Lower energy consumption and higher data rate have been becoming the key factors of modern wireless mobile communication for the improvement of user experiences. At present, the commercialization of 5G communications is gradually promoting the development of Internet of things (IoT) techniques. Due to the limited coverage capability of direct wireless communications, the indirect device-to-device (D2D) communications using information relay, in addition to the single 5G base station deployment, have been introduced. Along with the increase of information nodes, the relay devices have to undertake the nonnegligible extra data traffic. In order to adjust and optimize the information routing in D2D services, we present an algorithmic investigation referring to the ant colony optimization (ACO) algorithm and the artificial immune algorithm (AIA). By analyzing the characteristics of these algorithms, we propose a combined algorithm that enables the improved the iterative convergence speed and the calculation robustness of routing path determination. Meanwhile, the D2D optimization pursuing energy saving is numerically demonstrated to be improved than the original algorithms. Based on the simulation results under a typical architecture of 5G cellular network including various information nodes (devices), we show that the algorithmic optimization of D2D routing is potentially valid for the realization of primitive wireless IoT networks.

中文翻译：

---

基于ACO和AIA融合算法的节能D2D无线组网

更低的能耗和更高的数据速率已成为现代无线移动通信改善用户体验的关键因素。目前，5G通信的商用化正在逐步推动物联网（IoT）技术的发展。由于直接无线通信的覆盖能力有限，除了单5G基站部署外，还引入了使用信息中继的间接设备到设备（D2D）通信。随着信息节点的增加，中继设备不得不承担不可忽视的额外数据流量。为了调整和优化D2D服务中的信息路由，我们参考了蚁群优化（ACO）算法和人工免疫算法（AIA）进行了算法研究。通过分析这些算法的特点，我们提出了一种组合算法，可以提高迭代收敛速度和路由路径确定的计算鲁棒性。同时，追求节能的D2D优化在数值上证明比原始算法有所改进。基于包含各种信息节点（设备）的 5G 蜂窝网络典型架构下的仿真结果，我们表明 D2D 路由的算法优化对于实现原始无线物联网网络具有潜在的有效性。追求节能的D2D优化在数值上证明比原始算法有所改进。基于包含各种信息节点（设备）的 5G 蜂窝网络典型架构下的仿真结果，我们表明 D2D 路由的算法优化对于实现原始无线物联网网络具有潜在的有效性。追求节能的D2D优化在数值上证明比原始算法有所改进。基于包含各种信息节点（设备）的 5G 蜂窝网络典型架构下的仿真结果，我们表明 D2D 路由的算法优化对于实现原始无线物联网网络具有潜在的有效性。