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

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

Packet scheduling in satellite LTE networks employing MIMO technology.

Doctor of Philosophy in Electronic Engineering. University of KwaZulu-Natal, Durban 2014.Rapid growth in the number of mobile users and ongoing demand for different types of telecommunication services from mobile networks, have driven the need for new technologies that provide high data rates and satisfy their respective Quality of Service (QoS) requirements, irrespective of their location. The satellite component will play a vital role in these new technologies, since the terrestrial component is not able to provide global coverage due to economic and technical limitations. This has led to the emergence of Satellite Long Term Evolution (LTE) networks which employ Multiple-In Multiple-Out (MIMO) technology. In order to achieve the set QoS targets, required data rates and fairness among various users with different traffic demands in the satellite LTE network, it is crucial to design an effective scheduling and a sub-channel allocation scheme that will provide an optimal balance of all these requirements. It is against this background that this study investigates packet scheduling in satellite LTE networks employing MIMO technology. One of the main foci of this study is to propose new cross-layer based packet scheduling schemes, tagged Queue Aware Fair (QAF) and Channel Based Queue Sensitive (CBQS) scheduling schemes. The proposed schemes are designed to improve both fairness and network throughput without compromising users’ QoS demands, as they provide a good trade-off between throughput, QoS demands and fairness. They also improve the performance of the network in comparison with other scheduling schemes. The comparison is determined through simulations. Due to the fact that recent schedulers provide a trade-off among major performance indices, a new performance index to evaluate the overall performance of each scheduler is derived. This index is tagged the Scheduling Performance Metric (SPM). The study also investigates the impact of the long propagation delay and different effective isotropic radiated powers on the performance of the satellite LTE network. The results show that both have a significant impact on network performance. In order to actualize an optimal scheduling scheme for the satellite LTE network, the scheduling problem is formulated as an optimization function and an optimal solution is obtained using Karush-Kuhn-Tucker multipliers. The obtained Near Optimal Scheduling Scheme (NOSS), whose aim is to maximize the network throughput without compromising users’ QoS demands and fairness, provides better throughput and spectral efficiency performance than other schedulers. The comparison is determined through simulations. Based on the new SPM, the proposed NOSS1 and NOSS2 outperform other schedulers. A stability analysis is also presented to determine whether or not the proposed scheduler will provide a stable network. A fluid limit technique is used for the stability analysis. Finally, a sub-channel allocation scheme is proposed, with the aim of providing a better sub-channel or Physical Resource Block (PRB) allocation method, tagged the Utility Auction Based (UAB) subchannel allocation scheme that will improve the system performance of the satellite LTE network. The results show that the proposed method performs better than the other scheme. The comparison is obtained through simulations

Smart Grid communications in high traffic environments

The establishment of a previously non-existent data class known as the Smart Grid will pose many difficulties on current and future communication infrastructure. It is imperative that the Smart Grid (SG), as the reactionary and monitory arm of the Power Grid (PG), be able to communicate effectively between grid controllers and individual User Equipment (UE). By doing so, the successful implementation of SG applications can occur, including support for higher capacities of Renewable Energy Resources. As the SG matures, the number of UEs required is expected to rise increasing the traffic in an already burdened communications network. This thesis aims to optimally allocate radio resources such that the SG Quality of Service (QoS) requirements are satisfied with minimal effect on pre-existing traffic. To address this resource allocation problem, a Lotka-Volterra (LV) based resource allocation and scheduler was developed due to its ability to easily adapt to the dynamics of a telecommunications environment. Unlike previous resource allocation algorithms, the LV scheme allocated resources to each class as a function of its growth rate. By doing so, the QoS requirements of the SG were satisfied, with minimal effect on pre-existing traffic. Class queue latencies were reduced by intelligent scheduling of periodic traffic and forward allocation of resources. This thesis concludes that the SG will have a large effect on the telecommunications environment if not successfully controlled and monitored. This effect can be minimized by utilizing the proposed LV based resource allocation and scheduler system. Furthermore, it was shown that the allocation of periodic SG radio channels was optimized by continual updates of the LV model. This ensured the QoS requirements of the SG are achieved and provided enhanced performance. Successful integration of SG UEs in a wireless network can pave the way for increased capacity of Renewable and Intermittent Energy Resources operating on the PG

Statistical priority-based uplink scheduling for M2M communications

Currently, the worldwide network is witnessing major efforts to transform it from being the Internet of humans only to becoming the Internet of Things (IoT). It is expected that Machine Type Communication Devices (MTCDs) will overwhelm the cellular networks with huge traffic of data that they collect from their environments to be sent to other remote MTCDs for processing thus forming what is known as Machine-to-Machine (M2M) communications. Long Term Evolution (LTE) and LTE-Advanced (LTE-A) appear as the best technology to support M2M communications due to their native IP support. LTE can provide high capacity, flexible radio resource allocation and scalability, which are the required pillars for supporting the expected large numbers of deployed MTCDs. Supporting M2M communications over LTE faces many challenges. These challenges include medium access control and the allocation of radio resources among MTCDs. The problem of radio resources allocation, or scheduling, originates from the nature of M2M traffic. This traffic consists of a large number of small data packets, with specific deadlines, generated by a potentially massive number of MTCDs. M2M traffic is therefore mostly in the uplink direction, i.e. from MTCDs to the base station (known as eNB in LTE terminology). These characteristics impose some design requirements on M2M scheduling techniques such as the need to use insufficient radio resources to transmit a huge amount of traffic within certain deadlines. This presents the main motivation behind this thesis work. In this thesis, we introduce a novel M2M scheduling scheme that utilizes what we term the “statistical priority” in determining the importance of information carried by data packets. Statistical priority is calculated based on the statistical features of the data such as value similarity, trend similarity and auto-correlation. These calculations are made and then reported by the MTCDs to the serving eNBs along with other reports such as channel state. Statistical priority is then used to assign priorities to data packets so that the scarce radio resources are allocated to the MTCDs that are sending statistically important information. This would help avoid exploiting limited radio resources to carry redundant or repetitive data which is a common situation in M2M communications. In order to validate our technique, we perform a simulation-based comparison among the main scheduling techniques and our proposed statistical priority-based scheduling technique. This comparison was conducted in a network that includes different types of MTCDs, such as environmental monitoring sensors, surveillance cameras and alarms. The results show that our proposed statistical priority-based scheduler outperforms the other schedulers in terms of having the least losses of alarm data packets and the highest rate in sending critical data packets that carry non-redundant information for both environmental monitoring and video traffic. This indicates that the proposed technique is the most efficient in the utilization of limited radio resources as compared to the other techniques

Coordinated Multi-Point MIMO Processing for 4G

The concept of cooperative Multiple-Input-Multiple-Output (MIMO), also referred to as network MIMO, or as Coordinated Multi-Point Transmission (CoMP), was standardized in 3GPP Release 11. The goal of CoMP is to improve the coverage of high data rates and cell-edge throughput, and also to increase system throughput. In this paper we analyze only the latter scenario, using system level simulations in accordance with 3GPP guidelines. It is shown that the use of joint coordinated multipoint transmission achieves additional throughput gains. However, the gains depend on the scheduling type. This paper also indicates that the criterion of fairness is an important parameter when the number of users is high