[Paper Review] Cellular V2X in Unlicensed Spectrum: Harmonious Coexistence with VANET in 5G systems

Pengfei Wang, Boya Di+3 more|arXiv (Cornell University)|Dec 13, 2017

Vehicular Ad Hoc Networks (VANETs)18 references3 citations

TL;DR

This paper proposes an energy sensing-based spectrum sharing scheme and a dynamic vehicle-resource matching algorithm (DV-RMA) to enable harmonious coexistence between cellular V2X and VANET users in unlicensed 5G spectrum. By modeling resource allocation as a two-sided many-to-many matching with peer effects and leveraging semi-persistent scheduling, the scheme maximizes active cellular V2X users while minimizing interference to VANETs, achieving convergence with bounded complexity.

ABSTRACT

With the increasing demand for vehicular data transmission, limited dedicated cellular spectrum becomes a bottleneck to satisfy the requirements of all cellular vehicle-to-everything (V2X) users. To address this issue, unlicensed spectrum is considered to serve as the complement to support cellular V2X users. In this paper, we study the coexistence problem of cellular V2X users and vehicular ad-hoc network~(VANET) users over the unlicensed spectrum. To facilitate the coexistence, we design an energy sensing based spectrum sharing scheme, where cellular V2X users are able to access the unlicensed channels fairly while reducing the data transmission collisions between cellular V2X and VANET users. In order to maximize the number of active cellular V2X users, we formulate the scheduling and resource allocation problem as a two-sided many-to-many matching with peer effects. We then propose a dynamic vehicle-resource matching algorithm (DV-RMA) and present the analytical results on the convergence time and computational complexity. Simulation results show that the proposed algorithm outperforms existing approaches in terms of the performance of cellular V2X system when the unlicensed spectrum is utilized.

Motivation & Objective

• To address the growing demand for vehicular data transmission by offloading cellular V2X traffic to unlicensed spectrum.
• To enable fair and efficient coexistence between cellular V2X and VANET users sharing the same unlicensed spectrum.
• To minimize interference to VANET users while maximizing the number of active cellular V2X users.
• To reduce control overhead through semi-persistent scheduling in dynamic vehicular environments.
• To account for vehicle mobility and channel condition variations in resource allocation.

Proposed method

• Designs an energy sensing-based spectrum sharing mechanism to allow cellular V2X users to access unlicensed channels based on real-time channel occupancy.
• Models the scheduling and resource allocation problem as a two-sided many-to-many matching with peer effects to optimize user fairness and system throughput.
• Proposes the Dynamic Vehicle-Resource Matching Algorithm (DV-RMA) using preference lists and incompatible lists to ensure convergence.
• Integrates semi-persistent scheduling (SPS) to reduce signaling overhead in time-varying vehicular networks.
• Incorporates vehicle velocity into channel condition estimation to adapt to dynamic topologies.
• Uses geometric interference modeling to quantify overlapping interference ranges between vehicles based on distance and transmission range.

Experimental results

Research questions

• RQ1 How can cellular V2X and VANET users coexist fairly in unlicensed 5G spectrum without causing excessive interference?
• RQ2 What is the optimal resource allocation strategy that maximizes active cellular V2X users while minimizing interference to VANETs?
• RQ3 How can dynamic vehicle mobility and channel variations be effectively modeled and incorporated into the resource allocation process?
• RQ4 What is the convergence behavior and computational complexity of a matching-based algorithm in this vehicular coexistence scenario?
• RQ5 Can a semi-persistent scheduling approach reduce control overhead in high-mobility vehicular networks?

Key findings

• The proposed DV-RMA algorithm achieves convergence to a pairwise stable matching in finite time, ensuring stable and fair resource allocation.
• The computational complexity of DV-RMA is bounded by O((N+M)(K+Ku)²T²), where N and M are the number of vehicles and time-frequency resources, respectively.
• Simulation results demonstrate that the proposed scheme outperforms existing approaches in terms of the number of active cellular V2X users in unlicensed spectrum.
• The energy sensing mechanism effectively reduces data transmission collisions between cellular V2X and VANET users.
• The integration of semi-persistent scheduling significantly reduces signaling overhead in dynamic vehicular environments.
• The geometric interference model accurately captures the overlapping interference range between vehicles based on distance and transmission range.