Reconfigurable intelligent surface (RIS) is a new and revolutionary technology to achieve spectrum-, energy- and cost-efficient wireless networks. This paper studies the resource allocation for RIS-empowered device-to-device (D2D) communication underlaying a cellular network, in which an RIS is employed to enhance desired signals and suppress interference between paired D2D and cellular links. We maximize the overall network’s spectrum efficiency (SE) and energy efficiency (EE), respectively, by jointly optimizing the spectrum reuse indicators, the transmit power, the RIS’s passive beamforming and the BS’s receive beamforming. To solve both mixed-integer non-linear programming problems, we first propose an efficient and low-complexity user-pairing scheme based on relative channel strength to determine the spectrum reuse indicators. Other variables are then optimized to maximize the SE by an iterative algorithm, based on the techniques of alternating optimization, successive convex approximation, Lagrangian dual transform and quadratic transform. The EE-maximization problem is solved by an alternating algorithm integrated with Dinkelbach’s method. Numerical results show that the proposed design achieves significant SE and EE enhancements compared to traditional underlay D2D network without RIS, relay-assisted D2D network and other benchmarks.

中文翻译：

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基于蜂窝网络的可重构智能表面赋能设备到设备通信

可重构智能表面 (RIS) 是一项全新的革命性技术，可实现频谱、能源和成本效益的无线网络。本文研究了蜂窝网络下基于 RIS 的设备到设备 (D2D) 通信的资源分配，其中采用 RIS 来增强所需信号并抑制成对的 D2D 和蜂窝链路之间的干扰。我们通过联合优化频谱复用指标、发射功率、RIS 的无源波束成形和 BS 的接收波束成形，分别最大化整个网络的频谱效率 (SE) 和能源效率 (EE)。为了解决这两个混合整数非线性规划问题，我们首先提出了一种基于相对信道强度的高效且低复杂度的用户配对方案，以确定频谱重用指标。然后基于交替优化、逐次凸逼近、拉格朗日对偶变换和二次变换的技术，通过迭代算法优化其他变量以最大化 SE。EE 最大化问题通过与 Dinkelbach 方法相结合的交替算法来解决。数值结果表明，与没有 RIS 的传统底层 D2D 网络、中继辅助 D2D 网络和其他基准相比，所提出的设计实现了显着的 SE 和 EE 增强。