## 2 Related Work  
According to the Cisco Visual Networking Index, a video will continue to dominate IP traffic and overall Internet traffic growth--representing 80% of all Internet traffic by 2021, up from 67% in 2016 [4]. Many research works investigated characteristics of video streaming and its ability to be adapted to channel variation nature, especially in the context of interference. However, no significant attention has been given to tackle the context of HetNet and investigate the behaviour of video streaming when interference occurs. An adaptive video streaming architecture was proposed together with a resource allocation framework in [5]. However, the main aim of the paper was to improve the Quality of Experience (QoE) with handling the resource allocation problem with Integer Linear Programming (ILP) formulation. An energy-video aware multipath transport protocol (EVIS) for HetNet has been proposed and a mathematical model developed to analyse the energy per frames for multi-homed video communication over multiple communication paths in [6]. They also developed scheduling algorithms for prioritized frame scheduling and unequal loss protection to achieve target video quality with minimum device energy consumption, showing that EVIS has a significant improvement in energy conservation, video peak signal-to-noise ratio (PSNR), end-to-end delay, and goodput compared to other works in the literature. Real-time video traffic splitting strategies were introduced for heterogeneous wireless networks composed of WiFi and cellular networks to maximize the needed energy consumption with reducing delay, solutions were presented for resource management in [7]. Lyapunov drift-plus-penalty optimization was utilized for cellular/WiFi network over a test bed implementation. The development of an energy-efficient bandwidth aggregation scheme for video transmission over wireless channel has been addressed as another challenging issue [8]. For this, an Energy-quaLity aware Bandwidth Aggregation (ELBA) scheme is introduced integrating energy-minimized rate adaptation, delay-constrained unequal protection, and quality-aware packet distribution. The method could minimize energy with regards to the quality of video streaming within imposed deadlines. Video distortion in the decision process of a multipath data transfer is introduced and a distortion-aware concurrent multipath transfer (CMT-DA) solution has been proposed to analytically formulate the data distribution over multiple communication paths to minimize the end-to-end video distortion and derive the solution based on the utility maximization theory [9]. In order to prevent freezes at the clients, a network-based framework was introduced where a network controller prioritizes the transmission of specific video segments. Furthermore, a Machine Learning (ML) engine based framework was elaborated and, under various video streaming scenarios, an ML-based framework's performance was compared with many HTTP Adaptive Streaming (HAS) based solutions [10]. For video streaming, Dynamic Adaptive Streaming over HTTP was used in both wired and wireless environments, but video quality oscillation and video freeze in wireless environments cause poor user experience. The Wireless Quality Adaptation (WQUAD) algorithm was developed to provide stable performance [11]. The presented algorithm eliminated bandwidth estimation from quality adaptation and provided video freeze prevention and high video quality on average. For each Dynamic Adaptive Streaming over Hypertext Transfer Protocol (HTTP) (DASH) user, a wireless resources allocating scheduler was presented. The scheduler worked with the QoE-aware cross-layer and improved the video quality [12]. Authors in [13] introduced an extensive review of HAS techniques across multimedia and networking domains.