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|Title:||Optimal resource management in multi-service mobile cellular networks||Authors:||Yang, Xun||Keywords:||DRNTU::Engineering::Electrical and electronic engineering::Wireless communication systems||Issue Date:||2008||Source:||Yang, X. (2008). Optimal resource management in multi-service mobile cellular networks. Doctoral thesis, Nanyang Technological University, Singapore.||Abstract:||Resource management (RM) plays a critical role for QoS provisioning in the design of mobile wireless networks. In this thesis, we focus on the research of two key RM issues: call admission control (CAC) and bandwidth allocation (BA), for three main RM optimization problems in multi-service mobile wireless networks. We first study the MAXU problem, which is defined as maximizing system utilization subject to constraints on call blocking probabilities. Since it is difficult to promptly adjust bandwidth allocation on uplink and downlink according to the change of traffic load in the system, the mismatch of bandwidth allocation and traffic load results in low bandwidth utilization. In such environment, traditional CAC may admit superfluous Real-Time (RT) calls or Non-Real-Time (NRT) calls and thus lead to bandwidth waste. We propose and evaluate two new CAC schemes to address the low bandwidth utilization problems in such bandwidth asymmetry networks. By determining the admissible regions for RT calls and NRT calls, the proposed schemes prevent the calls of a specific class from overusing the bandwidth resources. Next, we focus on minimizing average system cost (MINCost) problem in multi-service mobile wireless networks. By modeling the admission control problem into a Markov decision process (MDP) and analyzing the corresponding value function, we obtain some monotonicity properties of the optimal policy. These properties suggest that the optimal admission control policy for the bandwidth asymmetry mobile wireless networks have a threshold structure and the threshold specified for a class of calls may change with system states. Due to the prohibitively high complexity for computing the thresholds in a system with large state-space, we propose a heuristic CAC policy called Call-Rate-based Dynamic Threshold (CRDT) policy to approximate the theoretical optimal policy based on the insights we obtain from the modeling and the analytical study on the properties of the optimal policy. Subsequently, we turn to study the problem of minimizing new call blocking probabilities with hard constraints on handoff call blocking probabilities (MINBlock) in multi-service mobile wireless networks. We propose a new Distributed Multi-service Admission Control scheme (DMS-AC) to handle the MINBlock problem in multi-service mobile wireless networks. In order to satisfy the QoS requirements of different call classes in a dynamic traffic load environment, we also propose bandwidth re-allocation as a complementary mechanism for CAC in bandwidth asymmetry mobile wireless networks. Based on the proposed DMS-AC scheme, we investigate when and how to adjust bandwidth allocation on uplink and downlink in a multi-service mobile wireless network with bandwidth asymmetry under dynamic traffic load conditions. With the designed bandwidth re-allocation scheme in conjunction with the proposed CAC, the QoS requirements of different call classes can be guaranteed under dynamic traffic conditions and in the mean time the system bandwidth utilization is improved significantly. Our work in this thesis is an essential extension for resource management in the design of multi-service mobile wireless networks, especially for bandwidth asymmetry mobile wireless networks. By studying and analyzing the special features of the multi-service mobile wireless networks, we investigate main call level RM optimization problems in the new environment, and propose some efficient and effective RM schemes based on comprehensive analysis and mathematical models. We believe that our work can bring some insights to the research work in the area of RM design in multi-service mobile wireless networks.||URI:||https://hdl.handle.net/10356/13224||DOI:||10.32657/10356/13224||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Theses|
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Updated on Oct 24, 2021
Updated on Oct 24, 2021
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