[Paper Review] Joint Relaying and Spatial Sharing Multicast Scheduling for mmWave Networks

Gek Hong, Sim+4 more|arXiv (Cornell University)|Jul 30, 2019

Millimeter-Wave Propagation and Modeling26 references4 citations

TL;DR

This paper proposes mmDiMu, a distributed multicast scheduling algorithm for mmWave networks that jointly exploits relaying and spatial reuse to minimize multicast completion time. By leveraging directional beams and relay nodes, mmDiMu reduces completion time by up to 96.21% compared to sub-6GHz-based methods and 78.22% compared to adaptive beamwidth schemes, achieving near-optimal performance with scalable, distributed operation.

ABSTRACT

Millimeter-wave (mmWave) communication plays a vital role to efficiently disseminate large volumes of data in beyond-5G networks. Unfortunately, the directionality of mmWave communication significantly complicates efficient data dissemination, particularly in multicasting, which is gaining more and more importance in emerging applications (e.g., V2X, public safety). While multicasting for systems operating at lower frequencies (i.e., sub-6GHz) has been extensively studied, they are sub-optimal for mmWave systems as mmWave has significantly different propagation characteristics, i.e., using the directional transmission to compensate for the high path loss and thus promoting spectrum sharing. In this paper, we propose novel multicast scheduling algorithms by jointly exploiting relaying and spatial sharing gains while aiming to minimize the multicast completion time. We first characterize the min-time mmWave multicasting problem with a comprehensive model and formulate it with an integer linear program (ILP). We further design a practical and scalable distributed algorithm named mmDiMu, based on gradually maximizing the transmission throughput over time. Finally, we carry out validation through extensive simulations in different scales and the results show that mmDiMu significantly outperforms conventional algorithms with around 95% reduction on multicast completion time.

Motivation & Objective

• Address the challenge of inefficient multicast dissemination in mmWave networks due to high path loss and directional beamforming.
• Overcome limitations of sub-6GHz multicast scheduling, which assume omnidirectional transmission and are suboptimal for mmWave.
• Design a scalable, distributed algorithm that jointly optimizes relay usage and spatial reuse of directional beams to minimize multicast completion time.
• Enable reliable scheduling in high-density mmWave networks with blockages and mobility by leveraging sub-6GHz for control signaling.

Proposed method

• Formulate the min-time mmWave multicast problem as an Integer Linear Program (ILP) to model joint relay selection, beamforming, and scheduling decisions.
• Design mmDiMu, a distributed, greedy algorithm that incrementally maximizes throughput by selecting high-gain transmission links at each time slot.
• Use a hybrid scheduling approach: combine unicast and multicast transmissions via relays to improve reachability and data rates.
• Leverage spatial reuse by allowing concurrent transmissions when beams do not interfere, exploiting the directional nature of mmWave.
• Integrate a synchronization mechanism where scheduling information is disseminated via robust sub-6GHz links (e.g., IEEE 802.11ad FST or DSRC) to ensure coordination.
• Model blockages via link discovery and beam training; dynamically exclude blocked links from scheduling while ensuring data delivery via relays.

Experimental results

Research questions

• RQ1 How can relay nodes and spatial reuse be jointly exploited in mmWave multicast to reduce completion time?
• RQ2 To what extent can a distributed algorithm match the performance of an optimal ILP formulation in large-scale mmWave networks?
• RQ3 How does the proposed scheme compare to conventional sub-6GHz multicast scheduling and adaptive beamwidth methods in terms of completion time?
• RQ4 What is the impact of interference in high-density mmWave networks when spatial reuse is enabled without explicit interference minimization?
• RQ5 How can scheduling be synchronized in mmWave networks despite the high path loss and blockage vulnerability of mmWave links?

Key findings

• The proposed ILP formulation achieves optimal multicast scheduling but suffers from poor scalability due to high computational complexity.
• The distributed mmDiMu algorithm achieves completion times within 3.79% of the optimal ILP solution, demonstrating near-optimality.
• mmDiMu reduces multicast completion time by up to 96.21% compared to conventional sub-6GHz-based multicast scheduling algorithms.
• Compared to an adaptive beamwidth scheme (Adapt), mmDiMu achieves up to 78.22% reduction in completion time in mmWave environments.
• Despite excluding interference minimization from the objective, the total interference remains low at only 5% even with 45° beamwidths in high-density scenarios.
• The algorithm maintains robustness under blockages by dynamically rerouting data through non-blocked relay nodes, ensuring end-to-end delivery.