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Power Back-Off Based Non-Orthogonal Random Access Scheme for Massive MTC Networks

机译:基于电源的基于电源的MATIVE MTC网络的非正交随机接入方案

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In this paper, we propose a power back-off based non-orthogonal random access (NORA) scheme for massive machine-type communications (mMTC) networks. Specifically, by employing the technique of tagged preambles (PA), multiple machine-type communication devices (MTCD) choosing the same PA can be distinguished and regarded as a non- orthogonal multiple access (NOMA) group, which enables multiple MTCDs to share the same physical uplink shared channel (PUSCH) for transmissions by multiplexing in power domain. Then, we adopt the Sukhatme's classic theory and characteristic function to formulate the optimization problem that aims at maximizing the throughput subject to the constraints on the power back-off factor, the number of MTCDs included in a NOMA group, and the successful transmission probability. By using the particle swarm optimization (PSO) algorithm, the formulated optimization problem is efficiently solved. We further adjust the access class barring (ACB) factor such that more MTCDs can obtain the access opportunities. Moreover, a low-complexity solution is also developed, which can achieve near PSO-based performance under high data rate requirement. Simulation results show that our proposed scheme can efficiently improve the network performance as compared with the existing schemes.
机译:在本文中,我们提出了一种用于大量机器型通信(MMTC)网络的基于功耗的基于电源的非正交随机接入(Nora)方案。具体地,通过采用标记的前导码(PA)的技术,可以区分和选择相同的PA的多个机器型通信设备(MTCD),并且被视为非正交的多个访问(NOMA)组,其使多个MTCDS能够共享通过在功率域中多路复用来传输相同的物理上行链路共享信道(PUSCH)。然后,我们采用Sukhatme的经典理论和特征函数来制定优化问题,旨在最大化吞吐量的吞吐量,所述吞吐量对电源回关因子的约束,NOMA组中包括的MTCD的数量以及成功的传输概率。通过使用粒子群优化(PSO)算法,有效解决了配制的优化问题。我们进一步调整访问类禁止(ACB)因子,使得更多MTCD可以获得访问机会。此外,还开发了低复杂性解决方案,其可以在高数据速率要求下实现近PSO的性能。仿真结果表明,与现有方案相比,我们所提出的方案可以有效地提高网络性能。

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