QoS-Driven Video Uplinking in NOMA-Based IoT

TL;DR

This paper proposes a novel NOMA and SVC integrated system for IoT video uplinking, formulating and solving a power allocation problem to enhance QoS and energy efficiency, validated through simulations.

Contribution

It introduces a new power allocation algorithm for NOMA-based IoT video uplink that maximizes QoS, addressing the non-convex optimization challenge.

Findings

Proposed algorithm outperforms existing schemes in QoS.

Enhanced energy efficiency in video uplinking.

Effective handling of non-convex optimization problem.

Abstract

In recent years, with the explosive growth of visual sensors and a large number of related video applications in Internet of Things (IoT), massive video data is generated by IoT devices. Since the volume of video data is far greater than traditional data in IoT, it is challenging to ensure high Quality of Service (QoS) for video uplinking in IoT. To address this challenge, we integrate non-orthogonal multiple access (NOMA) and scalable video coding (SVC) in IoT. To improve the video quality, we formulate a power allocation problem to maximize the average QoS in the proposed integrated system. Due to that the problem is non-convex, we transform it into a monotonic problem based on its hidden monotonicity. Then a power allocation algorithm based on polyblock outer approximation is proposed to solve the problem effectively. Finally, simulation results demonstrate that the proposed algorithm outperforms existing OMA and NOMA based schemes for video uplinking in IoT in terms of QoS and energy efficiency.