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Resource Allocation and User Grouping for Sum Rate and Fairness Optimization in NOMA and IoT

机译:NOMA和IOT中总和率和公平优化的资源分配和用户分组

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In this paper, we present the joint optimization of sum rate and fairness for contention based uplink multiple access with non-orthogonal multiple access (NOMA) communication system by resource allocation and user grouping. In particular, we study the cases of many users sharing the same resources that address application of the the internet of things (IoT). The key feature of contention based multiple access is to serve multiple users at the same time and frequency. With different power levels and user grouping, it can achieve better spectral efficiency over conventional orthogonal multiple access (OMA). However, unlike the OMA system, NOMA results in additional inter-user interference (IUI). It has also been shown that, without proper resource allocation for users in the uplink NOMA, the weak users can always be in outage. In this work, we have developed algorithms on subbands assignment, user grouping, and power allocation for joint optimization of sum rate and fairness. The algorithm allocates resources iteratively to handle the IUI in each iteration. Given a number of Ns subbands allocation to each user, we could prevent starvation of poor users, e.g. cell edge users. We have also compare and analyze the sum rate and fairness performance with different combination of L and Ns. We also find that, by properly limiting the maximum number of subbands each user can use, the system could better exploit multi-user diversity to improve the sum rate and hence the energy efficiency. The numerical simulations are also conducted to verify the results.
机译:在本文中,我们提出了基于竞争的上行链路由资源分配和用户分组与非正交多址接入(NOMA)通信系统的多址和速率和公平性的联合优化。特别是,我们研究了许多用户共享相同资源的用户,该资源正在寻址应用程序互联网(物联网)。基于争用的多个访问的关键特征是同时和频率为多个用户提供服务。利用不同的功率水平和用户分组,它可以通过传统的正交多址(OMA)来实现更好的频谱效率。但是,与OMA系统不同,NOMA导致额外的用户间干扰(IUI)。还有说,没有适当的资源分配为上行链路NOMA中的用户,弱者始终处于中断。在这项工作中,我们在子带分配,用户分组和功率分配中开发了算法,用于共同优化总和率和公平性。该算法迭代地分配资源以在每次迭代中处理IUI。给予了许多n s 对每个用户的子带分配,我们可以防止饥饿穷人,例如穷人细胞边缘用户。我们还通过L和N的不同组合进行了比较和分析总和率和公平性能 s 。我们还发现,通过适当地限制每个用户可以使用的子带的最大数量,系统可以更好地利用多用户分集来提高总和率并因此提高能效。还进行了数值模拟以验证结果。

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