Scheduling Algorithm For WiMAX Networks Research Articles

A CROSS-LAYER SCHEDULER WITH CHANNEL STATE INFORMATION FOR GUARANTEED QUALITY OF SERVICE

WiMAX networks are deployed for commercial use because of its nature high bandwidth. This requirement invokes the application level changes i n QoS provisioning techniques. The objective of the broadband wireless technologies is to ensure th e end to end Quality of Service (QoS) for the service classes. WiMAX is a revolution in wireless networks, which could support real time multimedia services. In order to provide QoS suppor t and efficient usage of system resources an intelligent scheduling algorithm is needed. The des ign of the detailed scheduling algorithm is a major focus for researchers and service providers. In thi s study, a channel aware cross-layer scheduling algorithm for WiMAX networks has been proposed. This scheme employs the Signal to Noise Ratio (SNR) value, which allocates the bandwidth based on the information about the quality of the channel and the service requirements of each connection. Th e proposed algorithm is described in detail and evaluated, through a series of simulations. The QoS parameters of throughput, bandwidth efficiency and transmission efficiency have been measured in s imulation.

COMPARISON FOR WIMAX SCHEDULING ALGORITHMS AND PROPOSAL QUALITY OF SERVICE IMPROVEMENT IN WIMAX NETWORKS

The objective of the broadband wireless technologie s is to ensure the end to end Quality of Service (Q oS) for service classes. Wimax is a revolution in wirel ess networks which could support real time multimedia services. In order to provide QoS suppor t and efficient usage of system resources an intelligent scheduling algorithm is needed. The des ign of detailed scheduling algorithm is a major focus for researchers and service providers. In thi s study, a channel aware cross-layer scheduling algorithm for Wimax networks has been proposed. This scheme employs Signal to Noise Ratio (SNR) value which allocates bandwidth based on the inform ation about the quality of the channel and service requirements of each connection. The proposed algor ithm is described in detail and evaluated through series of simulation. The simulation results prove that the proposed algorithm reduces the packet loss rate and delay and thus improves throughput by 12.8 %.

A preemption-based scheduling algorithm for WiMAX networks

Several scheduling techniques were designed for the base station BS of IEEE 802.16e wireless interoperability of microwave access networks. However, depending on the BS scheduler alone to determine the servicing order of each connection might affect the accuracy of the scheduling process because the BS does not necessarily have enough up-to-date information about the current state of the connections at the subscriber station. In this paper, we propose a preemption-based scheduling algorithm that focuses on improving the quality of service requirements of real-time service flow classes. The proposed algorithm incorporates two schedulers, one at the BS and another one at the subscriber station. We have implemented and integrated the proposed algorithm with the network simulator NS2 using the Network and Distributed Systems Laboratory wireless interoperability of microwave access module. Simulation results have shown that the proposed approach outperforms other scheduling algorithms in terms of enhancing the throughput and the average delay of real-time quality of service classes. Copyright © 2013 John Wiley & Sons, Ltd.

SGSA: A SDMA–OFDMA greedy scheduling algorithm for WiMAX networks

Future wireless networks need to address the predicted growth in mobile traffic volume, expected to have an explosive growth in the next 5years mainly driven by video and web applications. Transmission schemes based on Orthogonal Frequency Division Multiple Access (OFDMA) combined with Space Division Multiple Access (SDMA) techniques are key promising technologies to increase current spectral efficiencies. A Joint SDMA–OFDMA system has to allocate resources in time, frequency and space dimensions to different mobile stations, resulting in a highly complex resource allocation problem. In contrast to related work approaches, in this paper we take a comprehensive view at the complete SDMA–OFDMA scheduling challenge and propose a SDMA–OFDMA Greedy Scheduling Algorithm (sGSA) for WiMAX systems. The proposed solution considers feasibility constraints in order to allocate resources for multiple mobile stations on a per packet basis by using (i) a low complexity SINR prediction algorithm, (ii) a cluster-based SDMA grouping algorithm and (iii) a computationally efficient frame layout scheme which allocates multiple SDMA groups per frame according to their packet QoS utility. A performance evaluation of the proposed sGSA solution as compared to state of the art solutions is provided, based on a comprehensive WiMAX simulation tool.

Game theory and time utility functions for a radio aware scheduling algorithm for WiMAX networks

In WiMAX systems the Base Station scheduler plays a key role as it controls the sharing of the radio resources among the users. The goal of the scheduler is multiple: achieve fair usage of the resources, satisfy the QoS requirements of the users, maximize goodput, and minimize power consumption, and at the same time ensuring feasible algorithm complexity and system scalability. Since most of these goals are contrasting, scheduler designers usually focus their attention on optimizing one aspect only. In this scenario, we propose a scheduling algorithm (called $$\mathrm{GTS_N}$$ ) whose goal is to contemporaneously achieve efficiency and fairness, while also taking into account the QoS requirements and the channel state. $$\mathrm{GTS_N}$$ exploits the properties of Time Utility Functions (TUFs) and Game Theory. Simulations prove that the performance of $$\mathrm{GTS_N},$$ when compared to that of several well-known schedulers, is remarkable. $$\mathrm{GTS_N}$$ provides the best compromise between the two contrasting objectives of fairness and efficiency, while QoS requirements are in most cases guaranteed. However, the exponential complexity introduced by the game theory technique makes it rather impractical and not computationally scalable for a large number of users. Thus we developed a suboptimal version, named sub- $$\mathrm{GTS_N}.$$ We show that this version retains most of the features and performance figures of its brother, but its complexity is linear with the number of users.