Nguyen Anh-Nhat, Vo Van Nhan, So-In Chakchai, Ha Dac-Binh
Applied Network Technology (ANT) Laboratory, Department of Computer Science, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand.
Faculty of Information Technology, Duy Tan University, Da Nang 550000, Vietnam.
Sensors (Basel). 2021 Jan 4;21(1):285. doi: 10.3390/s21010285.
This paper investigates system performance in the Internet of Things (IoT) with an energy harvesting (EH) unmanned aerial vehicle (UAV)-enabled relay under Nakagami- fading, where the time switching (TS) and adaptive power splitting (APS) protocols are applied for the UAV. Our proposed system model consists of a base station (BS), two IoT device (ID) clusters (i.e., a far cluster and a near cluster), and a multiantenna UAV-enabled relay (UR). We adopt a UR-aided TS and APS (U-TSAPS) protocol, in which the UR can dynamically optimize the respective power splitting ratio (PSR) according to the channel conditions. To improve the throughput, the nonorthogonal multiple access (NOMA) technique is applied in the transmission of both hops (i.e., from the BS to the UR and from the UR to the ID clusters). The U-TSAPS protocol is divided into two phases. In the first phase, the BS transmits a signal to the UR. The UR then splits the received signal into two streams for information processing and EH using the APS scheme. In the second phase, the selected antenna of the UR forwards the received signal to the best far ID (BFID) in the far cluster and the best near ID (BNID) in the near cluster using the decode-and-forward (DF) or amplify-and-forward (AF) NOMA scheme. We derive closed-form expressions for the outage probabilities (OPs) at the BFID and BNID with the APS ratio under imperfect channel state information (ICSI) to evaluate the system performance. Based on these derivations, the throughputs of the considered system are also evaluated. Moreover, we propose an algorithm for determining the nearly optimal EH time for the system to minimize the OP. In addition, Monte Carlo simulation results are presented to confirm the accuracy of our analysis based on simulations of the system performance under various system parameters, such as the EH time, the height and position of the UR, the number of UR antennas, and the number of IDs in each cluster.
本文研究了在 Nakagami 衰落条件下，具有能量收集（EH）功能的无人机（UAV）中继的物联网（IoT）系统性能，其中时间切换（TS）和自适应功率分配（APS）协议应用于无人机。我们提出的系统模型由一个基站（BS）、两个物联网设备（ID）集群（即一个远集群和一个近集群）以及一个多天线无人机中继（UR）组成。我们采用了一种基于 UR 的 TS 和 APS（U - TSAPS）协议，其中 UR 可以根据信道条件动态优化各自的功率分配比（PSR）。为了提高吞吐量，非正交多址接入（NOMA）技术应用于两跳传输（即从 BS 到 UR 以及从 UR 到 ID 集群）。U - TSAPS 协议分为两个阶段。在第一阶段，BS 向 UR 发送信号。然后 UR 使用 APS 方案将接收到的信号分成两个流用于信息处理和能量收集。在第二阶段，UR 选择的天线使用解码转发（DF）或放大转发（AF）NOMA 方案将接收到的信号转发到远集群中的最佳远 ID（BFID）和近集群中的最佳近 ID（BNID）。我们推导了在不完美信道状态信息（ICSI）下，BFID 和 BNID 处中断概率（OP）与 APS 比率的闭式表达式，以评估系统性能。基于这些推导，还评估了所考虑系统的吞吐量。此外，我们提出了一种算法来确定系统的近似最优能量收集时间，以最小化 OP。此外，还给出了蒙特卡罗模拟结果，通过对各种系统参数（如能量收集时间、UR 的高度和位置、UR 天线数量以及每个集群中的 ID 数量）下的系统性能进行模拟，来证实我们分析的准确性。
