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Performance analysis and optimization for coverage enhancement strategy of Narrow-band Internet of Things

机译:窄带物联网覆盖增强策略的性能分析与优化

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Narrowband Internet of Things (NB-IoT) is a clean-slate wireless protocol proposed by the 3rd Generation Partnership Project intending for massive machine type communications. The general objectives of the NB-IoT include supporting massive connections, enhanced coverage, reduced cost and complexity, ultra-low power consumption, and flexible delay characteristics. To achieve the objective of 20dB enhanced coverage of NB-IoT, the concept of narrow-band modulation, coverage classes updating and adaptive repetition were introduced. To evaluate the performance of these new techniques, a Markov chain model with coverage classes as state variables was proposed to describe the dynamics of the coverage classes updating mechanism of NB-IoT. In addition, an optimization model minimizing average probability of access failure as well as average power consumption was formulated, with which the effects of preamble repetition number, system load and global maximum transmission number on the optimal configuration of maximum transmission number of each coverage class was analyzed. To solve the aforementioned optimization model, two algorithms, namely exhaustive search method combining constraint transform and particle swarm optimization (PSO) algorithm with self-adaptive stochastic inertia weight were proposed. Numerical results show that the maximum transmission number of normal coverage and extended coverage have a great influence on the system performance and their value ranges should be set within [3,10] and 11,61 respectively; while the maximum transmission number of extreme coverage has little influence on the system performance, and its recommended value is 1 for smaller power consumption. The average power consumption of coverage classes updating mechanism with coverage classes rollback is about 61% lower than that of 3GPP proposed model. All these researches together provide good reference for scale deployment of NB-IoT. (C) 2019 Elsevier B.V. All rights reserved.
机译:窄带物联网(NB-IoT)是第三代合作伙伴计划提出的旨在进行大规模机器类型通信的干净无线协议。 NB-IoT的总体目标包括支持大规模连接,增强覆盖范围,降低成本和复杂性,超低功耗以及灵活的延迟特性。为了实现NB-IoT覆盖范围扩大20dB的目标,引入了窄带调制,覆盖范围更新和自适应重复的概念。为了评估这些新技术的性能,提出了一个以覆盖类别作为状态变量的马尔可夫链模型来描述NB-IoT覆盖类别更新机制的动态。另外,建立了使接入失败的平均概率和平均功耗最小的优化模型,由此优化了前导码重复次数,系统负载和全局最大传输次数对每个覆盖等级的最大传输次数的最优配置的影响。分析。为解决上述优化模型,提出了两种算法,即结合约束变换的穷举搜索法和具有自适应随机惯性权重的粒子群算法。数值结果表明,正常覆盖和扩展覆盖的最大传输次数对系统性能有很大影响,其取值范围应分别设置在[3,10]和11,61之间。极限覆盖的最大传输次数对系统性能的影响很小,对于较小的功耗,推荐值为1。具有覆盖等级回滚的覆盖等级更新机制的平均功耗比3GPP提出的模型低约61%。这些研究为NB-IoT的大规模部署提供了很好的参考。 (C)2019 Elsevier B.V.保留所有权利。

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