论文标题
Beam-Align：具有多连通性的MMWave网络的分布式用户协会
Beam-align: distributed user association for mmWave networks with multi-connectivity
论文作者
论文摘要
由于低于6 GHz频段的频谱不足以满足5G用例的高带宽要求，因此5G网络将其操作扩展到MMWave频段。但是，这些频段的操作必须应对高渗透损失和阻断物体的敏感性。波束形成和多连通性（MC）可以共同缓解这些挑战。但是，要设计这样的最佳用户协会方案，利用这两个功能是非平凡且计算上昂贵的。先前的研究要么考虑所有用户的固定MC学位，要么忽略了波束成形。在问题的驱动下，MMWave网络中每个用户的MC最佳程度是什么，我们制定了一个用户关联方案，该方案可以最大化吞吐量考虑光束形成和MC。我们的数值分析表明，没有一定程度的最佳MC。这取决于用户的数量，其速率要求，位置和最大活性梁的最大数量在最佳关联上，我们设计了beam-Align：一种具有多项式时间复杂性的有效启发式o（| u | log | u |），其中| u |是用户数。此外，Beam -Align仅使用本地BS信息 - 即用户接收的信号质量。与先前的作品不同，Beam-Align认为束成绩，多连接性和视线可能性的可能性。通过模拟，我们表明，横梁对梁的能力和满意度的表现接近最佳，而基于频繁使用的信号到基于互换和基于噪声比例的关联方案则表现出色。然后，我们证明在各种具有挑战性的情况下，Beam-Align具有强大的性能：阻滞剂，雨水和聚类用户的存在。
Since the spectrum below 6 GHz bands is insufficient to meet the high bandwidth requirements of 5G use cases, 5G networks expand their operation to mmWave bands. However, operation at these bands has to cope with a high penetration loss and susceptibility to blocking objects. Beamforming and multi-connectivity (MC) can together mitigate these challenges. But, to design such an optimal user association scheme leveraging these two features is non-trivial and computationally expensive. Previous studies either considered a fixed MC degree for all users or overlooked beamforming. Driven by the question what is the optimal degree of MC for each user in a mmWave network, we formulate a user association scheme that maximizes throughput considering beam formation and MC. Our numerical analysis shows that there is no one-size-fits-all degree of optimal MC; it depends on the number of users, their rate requirements, locations, and the maximum number of active beams at a BS.Based on the optimal association, we design BEAM-ALIGN: an efficient heuristic with polynomial-time complexity O(|U|log|U|), where |U| is the number of users. Moreover, BEAM-ALIGN only uses local BS information - i.e. the received signal quality at the user. Differing from prior works, BEAM-ALIGN considers beamforming, multiconnectivity and line-of-sight probability. Via simulations, we show that BEAM-ALIGN performs close to optimal in terms of per-user capacity and satisfaction while it outperforms frequently-used signal-to-interference-and-noise-ratio based association schemes. We then show that BEAM-ALIGN has a robust performance under various challenging scenarios: the presence of blockers, rain, and clustered users.
