Abstract
In recent years, the concept of non-orthogonal multiple access (NOMA) has gathered much attention due to its potential to offer high spectral efficiency, present user fairness and grant free access to sixth generation (6G) vehicular networks. This paper proposes a new optimization framework for NOMA-enabled cooperative vehicular network. In particular, we jointly optimize the vehicle paring, channel assignment, and power allocation at source and relaying vehicles. The objective is to maximize the sum rate of the system subject to the power allocation, minimum rate, relay battery lifetime and successive interference cancelation constraints. To solve the joint optimization problem efficiently, we adopt duality theory followed by Karush-Kuhn-Tucker (KKT) conditions, where the dual variables are iteratively computed through sub-gradient method. Two less complex suboptimal schemes are also presented as the benchmark cooperative vehicular schemes. Simulation results compare the performance of the proposed joint optimization scheme compared to the other benchmark cooperative vehicular schemes.
Highlights
The exponentially growing number of connected vehicles has brought an unconventional change in sixth generation (6G) intelligent transportation systems [1], [2]
Orthogonal multiple access (OMA) techniques [4] have served as successful multiplexing scheme in existing transportation networks, it seems less capable to meet the requirements of the large-scale vehicular networks [5]
We provide a new joint optimization framework to improve the performance of NOMAenabled vehicular network
Summary
The exponentially growing number of connected vehicles has brought an unconventional change in sixth generation (6G) intelligent transportation systems [1], [2]. (Corresponding authors: Wali Ullah Khan and Omer Waqar) have been proposed ranging from exploring heterogeneous networks [6] to deploying multi antenna systems, among which non-orthogonal multiple access (NOMA) techniques have emerged as the attractive candidates and key enablers of advance vehicular networks [7]. It has been well-established that the NOMA techniques outperform the conventional OMA technologies in terms of spectral efficiency, quality of services (QoS) requirements and fairness [8], [9]. Since power domain NOMA offers higher flexibility and less complexity compared to code domain NOMA techniques [14], it has attracted key focus in many recent works [15]–[18]
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