Admission Control and Radio Resource Allocation for Multicasting Over High Altitude Platforms

Download or read book Admission Control and Radio Resource Allocation for Multicasting Over High Altitude Platforms written by Ahmed Ibrahim and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, optimization techniques for a joint admission control and radio resource allocation are developed for multicasting over high altitude platforms. First, a primary system model in a multicellular high altitude platform system is considered, in which each user can receive any requested multicast session in its cell from no more than only one HAP antenna simultaneously. All the users have equal priority for admission. The users are selected to join the respective multicast groups and the power, subchannels and time slots are allocated such that the spectrum utilization is maximized while satisfying the quality of service requirements. Lagrangian relaxation and the subgradient algorithm are used to obtain solution bounds for the primary system model problem formulation. These bounds were then used in the branch and bound algorithm for pruning of nodes. The numerical results illustrate the goodness of the bounds for different constraint set dualizations and for different subgradient step size rules. The system model is then extended to allow the multicast group users to receive a session's transmission from more than one antenna simultaneously at different frequencies. This also allows the user to receive multicast sessions transmitted in neighboring cells too, not just those transmitted in the cell which the user resides in. The users have different priority levels of admission and the objective is to maximize the admission of highest priority users to the system. A much efficient formulation is obtained for the extended model in terms of size, as compared to the primary model. Linear outer approximation using McCormick underestimators are used for the relaxation of the mixed binary quadratically constrained problem. The solution method is based on branch and cut scheme in which cutting planes, domain propagation and heuristics are integrated. Various branching schemes are considered and a presolving reformulation linearization scheme for a specific set of quadratic constraints is considered. The numerical experiments compare the performances in terms of the duality gap, number of nodes, number of iterations, the number of iterations per node, the time needed to obtain the first feasible solution and the percentage of instances a feasible solution was found.