PERFORMANCE ENHANCING INTERFERENCE MANAGEMENT TECHNIQUES FOR FUTURE CELLULAR SYSTEMS

UoM administered thesis: Phd

  • Authors:
  • Aysha Ebrahim

Abstract

The limited bandwidth available for cellular networks has necessitated on current wireless technologies, such as long-term evolution (LTE), to devise new strategies to improve the spectrum reuse and the capacity of cellular networks. Multi-tier heterogeneous networks is a low-cost solution in which the traditional macrocells are underlaid with small cells such as femto- and pico- cells that are centered around users to improve the network capacity. In this regard, radio resource management (RRM) based interference avoidance techniques have been widely used to minimize the interference incurred as a result of small cell deployment. This thesis proposes novel interference management techniques for improving the spectrum reuse efficiency in cellular networks. An RRM that utilizes a sleep mode (SL) strategy is proposed to identify the small cells that maximize the reuse efficiency outcome when set to sleep mode without requiring an exhaustive search. To improve the association of the switched off cells users and improve the overall performance, an interference aware user association technique that allows seamless association between BSs and users is introduced to increase access to resources. To enhance both the overall throughput and quality of service (QoS) metrics, a map of the various interference levels is constructed to be used for two purposes: First to satisfy QoS constrains by orthogonalizing certain interfering BSs/users, and second to maximize the resource utilization using an adaptive power control scheme. To reduce the signaling overhead on the back-haul network, a distributed RRM is presented to allow BSs to independently adjust their bandwidth usage to reduce the inter-cell interference. With the lack of central management and coordination among cells, this information is estimated locally by monitoring the uplink spectrum.

Details

Original languageEnglish
Awarding Institution
Supervisors/Advisors
Award date31 Dec 2016