Joint Scheduling for Multi-Service in Coordinated Multi-Point OFDMA Networks

In this paper, the issues upon user scheduling in the downlink packet transmission for multiple services are addressed for coordinated multi-point (CoMP) OFDMA networks. We consider mixed traffic with voice over IP (VOIP) and best effort (BE) services. In order to improve cell-edge performance and guarantee diverse quality of service (QoS), a utility-based joint scheduling algorithm is proposed, which consists of two steps: ant colony optimization (ACO) based joint user selection and greedy subchannel assignment. We compare the proposed algorithm with the greedy user selection (GUC) based scheme. Via simulation results, we show that 95% of BE users are satsified with average cell-edge data rate greater than 200kbps by using either of the two algorithms. Whereas, our proposed algorithm ensures that more than 95% of VoIP users are satisfied with packet drop ratio less than 2%, compared to 78% by the GUC based algorithm

Optimization and learning algorithms for orthogonal frequency division multiplexing-based dynamic spectrum access.

Ph.DDOCTOR OF PHILOSOPH

A TLBO-BASED ENERGY EFFICIENT BASE STATION SWITCH OFF AND USER SUBCARRIER ALLOCATION ALGORITHM FOR OFDMA CELLULAR NETWORKS

Downlink of a cellular network with orthogonal frequency-division multiple access (OFDMA) is considered. Joint base station switch OFF and user subcarrier-allocation with guaranteed user quality of service, is shown to be a promising approach for reducing network’s total power consumption. However, solving the aforementioned mix-integer and nonlinear optimization problem requires robust and powerful optimization techniques. In this paper, teaching-learning based optimization algorithm has been adopted to lower cellular network’s total power consumption. The results show that the proposed technique is able to reduce network’s total power consumption by determining a near optimum set of base stations to be switched OFF and near optimum subcarrier-user assignments. It is shown that the proposed scheme is superior to existing base station switch OFF schemes. Robustness of the proposed TLBO-based technique is verified

Joint relay selection and bandwidth allocation for cooperative relay network

Cooperative communication that exploits multiple relay links offers significant performance improvement in terms of coverage and capacity for mobile data subscribers in hierarchical cellular network. Since cooperative communication utilizes multiple relay links, complexity of the network is increased due to the needs for efficient resource allocation. Besides, usage of multiple relay links leads to Inter- Cell Interference (ICI). The main objective of this thesis is to develop efficient resource allocation scheme minimizes the effect of ICI in cooperative relay network. The work proposed a joint relay selection and bandwidth allocation in cooperative relay network that ensures high achievable data rate with high user satisfaction and low outage percentage. Two types of network models are considered: single cell network and multicell network. Joint Relay Selection and Bandwidth Allocation with Spatial Reuse (JReSBA_SR) and Optimized JReSBA_SR (O_JReSBA_SR) are developed for single cell network. JReSBA_SR considers link quality and user demand for resource allocation, and is equipped with spatial reuse to support higher network load. O_JReSBA_SR is an enhancement of JReSBA_SR with decision strategy based on Markov optimization. In multicell network, JReSBA with Interference Mitigation (JReSBA_IM) and Optimized JReSBA_IM (O_JReSBA_IM) are developed. JReSBA_IM deploys sectored-Fractional Frequency Reuse (sectored- FFR) partitioning concept in order to minimize the effect of ICI between adjacent cells. The performance is evaluated in terms of cell achievable rate, Outage Percentage (OP) and Satisfaction Index (SI). The result for single cell network shows that JReSBA_SR has notably improved the cell achievable rate by 35.0%, with reduced OP by 17.7% compared to non-joint scheme at the expense of slight increase in complexity at Relay Node (RN). O_JReSBA_SR has further improved the cell achievable rate by 13.9% while maintaining the outage performance with reduced complexity compared to JReSBA_SR due to the effect of optimization. The result for multicell network shows that JReSBA_IM enhances the cell achievable rate up to 65.1% and reduces OP by 35.0% as compared to benchmark scheme. Similarly, O_JReSBA_IM has significantly reduced the RN complexity of JReSBA_IM scheme, improved the cell achievable rate up to 9.3% and reduced OP by 1.3%. The proposed joint resource allocation has significantly enhanced the network performance through spatial frequency reuse, efficient, fair and optimized resource allocation. The proposed resource allocation is adaptable to variation of network load and can be used in any multihop cellular network such as Long Term Evolution-Advanced (LTE-A) network

