论文标题

基于NOMA的LPWA网络的资源分配

Resource Allocation for NOMA-based LPWA Networks Powered by Energy Harvesting

论文作者

Benkhelifa, Fatma, McCann, Julie A.

论文摘要

在本文中,我们探讨了永久,可扩展的,低功率的广阔区域网络(LPWA)。具体而言,我们专注于非正交多访问(NOMA)的LPWA网络的上行链路传输,该网络由多个自动节点和基于NOMA的单个网关组成。自供电的LPWA节点使用“收获-then-transmit”方案,在该方案中,它们从环境源(太阳能和射频信号)收集能量,然后传输其信号。研究的LPWA网络的主要特征是空气中的传输时间不同,多次上行链路传输尝试和占空比限制。这项工作的目的是通过优化传输时间分配,能源收集时间分配和功率分配来最大化上行链路传输速率的时间平均值;受最大发射功率和收获能量的可用性。我们提出了一个低复杂的解决方案,该解决方案将优化问题解散为三个子问题:我们分配了LPWA节点传输时间(使用公平或不公平的方法),我们使用一维搜索方法优化了能量收集(EH)时间,并使用一种concave-convex(cccp)过程来优化发射功率。在仿真结果中,我们将重点放在远距离(LORA)网络上,作为一个实践示例LPWA网络。我们验证了我们提出的解决方案,并观察到使用NOMA时的$ 15 \%$性能提高。

In this paper, we explore perpetual, scalable, Low-powered Wide-area networks (LPWA). Specifically we focus on the uplink transmissions of non-orthogonal multiple access (NOMA)-based LPWA networks consisting of multiple self-powered nodes and a NOMA-based single gateway. The self-powered LPWA nodes use the "harvest-then-transmit" protocol where they harvest energy from ambient sources (solar and radio frequency signals), then transmit their signals. The main features of the studied LPWA network are different transmission times-on-air, multiple uplink transmission attempts, and duty cycle restrictions. The aim of this work is to maximize the time-averaged sum of the uplink transmission rates by optimizing the transmission time-on-air allocation, the energy harvesting time allocation and the power allocation; subject to a maximum transmit power and to the availability of the harvested energy. We propose a low complex solution which decouples the optimization problem into three sub-problems: we assign the LPWA node transmission times (using either the fair or unfair approaches), we optimize the energy harvesting (EH) times using a one-dimensional search method, and optimize the transmit powers using a concave-convex (CCCP) procedure. In the simulation results, we focus on Long Range (LoRa) networks as a practical example LPWA network. We validate our proposed solution and we observe a $15\%$ performance improvement when using NOMA.

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