Beam-align: distributed user association for mmWave networks with multi-connectivity

TL;DR

This paper introduces BEAM-ALIGN, a heuristic user association scheme for mmWave 5G networks that optimally balances multi-connectivity and beamforming, improving capacity and robustness under various conditions.

Contribution

It formulates an optimal user association problem considering beamforming and multi-connectivity, and proposes BEAM-ALIGN, a polynomial-time heuristic that performs near-optimally using only local information.

Findings

BEAM-ALIGN achieves near-optimal per-user capacity and satisfaction.

It outperforms traditional SNR-based schemes in various scenarios.

The optimal degree of multi-connectivity varies with network conditions.

Abstract

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.