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.

翻译：由于6 GHz以下频段的频谱不足以满足5G用例的高带宽需求，5G网络将其运营扩展至毫米波频段。然而，在这些频段上的运行必须应对高穿透损耗和易受障碍物阻挡的挑战。波束成形与多连接性（MC）相结合可以共同缓解这些挑战。但是，设计一种充分利用这两个特性的最优用户关联方案并非易事，且计算成本高昂。先前的研究要么为所有用户考虑固定的MC度，要么忽略了波束成形。受“毫米波网络中每个用户的最优MC度是多少”这一问题的驱动，我们提出了一种考虑波束成形和MC、以最大化吞吐量为目标的用户关联方案。我们的数值分析表明，不存在一个适用于所有情况的最优MC度；它取决于用户数量、用户的速率需求、位置以及基站（BS）的最大激活波束数。基于最优关联，我们设计了BEAM-ALIGN：一种具有多项式时间复杂度O(|U|log|U|)的高效启发式算法，其中|U|为用户数。此外，BEAM-ALIGN仅使用基站的本地信息——即用户在基站处接收到的信号质量。与先前工作不同，BEAM-ALIGN考虑了波束成形、多连接性和视距概率。通过仿真，我们表明BEAM-ALIGN在每用户容量和满意度方面表现接近最优，同时其性能优于常用的基于信号与干扰加噪声比（SINR）的关联方案。我们进一步证明，BEAM-ALIGN在各种挑战性场景下均具有稳健的性能：存在障碍物、降雨以及用户聚集的情况。