| dc.description.abstract | In recent years, because of the increased prevalence of mobile broadband network and the rapid development of social network service (SNS) and emerging services, it attracts numerous users to access the services through various types of smart devices at any location. However, due to the diverse smart devices and emerging mobile services, different types of devices and services have different requirements of mobile broadband network and quality of service. Due to limitation of mobile broadband spectrum resources, network component capability, and battery lifetime, how to balance resource scheduling, power consumption, and user experience will become more challenging.
In this dissertation, we discuss signaling in 3G Environment for SNS first. To save power, a smart device was designed to release a data path immediately or to follow standards for transitioning to a power saving state. To provide better interaction, SNS was relevant power design Stay connected with the mechanism, the mechanism described above will produce a large number of signaling burden. To examine the signaling effects, this study analyzed measurements of signaling introduced by diverse smart devices when these devices run SNS in a real operator environment. The measurement results indicated that a high number of RRC related signaling messages are produced when a smart device runs a SNS, and the generated signaling messages introduce a heavy computational burden on the control plane. A possible enhancement approach is proposed and we expect the approach can reduce the signaling storm. The signaling fingerprints can be applied to establish signaling models for analyzing the performance of control planes.
In downlink long-term evolution, we propose quality of service (QoS) aware scheme (QAS) and buffer aware scheme (BAS) scheduling consider the QoS with user channel conditions and buffer of user equipment (UE) with the user channel status, respectively. And determines the scheduling priority based on a designed heuristic weighting function. In proposed QAS, the simulation results show the proposed scheme improves power consumption in the case of video-streaming service but not HTTP service. The simulation results show that the proposed scheme allocates resources more fairly than other schemes used for comparison. To avoid too many UEs contending the limited radio resources and reduce power consumption, the proposed BAS estimates the allowable maximum number of UE. The simulation results show the proposed BAS achieve achieves less streaming delivery time and generates less signaling overhead than the best CQI scheme when the traffic load is heavy and high resolution video streaming sources.
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