Abstract

Heterogeneous wireless access network (HWAN) is composed of fifth-generation (5G) and fourth-generation (4G) cellular systems and IEEE 802.11-based wireless local area networks (WLANs). These diverse and dense wireless networks have different data rates, coverage,
capacity, cost, and QoS. Furthermore, user devices are multi-modal devices that allow users to connect to more than one network simultaneously. This thesis presents radio resource management for RAT selection, radio resource allocation, load balancing, congestion control mechanism, and user device (UD) energy management that can effectively utilize the available resources in the heterogeneous wireless networks and enhance the quality-of-service (QoS) and user quality-of-experience (QoE).
Recent studies on radio resource management in HWAN lead to two broad categories, 1) centralized architecture and 2) distributed model. In the centralized model, all the decision making power confines to a centralized controller and user devices are assumed as passive
transceivers. In contrast, user devices actively participate in radio resource management in the distributed model, resulting in poor resource utilization and maximum call blocking and call dropping probabilities.
In this thesis, we present a novel hybrid radio resource management model for HWAN that is composed of OFDMA based system and WLAN. In this model, both the centralized controller and the user device take part in resource management. Our hybrid mechanism
considers attributes related to both user and network. However, these attributes are conflicting in nature. Moreover, a single RAT selection is performed based on user location and available networks, whereas UD with a multi-homing call receives the radio resource share from each network to fulfil its minimum data rate requirement. A novel approach is proposed for load balancing where an equal load ratio is maintained across all the available networks in HWAN. Performance evaluation through call blocking probability and network utilization will reveal the effectiveness of the proposed scheme.
The demand for more data rates is on the rise. The 5G heterogeneous wireless access network is a potential solution to tackle the high data rate demand. The 5GHWAN is composed of 5G new radio (NR) and 4G long-term evolution (LTE) base stations (BSs). In a practical system, the channel conditions fluctuate due to user mobility. We, therefore, investigate
radio resource allocation and congestion control mechanism along with network-assisted distributive RAT selection in a time-varying 5GHWAN. This joint problem of radio resource allocation and congestion control management has signalling overhead and computational
complexity limitations. Therefore, we use the Lyapunov optimization to convert the offline problem into an online optimization problem based on channel state information (CSI) and queue state information (QSI). The theoretical and simulation results evaluate the performance
of our proposed approach under the assumption of network stability. In addition, simulation results are presented to depict our proposed scheme’s effectiveness. Furthermore, our proposed RAT selection scheme performs better than the traditional centralized
and distributive mechanisms.
Recently an increase in the usage of video applications has been observed. Therefore, we explore hybrid radio resource management video streaming over time-varying HWAN. Using the Lyapunov optimization technique, we decompose our two-time scale stochastic optimization
problem into two main sub-problems. One of the sub-problems is related to radio resource allocation that operates at a scheduling time interval. The radio resource allocation policy is implemented at a centralized control node responsible for allocating radio resources
from the available wireless networks using Lagrange dual method. The other sub-problem is related to the quality rate adaptation policy that works at a chunk time scale. Each user selects the appropriate quality level of the video chunks adaptively in a distributive way based
on buffer state and channel state information. We analyze and compare the QoE of our proposed
approach over an arbitrary sample path of channel state information with an optimal T-slot algorithm. Finally, we evaluate the performance analysis of our proposed scheme for video streaming over a time-varying heterogeneous wireless access network through simulation results.