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Cellular Internet-of-Things (IoT) Communications over Unlicensed Band

机译:非授权频段上的蜂窝物联网(IoT)通信

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The mass deployments of Internet-of-Thing (IoT) devices may quick congest the cellular network, affecting the energy consumption of IoT devices and degrading the spectral efficiency of the cellular network. To tackle this problem, a promising issue is to extend the IoT communications into the unlicensed band. In this paper, we consider an uplink cellular IoT network where IoT devices can serve as the cluster head (CH) to aggregate the data from other IoT devices in the same cluster. To be specific, the IoT devices can either transmit the sensory data to the base station (BS) directly by cellular communications, or aggregate the data to a CH through Machine-to-Machine (M2M) communications before the CH uploads the aggregated data to the BS. To support the massive connection of IoT devices, the unlicensed spectrum is utilized for M2M communications. We first introduce the scheduled number maximization problem of IoT devices with the minimum transmit power, and then decouple it into two subproblems, which are solved by successive integer linear programming and convex optimization techniques, respectively. Simulation results show that the proposed unlicensed scheme can support more IoT devices than that only using licensed spectrum.
机译:物联网(IoT)设备的大规模部署可能会使蜂窝网络快速拥塞,从而影响IoT设备的能耗并降低蜂窝网络的频谱效率。为了解决这个问题,一个有前途的问题是将IoT通信扩展到非许可频段。在本文中,我们考虑一个上行链路蜂窝物联网网络,其中物联网设备可以用作群集头(CH),以聚合来自同一群集中其他物联网设备的数据。具体而言,IoT设备既可以通过蜂窝通信直接将传感数据传输到基站(BS),也可以在CH将聚合的数据上传到CH之前,通过机器对机器(M2M)的通信将数据聚合到CH。 BS。为了支持物联网设备的大规模连接,未经许可的频谱用于M2M通信。我们首先介绍具有最小发射功率的IoT设备的计划数量最大化问题,然后将其分解为两个子问题,分别通过连续整数线性规划和凸优化技术解决。仿真结果表明,与仅使用许可频谱相比,该提议的免许可方案可以支持更多的物联网设备。

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