# Performance Analysis of Cooperative V2V and V2I Communications under Correlated Fading

## TL;DR

This paper analyzes the performance of cooperative V2V and V2I communications under correlated fading, deriving closed-form error probability expressions and proposing a game-theoretic approach to optimize transmit power in vehicular networks.

## Contribution

It introduces a realistic correlated fading model for RSU antennas, derives analytical expressions for packet error probability, and formulates a Stackelberg game to optimize transmit power.

## Key findings

- Packet error probability varies with fading correlation and number of helper vehicles.
- Closed-form expressions enable performance assessment under different fading scenarios.
- Game-theoretic approach effectively determines optimal transmit power and pricing.

## Abstract

Cooperative vehicular networks will play a vital role in the coming years to implement various intelligent transportation-related applications. Both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications will be needed to reliably disseminate information in a vehicular network. In this regard, a roadside unit (RSU) equipped with multiple antennas can improve the network capacity. While the traditional approaches assume antennas to experience independent fading, we consider a more practical uplink scenario where antennas at the RSU experience correlated fading. In particular, we evaluate the packet error probability for two renowned antenna correlation models, i.e., constant correlation (CC) and exponential correlation (EC). We also consider intermediate cooperative vehicles for reliable communication between the source vehicle and the RSU. Here, we derive closed-form expressions for packet error probability which help quantify the performance variations due to fading parameter, correlation coefficients and the number of intermediate helper vehicles. To evaluate the optimal transmit power in this network scenario, we formulate a Stackelberg game, wherein, the source vehicle is treated as a buyer and the helper vehicles are the sellers. The optimal solutions for the asking price and the transmit power are devised which maximize the utility functions of helper vehicles and the source vehicle, respectively. We verify our mathematical derivations by extensive simulations in MATLAB.