الفهرس 
Chapter 1 IntroductionOnly 14 pages are availabe for public view
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Abstract
The unexpected explosion of mobile data traffic has led to that the cellular networks are overloaded. Therefore, in highly loaded areas, the mobile users will have to face degraded services, such as low data rates and low quality of services. A more effective approach is to offload the mobile data to another network or technology. The mobile operators are interested for data offloading to increase their network capacity while maintaining a good quality of service for users. Currently, many interests are focused on Wi-Fi networks to offload traffic as it uses unlicensed spectrum and can address the traffic demand. So, mobile operators can leverage the load from their networks using a low cost and easy to install technology, which is referred to as WiFi offloading. In this context, Long term evolution (LTE) wireless local area networks (WLAN) aggregation (LWA) has recently emerged as a promising technology for mobile data offloading, in which the data packets of a user’s service are split over both LTE and WiFi networks simultaneously. In this thesis, the first proposal considers a non-collocated LWA scenario in which the LTE eNB is connected to WLAN infrastructure through wireless backhaul link adopting adaptive modulation. A closed mathematical formula for the delay over wireless backhaul is obtained and its effect on the offloading and aggregation processes in LWA is investigated. Based on the delay analysis of the backhaul, a scheduling technique with embedded mode selection criteria for LWA is proposed. The technique is designed to maximize the amount of data traffic that can be offloaded to WLAN while considering the user’s service time constraint and hence gain the maximum benefit from the cost effective WiFi networks.
Secondly, an efficient dynamic traffic splitting technique for LWA network architecture is proposed. The key direction of this technique is to provide proportional load balancing while enabling packet scheduling at the PDCP layer based on the estimation of sojourn time delay on both LTE and Wi-Fi radio links. Therefore, a closed form for the traffic splitting ratio is derived such that proportional load balancing across the two radio access networks (LTE and Wi-Fi) is achieved. The packet streams are proportionally scheduled on both radio links in such a way that the reordering delay is compensated, avoiding throughput degradation.
Then, we study the effect of the network’s backhaul on the selection decision for this network. We are dealing with a single and multi-hop wireless backhaul transmission, in which a WiFi mesh network is considered as a backhaul network for WiFi users, under different circumstances and
different numbers of associated users. The user priorities and requirements are taken into account during the network selection process. Also, the Technique for order Preference by Similarity to Ideal Solution (TOPSIS) is used for arranging the available networks to the user, and associate him with the best available one to satisfy his requirements and the system’s QoS performance.
After that, a multi-RAT HetNet is considered, where three mode categories are defined, LTE mode, WiFi mode, and aggregation mode. A non-collocated LWA scenario is considered for the aggregation mode, in which a wireless backhaul link is connecting LTE with WLAN networks. We use TOPSIS technique in order to arrange the available modes and their own stations, according to several metrics and based on the user requirements. Thus, helping for optimum mode and network selection that will improve the system performance while satisfying the user requirements.
Finally, a distributed cell selection algorithm is proposed to consider the impact of fast fading channel on the system performance. The cell selection process is formulated as a combinatorial optimization problem to minimize the average outage probability for the users and thus improving the system performance. Based on well-formulated utility functions for users and different base stations in the multi-RAT HetNet, a two-sided matching game-based approach is proposed to provide the optimum cell selection solution.