论文标题

IoT网络中的基于零努力的下行链路虚拟MIMO-NOMA通信

Zero-Forcing Based Downlink Virtual MIMO-NOMA Communications in IoT Networks

论文作者

Shi, Zheng, Wang, Hong, Fu, Yaru, Yang, Guanghua, Ma, Shaodan, Hou, Fen, Tsiftsis, Theodoros A.

论文摘要

为了支持物联网(IoT)的大规模连通性和提高光谱效率,提出了一个下行链路方案,将虚拟多重输入多数输出(MIMO)和非正交多访问(NOMA)结合起来。每个群集中的所有单个Antenna IoT设备相互配合以建立一个虚拟MIMO实体,并且每个集群都要求多个独立的数据流。 NOMA用于叠加所有请求的数据流,每个群集利用零强度的检测来脱离输入数据流。仅在基站提供统计通道状态信息(CSI),以避免在频繁的CSI估计中浪费能量和带宽。通过考虑Kronecker模型,可以彻底研究虚拟MIMO-NOMA系统的中断概率和好处,该模型既包含传输和接收相关性。此外,渐近结果不仅有助于探索物理见解,而且还促进了最大化。特别是,渐近中断表达式提供了各种系统参数的定量影响,并能够调查多样性 - 多样化的权衡(DMT)。此外,可以正确选择功率分配系数和/或传输速率以实现最大好处。通过支持Karush-Kuhn-Tucker条件,可以以封闭形式解决了Goodput最大化问题,通过使用交替迭代优化,可以通过封闭形式解决联合功率和速率选择。Beside,在良好的传播通道下,优化算法倾向于将更大的功率分配给具有不利的通道条件和支持较高传输速度的clus依的群集。

To support massive connectivity and boost spectral efficiency for internet of things (IoT), a downlink scheme combining virtual multiple-input multiple-output (MIMO) and nonorthogonal multiple access (NOMA) is proposed. All the single-antenna IoT devices in each cluster cooperate with each other to establish a virtual MIMO entity, and multiple independent data streams are requested by each cluster. NOMA is employed to superimpose all the requested data streams, and each cluster leverages zero-forcing detection to de-multiplex the input data streams. Only statistical channel state information (CSI) is available at base station to avoid the waste of the energy and bandwidth on frequent CSI estimations. The outage probability and goodput of the virtual MIMO-NOMA system are thoroughly investigated by considering Kronecker model, which embraces both the transmit and receive correlations. Furthermore, the asymptotic results facilitate not only the exploration of physical insights but also the goodput maximization. In particular, the asymptotic outage expressions provide quantitative impacts of various system parameters and enable the investigation of diversity-multiplexing tradeoff (DMT). Moreover, power allocation coefficients and/or transmission rates can be properly chosen to achieve the maximal goodput. By favor of Karush-Kuhn-Tucker conditions, the goodput maximization problems can be solved in closed-form, with which the joint power and rate selection is realized by using alternately iterating optimization.Besides, the optimization algorithms tend to allocate more power to clusters under unfavorable channel conditions and support clusters with higher transmission rate under benign channel conditions.

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