Title: Improving Fairness for Cell-Free Massive MIMO Through Interference-Aware Massive Access Show Chinese title

Title: 通过干扰感知的大规模接入提高无蜂窝大规模MIMO的公平性

Abstract: 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. Show Chinese abstract

Abstract: 无蜂窝大规模多输入多输出（CF mMIMO）通过协调比用户设备（UEs）更多的接入点（APs）来提供良好的干扰管理。 当UE的数量接近AP的数量并远超过导频的数量时，确定哪些AP应为哪些UE使用哪些导频变得具有挑战性。 在这样的大规模接入场景中，需要在频谱效率（SE）和实现复杂性之间取得更好的折中。 本文提出了一种干扰感知的大规模接入（IAMA）方案，通过利用大尺度干扰特征，在CF mMIMO中实现了AP-UE关联和导频分配的联合优化。 我们提出了一种干扰感知奖励作为新的性能指标，并利用它开发了两种迭代算法来优化关联和导频分配。 数值结果表明，在用户公平性和平均SE方面，我们的IAMA方案明显优于基准方案。