Cooperative Content Caching With Green Communication For Next Generation Cellular Networks

Mobile applications and social networks tends to enhance the needs for high-quality content access.To address the expeditious growing demand for data services in 5G cellular networks,it is important to develop an efficient content caching and distribution techniques,aiming to significantly reduce redundant data transmission and thus improve the efficiency of the networks.Caching has emerged as a vital tool in modern communication systems for reducing peak data rates by allowing popular files to be pre-fetched and then stored at the edge of the networks.Caching at small cell base stations has recently been proposed to avoid bottlenecks in the limited capacity backhaul connection link to the core network.This dissertation explores the significant enablers of 5G wireless networks leveraging small cell deployments,namely proactive caching,cooperative caching,energy efficient and green communication cache.For predicting the popularity of the content,we need to analyze the behavior of the user,understanding collectively the behavior beneficial for content trend forecasting and improve network performance.The proposed model predicts the intensity of human emotions through social media?Twitter?and the classifier evaluates the features which are related to user behaviors and finally,values of features are pushed to the user profile.We further demonstrate how emotions extracted from Twitter can be utilized to improve the forecasting,describing things in a new way which can further be exploited as an optimization basis for networks performance enhancement.Afterward,in this dissertation,we tailored a more practical approach which has developed optimal collaborative content caching and delivery policy,where a geographical cluster model is designed for content retrieval across the collaborative small cell base stations?SBS?and replacement of cache framework.Furthermore,we divided the SBS caching storage space into two equal parts:one is local and the other is global content cache,also proposed an algorithm to minimize the content caching delay,transmission cost and backhaul bottleneck on the edge of networks.It is anticipated that energy harvesting and self-powered small base stations are the fundamental part of next-generation cellular networks.However,uncertainties in energy are the main reason to adopt energy efficient power control schemes to reduce SBS energy consumption and ensure the quality of services for users.Using the edge cooperative caching such energy efficient design can also be achievable which reduces the usage of the capacity limited SBSs backhaul and the energy consumption.To support the huge power demand of cellular network,renewable energy harvesting technologies can be leveraged.In addition to this,power supply to the infrastructures is the main challenge to the mobile network operators?MNOs?especially in terms of sustainability,economic optimum and green energy in developing countries for the growth of cellular networks.Renewable energy?RE?based solutions for cellular operators not only provide numerous profits but it also reduces the overall CO₂ emissions.Simulation results and analysis provide key insights that the proposed neighbor SBSs cooperative caching scheme brings a substantial improvement regarding content availability,cache storage capacity at the edge of cellular networks and also enhance the energy efficiency.Cache enabled system appreciable increases the network performance,energy efficiency and is a viable solution for the ever-evolving capacity demands in wireless communication landscape.Also,energy harvesting and self-powered base stations are the fundamental part of next generation?5G?cellular networks.