Ultra-Reliable and Low-Latency Vehicular Transmission: An Extreme Value Theory Approach
arXiv:1804.06368 · doi:10.1109/LCOMM.2018.2828407
Abstract
Considering a Manhattan mobility model in vehicle-to-vehicle networks, this work studies a power minimization problem subject to second-order statistical constraints on latency and reliability, captured by a network-wide maximal data queue length. We invoke results in extreme value theory to characterize statistics of extreme events in terms of the maximal queue length. Subsequently, leveraging Lyapunov stochastic optimization to deal with network dynamics, we propose two queue-aware power allocation solutions. In contrast with the baseline, our approaches achieve lower mean and variance of the maximal queue length.
Accepted in the IEEE Communications Letters with 5 pages, 6 figures, and 2 tables
References in corpus (1)
Cited by in corpus (20)
- Distributed Federated Learning for Ultra-Reliable Low-Latency Vehicular Communications
- Dynamic Task Offloading and Resource Allocation for Ultra-Reliable Low-Latency Edge Computing
- Optimized Age of Information Tail for Ultra-Reliable Low-Latency Communications in Vehicular Networks
- Meta-Reinforcement Learning Based Resource Allocation for Dynamic V2X Communications
- Ultra-Reliable Low-Latency Vehicular Networks: Taming the Age of Information Tail
- Ultra-Reliable and Low-Latency Vehicular Communication: An Active Learning Approach
- Taming the Tail of Maximal Information Age in Wireless Industrial Networks
- Risk-Sensitive Task Fetching and Offloading for Vehicular Edge Computing
- Non-Stationary Wireless Channel Modeling Approach Based on Extreme Value Theory for Ultra-Reliable Communications
- Spatiotemporal Analysis on Broadcast Performance of DSRC with External Interference in 5.9 GHz Band
- Multivariate Extreme Value Theory Based Channel Modeling for Ultra-Reliable Communications
- URLLC-Aware Proactive UAV Placement in Internet of Vehicles
- Study on MCS Selection and Spectrum Allocation for URLLC Traffic under Delay and Reliability Constraint in 5G Network
- Wireless Channel Modeling Based on Extreme Value Theory for Ultra-Reliable Communications
- Energy Efficient HARQ for Ultrareliability via Novel Outage Probability Bound and Geometric Programming
- Resource Allocation for Secure URLLC in Mission-Critical IoT Scenario
- Massive-MIMO MF Beamforming with or without Grouped STBC for Ultra-Reliable Single-Shot Transmission Using Aged CSIT
- Dependence Control for Reliability Optimization in Vehicular Networks
- Rate Maximization in Vehicular uRLLC with Optical Camera Communications
- Deep Reinforcement Learning Based Mode Selection and Resource Allocation for Cellular V2X Communications