per ST power budgets and module size constraint. Whereas this problem is NP-hard due to the module size constraint, to deal with it, we transform the hard module size constraint into the group sparse constraint by introducing the mixed row block norm, which yields a suitable semidefinite relaxation. Additionally, the parallel alternating direction method of multipliers (PADMM) is proposed to identify the trigger module subset, and then subsequently the transmit power allocation and passive beamforming can be obtained by solving the original minimum SINR maximization problem without the group sparse constraint via partial linearization for generalized fractional programs.

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