[论文解读] Throughput Analysis and User Barring Design for Uplink NOMA-Enabled Random Access

Wenjuan Yu, Chuan Heng Foh+3 more|arXiv (Cornell University)|Feb 9, 2020

Advanced Wireless Communication Technologies参考文献 19被引用 7

一句话总结

本文提出了一种基于非正交多址（NOMA）的随机接入（NOMA-RA）方案，用于上行链路大规模机器类通信（mMTC），通过在相同信道上采用功率域复用允许多个设备同时传输，从而提升频谱效率和吞吐量。通过分析建模吞吐量并引入基于信道反馈的自适应用户阻塞算法，该方案在突发性流量条件下仍实现比传统MS-ALOHA高出三倍以上的最大吞吐量。

ABSTRACT

Being able to accommodate multiple simultaneous transmissions on a single channel, non-orthogonal multiple access (NOMA) appears as an attractive solution to support massive machine type communication (mMTC) that faces a massive number of devices competing to access the limited number of shared radio resources. In this paper, we first analytically study the throughput performance of NOMA-based random access (RA), namely NOMA-RA. We show that while increasing the number of power levels in NOMA-RA leads to a further gain in maximum throughput, the growth of throughput gain is slower than linear. This is due to the higher-power dominance characteristic in power-domain NOMA known in the literature. We explicitly quantify the throughput gain for the very first time in this paper. With our analytical model, we verify the performance advantage of the proposed NOMA-RA scheme by comparing with the baseline multi-channel slotted ALOHA (MS-ALOHA), with and without capture effect. Despite the higher-power dominance effect, the maximum throughput of NOMA-RA with four power levels achieves over three times that of the MS-ALOHA. However, our analytical results also reveal the sensitivity of load on the throughput of NOMA-RA. To cope with the potential bursty traffic in mMTC scenarios, we propose adaptive load regulation through a practical user barring algorithm. By estimating the current load based on the observable channel feedback, the algorithm adaptively controls user access to maintain the optimal loading of channels to achieve maximum throughput. When the proposed user barring algorithm is applied, simulations demonstrate that the instantaneous throughput of NOMA-RA always remains close to the maximum throughput confirming the effectiveness of our load regulation.

研究动机与目标

• 解决mMTC中大规模设备接入的挑战，实现高谱效率与低时延随机接入。
• 分析在功率域复用和连续干扰消除（SIC）下基于NOMA的随机接入（NOMA-RA）的吞吐量性能。
• 设计一种自适应用户阻塞机制，以调节网络负载并维持最优信道利用率。
• 证明NOMA-RA在最大吞吐量和对流量突发性的鲁棒性方面优于传统MS-ALOHA。

提出的方法

• 使用泊松过程对每条信道上L个功率等级的用户传输进行建模。
• 推导条件吞吐量，即在U_i个用户接入信道i的条件下成功解码的数据包的期望数量。
• 通过考虑首次功率碰撞事件以及无碰撞但存在空闲功率等级的情况，构建空闲信道概率模型。
• 利用连续干扰消除（SIC）按接收信号功率顺序解调信号，实现多个用户同时传输。
• 提出一种用户阻塞算法，通过信道反馈估计当前负载，并控制接入以维持最优负载状态。
• 将分析性吞吐量模型与仿真相结合，验证在不同流量负载下的性能表现。

实验结果

研究问题

• RQ1 NOMA-RA中功率等级的数量如何影响最大系统吞吐量？
• RQ2 与基准MS-ALOHA相比，NOMA-RA在有无捕获效应情况下的理论吞吐量增益是多少？
• RQ3 NOMA-RA吞吐量对mMTC场景中流量负载变化的敏感度如何？
• RQ4 自适应用户阻塞算法是否能有效在突发性流量下维持接近最大吞吐量？
• RQ5 NOMA中高功率主导效应对系统性能和负载调节有何影响？

主要发现

• 即使在相同信道条件下，采用四个功率等级的NOMA-RA最大吞吐量也超过MS-ALOHA的三倍以上。
• 随着功率等级增加，吞吐量增益呈次线性增长，这是由于功率域NOMA中高功率主导效应所致。
• 所提出的用户阻塞算法通过基于信道反馈动态调节接入，使瞬时吞吐量保持在理论最大吞吐量的紧密范围内。
• 空闲信道概率模型准确捕捉了功率碰撞与可用空闲资源之间的权衡，从而实现有效的负载估计。
• 仿真结果证实，自适应用户阻塞机制在突发性流量下能稳定性能，防止高负载时吞吐量崩溃。
• 分析模型成功量化了吞吐量增益与负载敏感度，为mMTC网络中的实际部署提供了理论基础。