Cross-Layer Capacity Optimization In OFDMA Systems: WiMAX And LTE

Given the broad range of applications supported, high data rate required and low latency promised; dynamic radio resource management is becoming vital for newly emerging air interface technologies such as wireless interoperability for microwave access (Wimax) and long term evolution (lte) adopted by international standards. This thesis considers orthogonal frequency division multiple access (ofdma) system, which has been implemented in both Wimax and lte technologies as their air interface multiple access mechanism. A framework for optimized resource allocation with quality of service (qos) support that aims to balance between service provider\u27s revenue and subscriber\u27s satisfaction is proposed. A cross-layer optimization design for subchannel, for Wimax, and physical resource block (prb), for lte, and power allocations with the objective of maximizing the capacity (in bits/symbol/hz) subject to fairness parameters and qos requirements as constraints is presented. An adaptive modulation and coding (amc)-based cross-layer scheme has also been proposed in this thesis by adopting an amc scheme together with the cross-layer scheme to realize a more practical and viable resource allocation. The optimization does not only consider users channel conditions but also queue status of each user as well as different qos requirements. In the proposed framework, the problem of power allocation is solved analytically while the subchannel/prb allocation is solved using integer programming exhaustive search. The simulation and numerical results obtained in this thesis have shown improved system performance as compared to other optimization schemes known in literature

Cross-layer design for OFDMA wireless networks with finite queue length based on game theory

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.In next generation wireless networks such as 4G- LTE and WiMax, the demand for high data rates, the scarcity of wireless resources and the time varying channel conditions has led to the adoption of more sophisticated and robust techniques in PHY such as orthogonal frequency division multiplexing (OFDM) and the corresponding access technique known as orthogonal frequency division multiplexing access (OFDMA). Cross-layer schedulers have been developed in order to describe the procedure of resource allocation in OFDMA wireless networks. The resource allocation in OFDMA wireless networks has received great attention in research, by proposing many different ways for frequency diversity exploitation and system’s optimization. Many cross-layer proposals for dynamic resource allocation have been investigated in literature approaching the optimization problem from different viewpoints i.e. maximizing total data rate, minimizing total transmit power, satisfying minimum users’ requirements or providing fairness amongst users. The design of a cross-layer scheduler for OFDMA wireless networks is the topic of this research. The scheduler utilizes game theory in order to make decisions for subcarrier and power allocation to the users with the main concern being to maintain fairness as well as to maximize overall system’s performance. A very well known theorem in cooperative game theory, the Nash Bargaining Solution (NBS), is employed and solved in a close form way, resulting in a Pareto optimal solution. Two different cases are proposed. The first one is the symmetric NBS (S-NBS) where all users have the same weight and therefore all users have the same opportunity for resources and the second one, is the asymmetric NBS (A-NBS), where users have different weights, hence different priorities where the scheduler favours users with higher priorities at expense of lower priority users. As MAC layer is vital for cross-layer, the scheduler is combined with a queuing model based on Markov chain in order to describe more realistically the incoming procedure from the higher layers

A Study of Packet Scheduling Schemes for VoIP and Best Effort Traffic in LTE Networks

The Long Term Evolution (LTE) provides all services over Internet Protocol (IP) since it is an all IP network. To use available radio resources in an effective utilization, Packet Scheduling (PS) should be considered to enhance the Quality of Service (QoS) of Real Time (RT) and Non-Real Time (NRT) traffic. In this thesis, the PS of both RT and NRT traffic is studied in LTE networks. Apriority packet scheduling algorithm is proposed. The proposed algorithm has the ability to schedule the mixed traffic, RT and NRT, simultaneously. The objective of the algorithm is to maximize the Best Effort (BE) throughput while achieves the satisfaction QoS requirements of RT throughput. According to the obtained results of the thesis, the traffic should be differentiated and the services should be prioritized, when applying delay sensitive services. A system simulation is performed to support the study for mixed services approaches with Voice over IP (VoIP) and a second BE service such as File Transfer Protocol (FTP). The performance of the proposed algorithm and the impact of the different factors on the overall system performance have been tested. The work is done at Medium Access Control (MAC) layer and Physical Layer (PHY). Finally, a good results are achieved that guarantee a good end to end performance for both voice and data services

Radio network management in cognitive LTE-Femtocell Systems

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.There is a strong uptake of femtocell deployment as small cell application platforms in the upcoming LTE networks. In such two-tier networks of LTEfemtocell base stations, a large portion of the assigned spectrum is used sporadically leading to underutilisation of valuable frequency resources. Novel spectrum access techniques are necessary to solve these current spectrum inefficiency problems. Therefore, spectrum management solutions should have the features to improve spectrum access in both temporal and spatial manner. Cognitive Radio (CR) with the Dynamic Spectrum Access (DSA) is considered to be the key technology in this research in order to increase the spectrum efficiency. This is an effective solution to allow a group of Secondary Users (SUs) to share the radio spectrum initially allocated to the Primary User (PUs) at no interference. The core aim of this thesis is to develop new cognitive LTE-femtocell systems that offer a 4G vision, to facilitate the radio network management in order to increase the network capacity and further improve spectrum access probabilities. In this thesis, a new spectrum management model for cognitive radio networks is considered to enable a seamless integration of multi-access technology with existing networks. This involves the design of efficient resource allocation algorithms that are able to respond to the rapid changes in the dynamic wireless environment and primary users activities. Throughout this thesis a variety of network upgraded functions are developed using application simulation scenarios. Therefore, the proposed algorithms, mechanisms, methods, and system models are not restricted in the considered networks, but rather have a wider applicability to be used in other technologies. This thesis mainly investigates three aspects of research issues relating to the efficient management of cognitive networks: First, novel spectrum resource management modules are proposed to maximise the spectrum access by rapidly detecting the available transmission opportunities. Secondly, a developed pilot power controlling algorithm is introduced to minimise the power consumption by considering mobile position and application requirements. Also, there is investigation on the impact of deploying different numbers of femtocell base stations in LTE domain to identify the optimum cell size for future networks. Finally, a novel call admission control mechanism for mobility management is proposed to support seamless handover between LTE and femtocell domains. This is performed by assigning high speed mobile users to the LTE system to avoid unnecessary handovers. The proposed solutions were examined by simulation and numerical analysis to show the strength of cognitive femtocell deployment for the required applications. The results show that the new system design based on cognitive radio configuration enable an efficient resource management in terms of spectrum allocation, adaptive pilot power control, and mobile handover. The proposed framework and algorithms offer a novel spectrum management for self organised LTE-femtocell architecture. Eventually, this research shows that certain architectures fulfilling spectrum management requirements are implementable in practice and display good performance in dynamic wireless environments which recommends the consideration of CR systems in LTE and femtocell networks