Efficient Scheduling Algorithms for Wireless Resource Allocation and Virtualization in Wireless Networks

The continuing growth in demand for better mobile broadband experiences has motivated rapid development of radio-access technologies to support high data rates and improve quality of service (QoS) and quality of experience (QoE) for mobile users. However, the modern radio-access technologies pose new challenges to mobile network operators (MNO) and wireless device designers such as reducing the total cost of ownership while supporting high data throughput per user, and extending battery life-per-charge of the mobile devices. In this thesis, a variety of optimization techniques aimed at providing innovative solutions for such challenges are explored. The thesis is divided into two parts. In the first part, the challenge of extending battery life-per-charge is addressed. Optimal and suboptimal power-efficient schedulers that minimize the total transmit power and meet the QoS requirements of the users are presented. The second outlines the benefits and challenges of deploying wireless resource virtualization (WRV) concept as a promising solution for satisfying the growing demand for mobile data and reducing capital and operational costs. First, a WRV framework is proposed for single cell zone that is able to centralize and share the spectrum resources between multiple MNOs. Consequently, several WRV frameworks are proposed, which virtualize the spectrum resource of the entire network for cloud radio access network (C-RAN)- one of the front runners for the next generation network architecture. The main contributions of this thesis are in designing optimal and suboptimal solutions for the aforementioned challenges. In most cases, the optimal solutions suffer from high complexity, and therefore low-complexity suboptimal solutions are provided for practical systems. The optimal solutions are used as benchmarks for evaluating the suboptimal solutions. The results prove that the proposed solutions effectively contribute in addressing the challenges caused by the demand for high data rates and power transmission in mobile networks

Scheduling Policies in Time and Frequency Domains for LTE Downlink Channel: A Performance Comparison

A key feature of the Long-Term Evolution (LTE) system is that the packet scheduler can make use of the channel quality information (CQI), which is periodically reported by user equipment either in an aggregate form for the whole downlink channel or distinguished for each available subchannel. This mechanism allows for wide discretion in resource allocation, thus promoting the flourishing of several scheduling algorithms, with different purposes. It is therefore of great interest to compare the performance of such algorithms under different scenarios. Here, we carry out a thorough performance analysis of different scheduling algorithms for saturated User Datagram Protocol (UDP) and Transmission Control Protocol (TCP) traffic sources, as well as consider both the time- and frequency-domain versions of the schedulers and for both flat and frequency-selective channels. The analysis makes it possible to appreciate the difference among the scheduling algorithms and to assess the performance gain, in terms of cell capacity, users' fairness, and packet service time, obtained by exploiting the richer, but heavier, information carried by subchannel CQI. An important part of this analysis is a throughput guarantee scheduler, which we propose in this paper. The analysis reveals that the proposed scheduler provides a good tradeoff between cell capacity and fairness both for TCP and UDP traffic sources

A Review of MAC Scheduling Algorithms in LTE System

The recent wireless communication networks rely on the new technology named Long Term Evolution (LTE) to offer high data rate real-time (RT) traffic with better Quality of Service (QoS) for the increasing demand of customer requirement. LTE provide low latency for real-time services with high throughput, with the help of two-level packet retransmission. Hybrid Automatic Repeat Request (HARQ) retransmission at the Medium Access Control (MAC) layer of LTE networks achieves error-free data transmission. The performance of the LTE networks mainly depends on how effectively this HARQ adopted in the latest communication standard, Universal Mobile Telecommunication System (UMTS). The major challenge in LTE is to balance QoS and fairness among the users. Hence, it is very essential to design a down link scheduling scheme to get the expected service quality to the customers and to utilize the system resources efficiently. This paper provides a comprehensive literature review of LTE MAC layer and six types of QoS/Channel-aware downlink scheduling algorithms designed for this purpose. The contributions of this paper are to identify the gap of knowledge in the downlink scheduling procedure and to point out the future research direction. Based on the comparative study of algorithms taken for the review, this paper is concluded that the EXP Rule scheduler is most suited for LTE networks due to its characteristics of less Packet Loss Ratio (PLR), less Packet Delay (PD), high throughput, fairness and spectral efficiency

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