Nguyen Tan N, Minh Bui Vu, Tran Dinh-Hieu, Le Thanh-Lanh, Le Anh-Tu, Nguyen Quang-Sang, Lee Byung Moo
Communication and Signal Processing Research Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City 70000, Vietnam.
Faculty of Engineering and Technology, Nguyen Tat Thanh University, 300A-Nguyen Tat Thanh, Ward 13, District 4, Ho Chi Minh City 754000, Vietnam.
Sensors (Basel). 2023 Sep 2;23(17):7618. doi: 10.3390/s23177618.
This paper investigates the security-reliability of simultaneous wireless information and power transfer (SWIPT)-assisted amplify-and-forward (AF) full-duplex (FD) relay networks. In practice, an AF-FD relay harvests energy from the source (S) using the power-splitting (PS) protocol. We propose an analysis of the related reliability and security by deriving closed-form formulas for outage probability (OP) and intercept probability (IP). The next contribution of this research is an asymptotic analysis of OP and IP, which was generated to obtain more insight into important system parameters. We validate the analytical formulas and analyze the impact on the key system parameters using Monte Carlo simulations. Finally, we propose a deep learning network (DNN) with minimal computation complexity and great accuracy for OP and IP predictions. The effects of the system's primary parameters on OP and IP are examined and described, along with the numerical data.
本文研究了同时进行无线信息与能量传输（SWIPT）辅助的放大转发（AF）全双工（FD）中继网络的安全可靠性。在实际中，AF-FD中继使用功率分配（PS）协议从源节点（S）收集能量。我们通过推导中断概率（OP）和拦截概率（IP）的闭式公式，对相关的可靠性和安全性进行了分析。本研究的下一个贡献是对OP和IP的渐近分析，其目的是更深入地了解重要的系统参数。我们通过蒙特卡罗模拟验证了解析公式，并分析了对关键系统参数的影响。最后，我们提出了一种计算复杂度最低且精度高的深度学习网络（DNN），用于OP和IP预测。研究了系统主要参数对OP和IP的影响，并结合数值数据进行了描述。
