Joint Path Selection and Rate Allocation Framework for 5G Self-Backhauled mmWave Networks
arXiv:1805.07743 · doi:10.1109/TWC.2019.2904275
Abstract
Owing to severe path loss and unreliable transmission over a long distance at higher frequency bands, we investigate the problem of path selection and rate allocation for multi-hop self-backhaul millimeter wave (mmWave) networks. Enabling multi-hop mmWave transmissions raises a potential issue of increased latency, and thus, in this work we aim at addressing the fundamental questions: how to select the best multi-hop paths and how to allocate rates over these paths subject to latency constraints? In this regard, we propose a new system design, which exploits multiple antenna diversity, mmWave bandwidth, and traffic splitting techniques to improve the downlink transmission. The studied problem is cast as a network utility maximization, subject to an upper delay bound constraint, network stability, and network dynamics. By leveraging stochastic optimization, the problem is decoupled into: path selection and rate allocation sub-problems, whereby a framework which selects the best paths is proposed using reinforcement learning techniques. Moreover, the rate allocation is a nonconvex program, which is converted into a convex one by using the successive convex approximation method. Via mathematical analysis, we provide a comprehensive performance analysis and convergence proofs for the proposed solution. Numerical results show that our approach ensures reliable communication with a guaranteed probability of up to , and reduces latency by and as compared to baseline models. Furthermore, the results showcase the key trade-off between latency and network arrival rate.
arXiv commentKeywords: URLLC, mmWave communications, latency, reliability, 5G, stochastic optimization, non-convex optimization, reinforcement learning. arXiv admin note: text overlap with arXiv:1802.02085
References in corpus (16)
- Spatially Sparse Precoding in Millimeter Wave MIMO Systems
- Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems
- Massive MIMO: Ten Myths and One Critical Question
- Millimeter Wave Beamforming for Wireless Backhaul and Access in Small Cell Networks
- Limited Feedback Hybrid Precoding for Multi-User Millimeter Wave Systems
- Towards Low-Latency and Ultra-Reliable Virtual Reality
- On the Joint Impact of Beamwidth and Orientation Error on Throughput in Directional Wireless Poisson Networks
- Ultra-Reliable and Low Latency Communication in mmWave-Enabled Massive MIMO Networks
- Quality-Of-Service Provisioning in Decentralized Networks: A Satisfaction Equilibrium Approach
- Multi-Connectivity in 5G mmWave Cellular Networks
- Hierarchical Interference Mitigation for Massive MIMO Cellular Networks
- Joint load balancing and interference mitigation in 5G HETNETS
- Gbps User Rates Using mmWave Relayed Backhaul with High Gain Antennas
- Backhaul-Aware Interference Management in the Uplink of Wireless Small Cell Networks
- Ultra-Reliable Communication in 5G mmWave Networks: A Risk-Sensitive Approach
- Matching Theory for Backhaul Management in Small Cell Networks with mmWave Capabilities