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Interference-Aware Subcarrier Allocation for Massive Machine-Type Communication in 5G-Enabled Internet of Things

机译:支持5G的物联网中用于大规模机器类型通信的可识别干扰的子载波分配

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摘要

Massive machine-type communication (mMTC) is investigated as one of three typical scenes of the 5th-generation (5G) network. In this paper, we propose a 5G-enabled internet of things (IoT) in which some enhanced mobile broadband devices transmit video stream to a centralized controller and some mMTC devices exchange short packet data with adjacent devices via D2D communication to promote inter-device cooperation. Since massive MTC devices have data transmission requirements in 5G-enabled IoT with limited spectrum resources, the subcarrier allocation problem is investigated to maximize the connectivity of mMTC devices subject to the quality of service (QoS) requirement of enhanced Mobile Broadband (eMBB) devices and mMTC devices. To solve the formulated mixed-integer non-linear programming (MINLP) problem, which is NP-hard, an interference-aware subcarrier allocation algorithm for mMTC communication (IASA) is developed to maximize the number of active mMTC devices. Finally, the performance of the proposed algorithm is evaluated by simulation. Numerical results demonstrate that the proposed algorithm outperforms the three traditional benchmark methods, which significantly improves the utilization of the uplink spectrum. This indicates that the proposed IASA algorithm provides a better solution for IoT application.
机译:大规模机器型通信(mMTC)被研究为第五代(5G)网络的三个典型场景之一。在本文中,我们提出了一种支持5G的物联网(IoT),其中一些增强型移动宽带设备将视频流传输到中央控制器,而某些mMTC设备通过D2D通信与相邻设备交换短分组数据,以促进设备间合作。由于大规模MTC设备在频谱资源有限的5G IoT中具有数据传输要求,因此对子载波分配问题进行了研究,以最大程度地满足增强型移动宽带(eMBB)设备和服务质量(QoS)要求下mMTC设备的连接性。 mMTC设备。为了解决NP-hard提出的混合整数非线性规划(MINLP)问题,开发了一种用于mMTC通信(IASA)的具有干扰感知的子载波分配算法,以最大化活动mMTC设备的数量。最后,通过仿真评估了所提算法的性能。数值结果表明,该算法优于传统的三种基准测试方法,大大提高了上行频谱的利用率。这表明所提出的IASA算法为物联网应用提供了更好的解决方案。

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