الفهرس | Only 14 pages are availabe for public view |
Abstract Content caching in Device-to-Device (D2D) wireless cellular network can be considered an attractive solution to decrease network load during peak time hence improve network performance. The literature has a strong evidence that user behavior is highly predictable as well as mobility patterns of users. Cellular networks can track, learn and predict user preferences and mobility patterns. In such network, predicting users’ movement pattern allows proactive caching to alleviate its congestion leading to load decrease. Optimizing caching process is one important solution to enhance network performance and thus increase offloading probability. Caching some data items in the off-peak times moves some of the network load to user nodes and reduces service cost. Moreover, D2D communications permit users to deliver their pro active dewnloads with requester users in their neighborhood area. Therefore, users can find their request data either with other helper users around them or in their local caches. Nonetheless, harnessing user mobility information enhances networks caching decisions and reduces its cost. The user’s trajectories information allows the network to predict their presence probability in some popular locations. Finding an optimal caching strategy eases the network congestion in these popular locations and enhances the network performance. This thesis introduces a study to cover the capabilities of D2D caching cellular networks and investigates how to improve its performance. The research consists of three main directions, in first, take advantage of user behavior predictability to offload the network data. Secondly, beneficially the relations between users to introduce a content storing and sharing among other users. Lastly, leveraging the information about user locations and hence Quality of Service (QoS) parameters to enhance caching strategy and the overall throughput. Starting by investigating how to contribute the user behavior predictability to store some data files during . times for a possible request throughout peak times. A caching policy strategy is introduced where the network jointly recognizes group mobility and user preferences using rewarding system to solve the caching optimization problem. Hence, optimization algorithms is used to minimize the overall network load by optimizing the amount of data cached in users devices. Further, the relations between users’ requests and QoS parameters are introduced in terms of Signal to Interference plus Noise Ratio (SINR) and energy consumed from helper users’ batteries. Simulations are carried out to evaluate performance of the presented optimal caching policy with and without QoS constraints. Moreover, joint channel and power allocation for D2D communications underlaying 5G networks is discussed including caching policy consideration. Here is, Uplink (UL) resource reuse between multiple Cellular Users (CUs) and multiple D2Ds connections located in single Main Base-Station (MBS) and multiple Small Base Stations (SBSs) is investigated. In order to gain from allocating the UL spectrum, resource and power allocation algorithm is designed to maximize the overall network sum rate while guaranteeing QoS requirements for both CUs and D2D links. Finally, simulation results show that the proposed algorithm efficiently improve the overall network performance under the consideration of different network parameters. |