A Cognitive Network Architecture for Vehicle-to-Network (V2N) Communications over Smart Meters for URLLC

TL;DR

This paper proposes a smart meter-based cognitive network architecture to enhance vehicle-to-network communications in smart cities, focusing on reducing latency and increasing reliability for ultra-reliable low latency communication (URLLC).

Contribution

It introduces a novel SM-based cognitive network architecture and algorithms for vehicle association, improving V2N communication performance over traditional base station methods.

Findings

Significant reduction in communication latency.

Enhanced reliability compared to conventional architectures.

Effective utilization of underused smart meter resources.

Abstract

With the rapid advancement of smart city infrastructure, vehicle-to-network (V2N) communication has emerged as a crucial technology to enable intelligent transportation systems (ITS). The investigation of new methods to improve V2N communications is sparked by the growing need for high-speed and dependable communications in vehicular networks. To achieve ultra-reliable low latency communication (URLLC) for V2N scenarios, we propose a smart meter (SM)-based cognitive network (CN) architecture for V2N communications. Our scheme makes use of SMs' available underutilized time resources to let them serve as distributed access points (APs) for V2N communications to increase reliability and decrease latency. We propose and investigate two algorithms for efficiently associating vehicles with the appropriate SMs. Extensive simulations are carried out for comprehensive performance evaluation of our proposed architecture and algorithms under diverse system scenarios. Performance is investigated with particular emphasis on communication latency and reliability, which are also compared with the conventional base station (BS)-based V2N architecture for further validation. The results highlight the value of incorporating SMs into the current infrastructure and open the door for future ITSs to utilize more effective and dependable V2N communications.