An Optimization Theoretical Framework for Resource Allocation over Wireless Networks

With the advancement of wireless technologies, wireless networking has become ubiquitous owing to the great demand of pervasive mobile applications. Some fundamental challenges exist for the next generation wireless network design such as time varying nature of wireless channels, co-channel interferences, provisioning of heterogeneous type of services, etc. So how to overcome these difficulties and improve the system performance have become an important research topic. Dynamic resource allocation is a general strategy to control the interferences and enhance the performance of wireless networks. The basic idea behind dynamic resource allocation is to utilize the channel more efficiently by sharing the spectrum and reducing interference through optimizing parameters such as the transmitting power, symbol transmission rate, modulation scheme, coding scheme, bandwidth, etc. Moreover, the network performance can be further improved by introducing diversity, such as multiuser, time, frequency, and space diversity. In addition, cross layer approach for resource allocation can provide advantages such as low overhead, more efficiency, and direct end-to-end QoS provision. The designers for next generation wireless networks face the common problem of how to optimize the system objective under the user Quality of Service (QoS) constraint. There is a need of unified but general optimization framework for resource allocation to allow taking into account a diverse set of objective functions with various QoS requirements, while considering all kinds of diversity and cross layer approach. We propose an optimization theoretical framework for resource allocation and apply these ideas to different network situations such as: 1.Centralized resource allocation with fairness constraint 2.Distributed resource allocation using game theory 3.OFDMA resource allocation 4.Cross layer approach On the whole, we develop a universal view of the whole wireless networks from multiple dimensions: time, frequency, space, user, and layers. We develop some schemes to fully utilize the resources. The success of the proposed research will significantly improve the way how to design and analyze resource allocation over wireless networks. In addition, the cross-layer optimization nature of the problem provides an innovative insight into vertical integration of wireless networks

Performance analysis of biological resource allocation algorithms for next generation networks.

Masters Degree. University of KwaZulu-Natal, Durban.Abstract available in PDF.Publications listed on page iii

Distributed resource allocation for inter cell interference mitigation in irregular geometry multicell networks

Extensive increase in mobile broadband applications and proliferation of smart phones and gadgets require higher data rates of wireless cellular networks. However, limited frequency spectrum has led to aggressive frequency reuse to improve network capacity at the expense of increased Inter Cell Interference (ICI). Fractional Frequency Reuse (FFR) has been acknowledged as an effective ICI mitigation scheme but in irregular geometric multicellular network, ICI mitigation poses a very challenging issue. The thesis developed a decentralized ICI mitigation scheme to improve both spectral and energy efficiency in irregular geometric multicellular networks. ICI mitigation was realized through Distributed Resource Allocation (DRA) deployed at the cell level and region level of an irregular geometric cell. The irregular geometric cell consists of a minimum of four regions comprising three sectors and a central region. DRA at the cell level is defined as Multi Sector DRA (MSDRA), and at the region level is defined as Distributed Channel Selection and Power Allocation (DCSPA). MSDRA allocates discrete power to every region in a cell based on Game Theory and Regret Learning Process with correlated equilibrium as the optimum decision level. The DCSPA allocates power to every channel in a region based on non-coalesce liquid droplet phenomena by selecting optimum channels in a region and reserving appropriate power for the selected channels. The performance was evaluated through simulation in terms of data rate, spectral efficiency and energy efficiency. The results showed that MSDRA significantly improved cell data rate by 58.64% and 37.92% in comparision to Generalized FFR and Fractional Frequency Reuse-3 (FFR-3) schemes, respectively. The performance of MSDRA at the cell level showed that its spectral and energy efficiency improved 32% and 22%, respectively in comparison to FFR-3. When the number of sectors increased from three to four, data rate was improved by 30.26% and for three to six sectors, it was improved by 56.32%. The DCSPA further improved data rate by 41.07% when compared with Geometric Water Filling, and 86.46% in comparison to Asynchronous Iterative Water Filling. The DCSPA enhanced data rate achieved in MSDRA by 15.6%. Overall, DRA has shown to have significant improvement in data rate by 53.6%, and spectral efficiency by 38.10% as compared to FFR-3. As a conclusion, the DRA scheme is a potential candidate for Long Term Evaluation – Advanced, Fifth Generation networks and can be deployed in future heterogeneous irregular geometric multicellular Orthogonal Frequency Division Multiple Access networks

Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization