Resource management in QoS-aware wireless cellular networks

2011 Summer.Includes bibliographical references.Emerging broadband wireless networks that support high speed packet data with heterogeneous quality of service (QoS) requirements demand more flexible and efficient use of the scarce spectral resource. Opportunistic scheduling exploits the time-varying, location-dependent channel conditions to achieve multiuser diversity. In this work, we study two types of resource allocation problems in QoS-aware wireless cellular networks. First, we develop a rigorous framework to study opportunistic scheduling in multiuser OFDM systems. We derive optimal opportunistic scheduling policies under three common QoS/fairness constraints for multiuser OFDM systems--temporal fairness, utilitarian fairness, and minimum-performance guarantees. To implement these optimal policies efficiently, we provide a modified Hungarian algorithm and a simple suboptimal algorithm. We then propose a generalized opportunistic scheduling framework that incorporates multiple mixed QoS/fairness constraints, including providing both lower and upper bound constraints. Next, taking input queues and channel memory into consideration, we reformulate the transmission scheduling problem as a new class of Markov decision processes (MDPs) with fairness constraints. We investigate the throughput maximization and the delay minimization problems in this context. We study two categories of fairness constraints, namely temporal fairness and utilitarian fairness. We consider two criteria: infinite horizon expected total discounted reward and expected average reward. We derive and prove explicit dynamic programming equations for the above constrained MDPs, and characterize optimal scheduling policies based on those equations. An attractive feature of our proposed schemes is that they can easily be extended to fit different objective functions and other fairness measures. Although we only focus on uplink scheduling, the scheme is equally applicable to the downlink case. Furthermore, we develop an efficient approximation method--temporal fair rollout--to reduce the computational cost

An improved resource allocation scheme for WiMAX using channel information

In recent years, tremendous progress has been made in wireless communication systems to provide wireless coverage to end users at different data rates. WiMAX technology provides wireless broadband access over an extended coverage area in both fixed and mobility environments. Most of the existing resource allocation schemes allocate resources based on respective service class of the incoming users’ requests. However, due to variation in channel conditions, user mobility and diverse resource requirements QoS based resource allocation either results in over or under utilization of allocated resources. Therefore, resource allocation is a challenging task in WiMAX. This research proposes an improved resource management mechanism that performs resource allocation by taking into consideration not only the user service class but also the respective channel status. Based on these two parameters, this research aims to achieve improved resource allocation in terms of resource utilization, fairness and network throughput. First, a Channel Based Resource Allocation scheme is introduced where priority in resource allocation is given to users’ requests with relatively higher service classes and better channel status. To maintain fairness in resource allocation process, a Fair Resource Allocation Based Service mechanism is developed where priority is given to users’ requests having less additional resources demand. Finally, to improve throughput of the network, a Channel Based Throughput Improvement approach is proposed which dynamically selects a threshold level of channel gain based on individual channel gain of users. During resource allocation process, users above the threshold level are selected for resource allocation such that priority is given to users with high channel gain. Different simulation scenario results reveal an overall improved resource utilization from 87% to 91% and the throughput improves up to 15% when compared to existing schemes. In conclusion the performance of resource utilization is improved if channel status is considered as an input parameter