# Optimization of Speed and Network Deployment for Reliable V2I Communication in the Presence of Handoffs and Interference

arXiv: https://arxiv.org/abs/2307.06852 · HTML: https://mlsanity.com/paper/2307.06852/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 May 2023.

## Built on by (most cited first, 3 of 3)

- [Multi-UAV Speed Control with Collision Avoidance and Handover-aware Cell Association: DRL with Action Branching](https://mlsanity.com/paper/2307.13158/) (2023)
- [Generalized Multi-Objective Reinforcement Learning with Envelope Updates in URLLC-enabled Vehicular Networks](https://mlsanity.com/paper/2405.11331/) (2024)
- [Hierarchical LLM-Driven Control for HAPS-Assisted UAV Networks: Joint Optimization of Flight and Connectivity](https://mlsanity.com/paper/2605.11509/) (2026)

## Abstract (arXiv)

Vehicle-to-infrastructure (V2I) communication is becoming indispensable for successful roll-out of connected and autonomous vehicles (CAVs). While increasing the CAVs' speed improves the average CAV traffic flow, it increases communication handoffs (HOs) thus reducing wireless data rates. Furthermore, unplanned density of active base-stations (BSs) may result in severe interference which negatively impacts CAV data rate. In this letter, we first characterize macroscopic traffic flow by considering log-normal distribution of the spacing between CAVs. We then derive novel closed-form expressions for the exact HO-aware rate outage probability and ergodic capacity in a large-scale network with interference. Then, we formulate a traffic flow maximization problem to optimize the speed of CAVs and deployment density of BSs with HO-aware rate constraints and collision avoidance constraints. Our numerical results validate the closed-form analytical expressions, extract useful insights about the optimal speed and BS density, and highlight the key trade-offs between the HO-aware data rates and CAV traffic flow.