## 1 Introduction  
Networks of the future will be heterogeneous as they will shape the landscape of the wireless environment through offering different kinds of services like data rates, Quality of Service (QoS) capabilities and mobility. Such kind of network is introduced in Long-Term Evolution Advanced (LTE-A). The reason behind introducing Heterogeneous Networks (HetNet) LTE-A is to cope with the increasing number of mobile broadband data subscribers and bandwidth-intensive services competing for limited radio resources in 5G networks [1]. Since the sole macrocell cannot meet the requirements of mobile users in terms of QoS, HetNet architecture consists of different types of Radio Access Networks (RANs) or cells: a collocated macrocell, picocells, femtocells and relay nodes. In our case, we focus on the integration of femtocells and macrocells as a case study. However, in the scenario when the Macrocell Base Station (MBS) and Femtocell Base Station (FBS) use the same spectrum, a cross-tier interference will occur and will cause a severe interference to the Macrocell User Equipment (MUEs), especially when they are not registered with the operator of the FBS. The major issue that should be considered is how to mitigate the interference in a scenario when FBSs use the Close Subscriber Group (CSG) for Femtocell User Equipments (FUEs) and cause a severe interference to MUEs, leading to a bad quality of Signal-to-Interference Noise Ratio (SINR) received by the MUEs [2]. The Downlink (DL) direction of LTE specifications uses an Orthogonal Frequency Division Multiple Access (OFDMA) modulation technique where the basic unit of resource allocation is called Resource Block (RB), and it is assigned by the scheduler every 1 ms [3]. The bad quality of the SINR affects the QoS of the different ongoing applications regardless of their type in HetNet scenario. However, in this article, we are more focused on the Video Streaming application as an example of an application suffering from bad channel quality caused by interference. We selected the video streaming because it has a special character that overcomes the problem of interference by Scalable Video Coding (SVC) technique, which is the Annex G extension of the H.264/MPEG-4 AVC video compression standard. It implements the bit rate adaptivity. It encodes the raw video clip into a base layer and a number of enhancement layers with different priorities. Naturally, the base layer has the highest priority since it contains the video bits with the highest importance, which can provide a minimum video quality. The enhancement layers with lower priorities may be progressively encoded to further refine the quality of the base-layer stream. Scalable video coding and adaptive streaming techniques can be jointly combined to accomplish effectively the best possible quality of video streaming services. Hence, we can dynamically adjust the number of SVC layers depending on the current link status. However, before using any mechanism of adaptation between video rate and link status, it is important to know the link status that is playing a great role for delivering a good quality video service. Since, in our context, the user channel is experiencing an interference, it should be mitigated. Once the quality of channel is known, the rate of the video should be adapted to it. In this article, we propose a complete framework of HetNet Integration between macrocell and femtocells. Since such integration raises the challenge of interference, we then suggest a solution based on power adjustment in order to mitigate interference. A solution is suggested based on a distributed Power Allocation (PA) method to reduce the cross-tier interference caused to the MUEs by the FBSs. Firstly, we classify the interfering femtocells into clusters depending on the Received Signal Strengths (RSSs) reports that are sent periodically by MUEs on the Uplink (UL) transmission. This will help each FBS to identify the average number of MUE victims of interference.