论文标题
通过干扰可见的大规模进入，改善无细胞的大型MIMO的公平性
Improving Fairness for Cell-Free Massive MIMO Through Interference-Aware Massive Access
论文作者
论文摘要
与用户设备（UES）相比，通过协调更多的访问点（AP），无单元的大量多输入多输出（CF MMIMO）提供了良好的干扰管理。当UE近似AP的数量并远远超过飞行员数量时，确定哪些AP应为哪些AP服务于哪些UES。与以前的工作相比，在这种庞大的访问方案中，需要更好地妥协光谱效率（SE）和实施简单性。本文提出了通过利用大规模干扰功能来实现CF MMIMO的联合AP-EUS结合和试点分配的干扰感知方案（IAMA）方案。我们提出了一种干涉感知的奖励作为一种新型的性能指标，并使用它来开发两种迭代算法来优化关联和试点分配。数值结果表明，就用户公平性和平均SE而言，我们的IAMA方案比基准方案的显着优势。
Cell-free massive multiple-input multiple-output (CF mMIMO) provides good interference management by coordinating many more access points (APs) than user equipments (UEs). It becomes challenging to determine which APs should serve which UEs with which pilots when the number of UEs approximates the number of APs and far exceeds the number of pilots. Compared to the previous work, a better compromise between spectral efficiency (SE) and implementation simplicity is needed in such massive access scenarios. This paper proposes an interference-aware massive access (IAMA) scheme realizing joint AP-UE association and pilot assignment for CF mMIMO by exploiting the large-scale interference features. We propose an interference-aware reward as a novel performance metric and use it to develop two iterative algorithms to optimize the association and pilot assignment. The numerical results show a prominent advantage of our IAMA scheme over the benchmark schemes in terms of the user fairness and the average SE.
