论文标题
一种新型的混合反向散射和多跳物IoT网络的常规算法
A Novel Hybrid Backscatter and Conventional Algorithm for Multi-Hop IoT Networks
论文作者
论文摘要
本文从端到端的位交付方面研究了多跳的认知无线网络。该网络以混合方式利用反向散射通信（BackCom）和收获-Transmit（HTT）模式。这种网络可以在物联网应用程序（IoT）应用程序中使用，其中IoT用户与主网络（PN）并存，并使用主要频谱在BackCom和HTT模式中传输数据。此外，此类用户可以从主要信号中收集能量。提出了一种新型的混合反向散射和常规传输（HBCT）算法，以通过共同优化时间和功率分配来最大化端到端位。为此，我们制定了一个非凸优化问题。接下来，我们将问题转换为凸面并开发出新的分析公式，通过该公式，我们通过该公式计算封闭形式方程中的最佳功率和时间分配。与当前方案相比，数值结果证明了HBCT的优势。
This paper investigates a multi-hop cognitive radio network in terms of end-to-end bit delivery. The network exploits backscatter communication (BackCom) and harvest-then-transmit (HTT) mode in a hybrid manner. Such a network can be used in internet of things (IoT) applications in which IoT users coexist with a primary network (PN) and use the primary spectrum to transmit data in both BackCom and HTT modes. Besides, such users can harvest energy from the primary signals. A novel hybrid backscatter and conventional transmission (HBCT) algorithm is proposed in order to maximize end-to-end bit delivery by jointly optimizing time and power allocations. For this goal, we formulate a non-convex optimization problem. Next, we transform the problem into a convex one and develop a new analytical formulation by which we calculate the optimal power and time allocation in closed-form equations. The numerical results demonstrate the superiority of HBCT compared with current schemes.
