Relay-enabled backscatter communication (BC) is an intriguing paradigm to alleviate energy shortage and improve throughput of Internet-of-Things (IoT) devices. Most of the existing works focus on the resource allocation that considered the unequal and continuous time allocation for both source-relay and relay-destination links. However, the continuous time allocation may be infeasible since in practice, the time allocation shall be carried out in integral multiple of the subframe duration unit. In this article, we study a discrete time scheme from the perspective of frame structure, where one transmission block is divided into two phases and the linear mapping is employed as a re-encoding method to determine the number of subframes for both phases and the power allocation for each subframe in a relay-enabled BC system. Based on this, we derive an accurate system-throughput expression and formulate a mixed-integral non-convex optimization problem to maximize the system throughput by jointly optimizing the power reflection coefficient (PRC) of the IoT node, the power allocation of the hybrid access point (HAP) and the linear mapping matrix, and solve it via a three-step approach. Accordingly, we propose a low complexity iterative algorithm to obtain the throughput maximization-based resource allocation solution. Numerical results analyze the performance of our proposed algorithm, verify the superiority of our proposed scheme, and evaluate the impacts of network parameters on the system throughput.

翻译：启用中继的反向散射通信（BC）是缓解物联网（IoT）设备能量短缺并提升其吞吐量的一种引人入胜的范式。现有研究大多聚焦于资源分配问题，通常考虑信源-中继与中继-目的链路间非均等的连续时间分配。然而，由于实际中时间分配必须以子帧时长单位的整数倍执行，连续时间分配可能并不可行。本文从帧结构视角研究离散时间方案：在一个传输块划分为两个阶段的框架下，采用线性映射作为重编码方法，以确定启用中继的反向散射通信系统中两个阶段的子帧数量及各子帧的功率分配。基于此，我们推导了精确的系统吞吐量表达式，并构建了一个混合整数非凸优化问题，通过联合优化IoT节点的功率反射系数（PRC）、混合接入点（HAP）的功率分配及线性映射矩阵来最大化系统吞吐量，进而采用三步法求解该问题。相应地，我们提出了一种低复杂度迭代算法，以获得基于吞吐量最大化的资源分配方案。数值结果分析了所提算法的性能，验证了所提方案的优越性，并评估了网络参数对系统吞吐量的影响。