Cross-layer scheduling and resource allocation for heterogeneous traffic in 3G LTE

3G long term evolution (LTE) introduces stringent needs in order to provide different kinds of traffic with Quality of Service (QoS) characteristics. The major problem with this nature of LTE is that it does not have any paradigm scheduling algorithm that will ideally control the assignment of resources which in turn will improve the user satisfaction. This has become an open subject and different scheduling algorithms have been proposed which are quite challenging and complex. To address this issue, in this paper, we investigate how our proposed algorithm improves the user satisfaction for heterogeneous traffic, that is, best-effort traffic such as file transfer protocol (FTP) and real-time traffic such as voice over internet protocol (VoIP). Our proposed algorithm is formulated using the cross-layer technique. The goal of our proposed algorithm is to maximize the expected total user satisfaction (total-utility) under different constraints. We compared our proposed algorithm with proportional fair (PF), exponential proportional fair (EXP-PF), and U-delay. Using simulations, our proposed algorithm improved the performance of real-time traffic based on throughput, VoIP delay, and VoIP packet loss ratio metrics while PF improved the performance of best-effort traffic based on FTP traffic received, FTP packet loss ratio, and FTP throughput metrics

Radio Resource Management Optimization For Next Generation Wireless Networks

The prominent versatility of today’s mobile broadband services and the rapid advancements in the cellular phones industry have led to a tremendous expansion in the wireless market volume. Despite the continuous progress in the radio-access technologies to cope with that expansion, many challenges still remain that need to be addressed by both the research and industrial sectors. One of the many remaining challenges is the efficient allocation and management of wireless network resources when using the latest cellular radio technologies (e.g., 4G). The importance of the problem stems from the scarcity of the wireless spectral resources, the large number of users sharing these resources, the dynamic behavior of generated traffic, and the stochastic nature of wireless channels. These limitations are further tightened as the provider’s commitment to high quality-of-service (QoS) levels especially data rate, delay and delay jitter besides the system’s spectral and energy efficiencies. In this dissertation, we strive to solve this problem by presenting novel cross-layer resource allocation schemes to address the efficient utilization of available resources versus QoS challenges using various optimization techniques. The main objective of this dissertation is to propose a new predictive resource allocation methodology using an agile ray tracing (RT) channel prediction approach. It is divided into two parts. The first part deals with the theoretical and implementational aspects of the ray tracing prediction model, and its validation. In the second part, a novel RT-based scheduling system within the evolving cloud radio access network (C-RAN) architecture is proposed. The impact of the proposed model on addressing the long term evolution (LTE) network limitations is then rigorously investigated in the form of optimization problems. The main contributions of this dissertation encompass the design of several heuristic solutions based on our novel RT-based scheduling model, developed to meet the aforementioned objectives while considering the co-existing limitations in the context of LTE networks. Both analytical and numerical methods are used within this thesis framework. Theoretical results are validated with numerical simulations. The obtained results demonstrate the effectiveness of our proposed solutions to meet the objectives subject to limitations and constraints compared to other published works

A Survey on Delay-Aware Resource Control for Wireless Systems --- Large Deviation Theory, Stochastic Lyapunov Drift and Distributed Stochastic Learning

In this tutorial paper, a comprehensive survey is given on several major systematic approaches in dealing with delay-aware control problems, namely the equivalent rate constraint approach, the Lyapunov stability drift approach and the approximate Markov Decision Process (MDP) approach using stochastic learning. These approaches essentially embrace most of the existing literature regarding delay-aware resource control in wireless systems. They have their relative pros and cons in terms of performance, complexity and implementation issues. For each of the approaches, the problem setup, the general solution and the design methodology are discussed. Applications of these approaches to delay-aware resource allocation are illustrated with examples in single-hop wireless networks. Furthermore, recent results regarding delay-aware multi-hop routing designs in general multi-hop networks are elaborated. Finally, the delay performance of the various approaches are compared through simulations using an example of the uplink OFDMA systems.Comment: 58 pages, 8 figures; IEEE Transactions on Information Theory, 201

Packet scheduling algorithms in LTE systems

University of Technology Sydney. Faculty of Engineering and Information Technology.There has been a huge increase in demand towards improving the Quality of Service (QoS) of wireless services. Long Term Evolution (LTE) is a development of the Third-Generation Partnership Project (3GPP) with the aim to meet the needs of International Telecommunication Union (ITU). Some of its aspects are highlighted as follows: increase in data rate, scalable bandwidth, reduced latency and increase in coverage and capacity that result in better quality of service in communication. LTE employs Orthogonal Frequency Division Multiple Access (OFDMA) to simultaneously deliver multimedia services at a high speed rate. Packet switching is used by LTE to support different media services. To meet the QoS requirements for LTE networks, packet scheduling has been employed. Packet scheduling decides when and how different packets are delivered to the receiver. It is responsible for smart user packet selection to allocate radio resources appropriately. Therefore, packet scheduling should be cleverly designed to achieve QoS that is similar to fixed line services. eNodeB is a node in LTE network which is responsible for radio resource management that involves packet scheduling. There are two main categories of application in multimedia services: RT (Real Time) and NRT (None Real Time) services. RT services are either delay sensitive (e.g. voice over IP), loss sensitive (e.g. Buffered Video) or both (delay &loss sensitive) for example video conferencing. Best effort users are an example of NRT services that do not have exact requisites and have been allocated to spare resources. Reaching higher throughput has sometimes resulted in unfair allocation to users who are located far from the base station or users who suffer from bad channel conditions. Therefore, a sufficient trade-off between throughput and fairness is essential. The scarce bandwidth, fading radio channels and the QoS requirement of the users, makes resource allocation a demanding issue. Different scheduling approaches have been suggested for different service demands described briefly throughout the thesis. Initially, a comprehensive literature review of existing work on the packet scheduling topic has been accomplished in this thesis to realize the characteristics of packet scheduling and the resource allocation for the wireless network. Many packet scheduling algorithms developed to provide satisfactory QoS for multimedia services in downlink LTE systems. Several algorithms considered in this thesis include time and frequency domain algorithms and their way of approach has been investigated. The next objective of this thesis is to improve the performance of packet scheduling in LTE downlink systems. A new packet scheduling algorithm has been introduced in this thesis. A study on VoLTE (Voice over LTE), video streaming and best effort traffic under three different scheduling algorithms has been conducted. Heterogeneous traffic based on precise modelling of packets has been used in the simulation. The main resource allocation and assignment technique used in this work namely Dynamic Subcarrier Allocation scheme is shown to provide a solution to solve the cross layer optimisation problem. It depends on Channel Quality Information (CQI) and has been broadly investigated for single carrier and multicarrier wireless networks. The problem is based on the maximisation of average utility functions. Different scheduling algorithms in this method consider to be utility functions. The throughput, fairness and Packet Loss Ratio have been considered as the requirements for examining the performance of algorithms. Simulation results show that the proposed algorithm significantly increases the performance of streaming and best effort users in terms of PLR and throughput. Fairness has also been improved with less computational complexity compared to previous algorithms that have been introduced in this thesis

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