Incorporating Context Awareness in Cellular Networks to Enhance System Performance and User Mobility Support

In today’s world, mobile communication has become one of the most widely used technologies corroborated by growing number of mobile subscriptions and extensive usage of mobile multimedia services. It is a key challenge for the network operators to accommodate such large number of users and high traffic volume. Further, several day-to-day scenarios such as public transportation, public events etc., are now characterized with high mobile data usage. A large number of users avail cellular services in such situations posing high load to the respective base stations. This results in increased number of dropped connections, blocking of new access attempts and blocking of handovers (HO). The users in such system will thus be subjected to poor Quality of Experience (QoE). Beforehand knowledge of the changing data traffic dynamics associated with such practical situations will assist in designing radio resource management schemes aiming to ease the forthcoming congestion situations. The key hypothesis of this thesis is that consideration and utilization of additional context information regarding user, network and his environment is valuable in designing such smart Radio Resource Management(RRM) schemes. Methods are developed to predict the user cell transitions, considering the fact that mobility of the users is not purely random but rather direction oriented. This is particularly used in case of traffic dense moving network or group of users moving jointly in the same vehicle (e.g., bus, train, etc.) to predict the propagation of high load situation among cells well in advance. This enables a proactive triggering of load balancing (LB) in cells anticipating the arrival of high load situation and accommodating the incoming user group or moving network. The evaluated KPIs such as blocked access attempts, dropped connections and blocked HO are reduced. Further, everyday scenario of dynamic crowd formation is considered as another potential case of high load situation. In real world scenarios such as open air festivals, shopping malls, stadiums or public events, several mobile users gather to form a crowd. This poses high load situation to the respective serving base station at the site of crowd formation, thereby leading to congestion. As a consequence, mobile users are subjected to poor QoE due to high dropping and blocking rates. A framework to predict crowd formation in a cell is developed based on coalition of user cell transition prediction, cluster detection and trajectory prediction. This framework is suitably used to prompt context aware load balancing mechanism and activate a small cell at the probable site of crowd formation. Simulations show that proactive LB reduces the dropping of users (23%), blocking of users (10%) and blocked HO (15%). In addition, activation of a Small Cell (SC) at the site of frequent crowd formation leads to further reductions in dropping of users (60%), blocking of users (56%) and blocked HO (59%). Similar to the framework for crowd formation prediction, a concept is developed for predicting vehicular traffic jams. Many vehicular users avail broadband cellular services on a daily basis while traveling. The density of such vehicular users change dynamically in a cell and at certain sites (e.g. signal lights), traffic jams arise frequently leading to a high load situation at respective serving base station. A traffic prediction algorithm is developed from cellular network perspective as a coalition strategy consisting of schemes to predict user cell transition, vehicular cluster/moving network detection, user velocity monitoring etc. The traffic status indication provided by the algorithm is then used to trigger LB and activate/deactivate a small cell suitably. The evaluated KPIs such as blocked access attempts, dropped connections and blocked HO are reduced by approximately 10%, 18% and 18%, respectively due to LB. In addition, switching ON of SC reduces blocked access attempts, dropped connections and blocked HO by circa 42%, 82% and 81%, respectively. Amidst increasing number of connected devices and traffic volume, another key issue for today’s network is to provide uniform service quality despite high mobility. Further, urban scenarios are often characterized by coverage holes which hinder service continuity. A context aware resource allocation scheme is proposed which uses enhanced mobility prediction to facilitate service continuity. Mobility prediction takes into account additional information about the user’s origin and possible destination to predict next road segment. If a coverage hole is anticipated in upcoming road, then additional resources are allocated to respective user and data is buffered suitably. The buffered data is used when the user is in a coverage hole to improve service continuity. Simulation shows improvement in throughput (in coverage hole) by circa 80% and service interruption is reduced by around 90%, for a non-real-time streaming service. Additionally, investigation of context aware procedures is carried out with a focus on user mobility, to find commonalities among different procedures and a general framework is proposed to support mobility context awareness. The new information and interfaces which are required from various entities (e.g., vehicular infrastructure) are discussed as well. Device-to-Device (D2D) communications commonly refer to the technology that enables direct communication between devices, hence relieving the base station from traffic routing. Thus, D2D communication is a feasible solution in crowded situations, where users in proximity requesting to communicate with one another could be granted D2D links for communication, thereby easing the traffic load to serving base station. D2D links can potentially reuse the radio resources from cellular users (known as D2D underlay) leading to better spectral utilization. However, the mutual interference can hinder system performance. For instance, if D2D links are reusing cellular uplink resources then D2D transmissions cause interference to cellular uplink at base station. Whereas, cellular transmissions cause interference to D2D receivers. To cope up with such issues, location aware resource allocation schemes are proposed for D2D communication. The key aim of such RA scheme is to reuse resources with minimal interference. The RA scheme based on virtual sectoring of a cell leads to approximately 15% more established links and 25% more capacity with respect to a random resource allocation. D2D transmissions cause significant interference to cellular links with which they reuse physical resource blocks, thereby hindering cellular performance. Regulating D2D transmissions to mitigate the aforementioned problem would mean sub-optimal exploitation of D2D communications. As a solution, post-resource allocation power control at cellular users is proposed. Three schemes namely interference aware power control, blind power control and threshold based power control are discussed. Simulation results show reductions in dropping of cellular users due to interference from D2D transmissions, improvement in throughput at base station (uplink) while not hindering the D2D performance