Game theory-based radio resource allocation in NOMA vehicular communication networks supported by UAV

Abstract

Vehicular communication networks are emerging as a promising technology to provide high-quality internet service such as entertainment for road users via infrastructure-to-vehicle (I2V) communication, and to guarantee road users’ safety via vehicle-to-vehicle (V2V) communication. Some technical issues that impact the performance of these networks are the lack of or poor communication paths between vehicles, and the limitation of radio resources. Unmanned aerial vehicles (UAVs) as promising solutions for supporting vehicular networks could provide communication coverage in hazardous environments and areas with no capacities for installation or maintenance of ground base stations (BSs). Also, non-orthogonal multiple access (NOMA) methods can improve spectral and energy efficiency and thereby allow more users to be connected to the desired network. In this paper, exploring the NOMA, we develop a scheme for optimum resource allocation in presence of a UAV that supports vehicular communications. Resource allocation for this scenario is formulated as a mixed-integer non-linear programming (MINLP) problem. Due to the high complexity of such problems, we propose two low-complexity near-optimal methods. First, we apply difference-of-concave-functions (DC) approximations to solve the problem in an iterative process. Next, we use Stackelberg game-based method for efficient solving, and then, closed-form expressions of optimal power allocations using KKT-conditions are derived. Simulations illustrate the effectiveness of the proposed scheme along with the Stackelberg game-based method.