Dynamic frequency and power resource allocation with granular policy management

Abstract

Technologies are generally described to provide multi-objective dynamic resource optimization for self-organizing networks. In some examples, a system employing dynamic resource optimization may allocate network resources to a group of subscribers to enable granular policy management per cell, per subscriber type, per service, and/or per user resource. The dynamic resource optimization may be based on optimization/improvement of a throughput objective and a quality of experience (QoE) objective. Users maybe segmented into different groups according to subscriber types with each group having a priority level assigned. Resources may be allocated first to a highest or relatively higher priority group of users, and remaining resources may be consecutively allocated to lower priority groups. The QoE objective may be quantitatively determined by mapping real time quality of service (QoS) parameters associated with the subscriber group. A set of group policy parameters may also be applied to weight the throughput and QoE objectives.