Interference Aware Cognitive Femtocell Networks

Femtocells Access Points (FAP) are low power, plug and play home base stations which are designed to extend the cellular radio range in indoor environments where macrocell coverage is generally poor. They offer significant increases in data rates over a short range, enabling high speed wireless and mobile broadband services, with the femtocell network overlaid onto the macrocell in a dual-tier arrangement. In contrast to conventional cellular systems which are well planned, FAP are arbitrarily installed by the end users and this can create harmful interference to both collocated femtocell and macrocell users. The interference becomes particularly serious in high FAP density scenarios and compromises the ensuing data rate. Consequently, effective management of both cross and co-tier interference is a major design challenge in dual-tier networks. Since traditional radio resource management techniques and architectures for single-tier systems are either not applicable or operate inefficiently, innovative dual-tier approaches to intelligently manage interference are required. This thesis presents a number of original contributions to fulfill this objective including, a new hybrid cross-tier spectrum sharing model which builds upon an existing fractional frequency reuse technique to ensure minimal impact on the macro-tier resource allocation. A new flexible and adaptive virtual clustering framework is then formulated to alleviate co-tier interference in high FAP densities situations and finally, an intelligent coverage extension algorithm is developed to mitigate excessive femto-macrocell handovers, while upholding the required quality of service provision. This thesis contends that to exploit the undoubted potential of dual-tier, macro-femtocell architectures an interference awareness solution is necessary. Rigorous evidence confirms that noteworthy performance improvements can be achieved in the quality of the received signal and throughput by applying cognitive methods to manage interference

Performance analysis of channel assignment schemes for coordinated cognitive WLAN networks

Nowadays local wireless networks are very used by an elevated number of people and its use continues rising. This provokes an increase of the interference and as consequence, congestion in the non-licensed band of 2.4GHz, caused by the increase of users in a given zone and thus, the limitation of channels offered by this band. As a solution to this problem, in this project it is studied the possibility of using additional channels from licensed bands used for other radio-communications services. The use of these channels in the local network (named in this context as secondary user of this spectrum) is done in an opportunistic manner, when ever it does not provoke any interference to the users of the service which have the rights to use this spectrum (named primary users in this context), since these ones have priority to access these bands of the spectrum. As a first approximation to the solution of the assignment problem, it is studied the behaviour of a random channel assignment in a scenario with a certain density of local networks that can generate interference between them and where the availability of the primary channel for opportunistic use is not homogeneous. Later, stated the possibility of improving the level of interference even with a random channel assignment, there are proposed two channel assignment methods designed to have in concern the availability of primary channels. The first method is set out through the formulation of an Integer Linear Programming (ILP) problem, which allows obtaining an optimal solution but with an elevated execution time. The other method is an heuristic one based on obtaining a Minimum Spanning Tree (MST) on interference terms, which allows to obtain near-optimal solutions in less time of execution. In the project it is done a detailed comparison of these two methods to contrast the advantages of each one. Finally, there are identified some aspects of the implementation of these methods in a real scenario