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Joint Machine-Type Device Selection and Power Allocation for Buffer-Aided Cognitive M2M Communication

机译:联合机器类型的设备选择和功率分配,以进行缓冲辅助的认知M2M通信

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摘要

In this paper, a cognitive machine-to-machine(M2M) communication network is considered, in which a cellularnetwork shares the spectrum with the M2M communicationnetwork with M machine-type devices (MTDs), one half-duplexrelay, and one MTD gateway for data gathering. One keychallenge is that in the future 5G wireless networks, there willbe billions of those small MTDs, and therefore, a MTD selectionprotocol is required for managing data transmission betweenMTDs. A joint buffer-aided MTD selection and power allocationprotocol is proposed to maximize the MTDs’ sum-rate providedthat the induced interference to the cellular network is limited.In particular, in the proposed scheme, at each time slot andeach subcarrier, the cognitive M2M network optimally decideson whether to be silent or to select either the relay or one of theMTDs for data transmission. To this end, for each MTD, thereexists a buffer at the relay to avoid data loss. The closed-formexpressions for the power coefficients of MTDs are calculated.Simulation results show that the proposed policy improves thesum-rate of the CM2M network in comparison with the otherproposed schemes for M2M communication without buffer
机译:本文考虑了一种认知机器对机器(M2M)通信网络,其中蜂窝网络与M2M通信网络共享频谱,该网络具有M个机器类型设备(MTD),一个半双工中继和一个MTD网关,用于数据收集。一个关键的挑战是,在未来的5G无线网络中,将有数十亿个小型MTD,因此,需要MTD选择协议来管理MTD之间的数据传输。提出了一种联合缓冲辅助的MTD选择和功率分配协议,以在限制对蜂窝网络的干扰的前提下最大化MTD的求和率。特别是,在该方案中,在每个时隙和每个子载波上,认知M2M网络最佳地决定是保持沉默还是选择中继器或选择MTD之一进行数据传输。为此,对于每个MTD,在中继器处都存在缓冲器以避免数据丢失。仿真结果表明,与其他提出的无缓冲M2M通信方案相比,该策略提高了CM2M网络的求和率。

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