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

Priority-Based Resource Allocation for Downlink OFDMA Systems Supporting RT and NRT Traffics

Efficient radio resource management is essential in Quality-of-Service (QoS) provisioning for wireless communication networks. In this paper, we propose a novel priority-based packet scheduling algorithm for downlink OFDMA systems. The proposed algorithm is designed to support heterogeneous applications consisting of both real-time (RT) and non-real-time (NRT) traffics with the objective to increase the spectrum efficiency while satisfying diverse QoS requirements. It tightly couples the subchannel allocation and packet scheduling together through an integrated cross-layer approach in which each packet is assigned a priority value based on both the instantaneous channel conditions as well as the QoS constraints. An efficient suboptimal heuristic algorithm is proposed to reduce the computational complexity with marginal performance degradation compared to the optimal solution. Simulation results show that the proposed algorithm can significantly improve the system performance in terms of high spectral efficiency and low outage probability compared to conventional packet scheduling algorithms, thus is very suitable for the downlink of current OFDMA systems

Wireless OFDM Systems and Cross-Layer Optimization

The increasing popularity of wireless broadband services nowadays indicates that, future wireless systems will witness a rapid growth of high-data-rate applications with very diverse quality of service requirements. To support such applications under limited radio resources and harsh wireless channel conditions, dynamic resource allocation, which achieves both higher system spectral efficiency and better QoS, has been identified as one of the most promising techniques. In particular, jointly optimizing resource allocation across adjacent and even nonadjacent layers of the protocol stack leads to dramatic improvement in overall system performance. In this article an overview of recent research on dynamic resource allocation, especially for OFDM systems is provided. Recent work and open issues on cross-layer resource allocation and adaptation are also discusse

Cross layer designs for OFDMA wireless systems with heterogeneous delay requirements

This paper investigates a cross layer scheduling scheme for OFDMA wireless system with heterogeneous delay requirements. Unlike most existing cross layer designs which take a decoupling approach, our design considers both queueing theory and information theory in modeling the system dynamics. The cross layer design is formulated as an optimization of total system throughput, subject to individual user's delay constraint and total base station transmit power constraint. The optimal scheduling algorithm for the delay-sensitive cross layer optimization is to dynamically allocate radio resources based on users' channel state information, source statistics and delay requirements. Specifically, optimal power allocation was found to be multilevel water-filling where urgent users have higher water-filling levels, while optimal subcarrier allocation strategy is shown to be achievable by low complexity greedy algorithm. Simulation results also show the proposed jointly optimal power and subcarrier allocation policy can provide substantial throughput gain with all delay constraints being satisfied. © 2006 IEEE.published_or_final_versio

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

QoS based Radio Resource Management Techniques for Next Generation MU-MIMO WLANs: A Survey

IEEE 802.11 based Wireless Local Area Networks (WLANs) have emerged as a popular candidate that offers Internet services for wireless users. The demand of data traffic is increasing every day due to the increase in the use of multimedia applications, such as digital audio, video, and online gaming. With the inclusion of Physical Layer (PHY) technologies, such as the OFDM and MIMO, the current 802.11ac WLANs are claiming Gigabit speeds. Hence, the existing Medium Access Control (MAC) must be in a suitable position to convert the offered PHY data rates for efficient throughput. Further, the integration of cellular networks with WLANs requires unique changes at MAC layer. It is highly required to preserve the Quality of Service (QoS) in these scenarios. Fundamentally, many QoS issues arise from the problem of effective Radio Resource Management (RRM). Although IEEE 802.11 has lifted PHY layer aspects, there is a necessity to investigate MAC layer issues, such as resource utilization, scheduling, admission control and congestion control. In this survey, a literature overview of these techniques, namely the resource allocation and scheduling algorithms are briefly discussed in connection with the QoS at MAC layer. Further, some anticipated enhancements proposed for Multi-User Multiple-Input and Multiple-Output (MU-MIMO) WLANs are discussed

Wireless Power Transfer and Data Collection in Wireless Sensor Networks

In a rechargeable wireless sensor network, the data packets are generated by sensor nodes at a specific data rate, and transmitted to a base station. Moreover, the base station transfers power to the nodes by using Wireless Power Transfer (WPT) to extend their battery life. However, inadequately scheduling WPT and data collection causes some of the nodes to drain their battery and have their data buffer overflow, while the other nodes waste their harvested energy, which is more than they need to transmit their packets. In this paper, we investigate a novel optimal scheduling strategy, called EHMDP, aiming to minimize data packet loss from a network of sensor nodes in terms of the nodes' energy consumption and data queue state information. The scheduling problem is first formulated by a centralized MDP model, assuming that the complete states of each node are well known by the base station. This presents the upper bound of the data that can be collected in a rechargeable wireless sensor network. Next, we relax the assumption of the availability of full state information so that the data transmission and WPT can be semi-decentralized. The simulation results show that, in terms of network throughput and packet loss rate, the proposed algorithm significantly improves the network performance.Comment: 30 pages, 8 figures, accepted to IEEE Transactions on Vehicular Technolog

Cross-Layer Capacity Optimization In OFDMA Systems: WiMAX And LTE

Given the broad range of applications supported, high data rate required and low latency promised; dynamic radio resource management is becoming vital for newly emerging air interface technologies such as wireless interoperability for microwave access (Wimax) and long term evolution (lte) adopted by international standards. This thesis considers orthogonal frequency division multiple access (ofdma) system, which has been implemented in both Wimax and lte technologies as their air interface multiple access mechanism. A framework for optimized resource allocation with quality of service (qos) support that aims to balance between service provider\u27s revenue and subscriber\u27s satisfaction is proposed. A cross-layer optimization design for subchannel, for Wimax, and physical resource block (prb), for lte, and power allocations with the objective of maximizing the capacity (in bits/symbol/hz) subject to fairness parameters and qos requirements as constraints is presented. An adaptive modulation and coding (amc)-based cross-layer scheme has also been proposed in this thesis by adopting an amc scheme together with the cross-layer scheme to realize a more practical and viable resource allocation. The optimization does not only consider users channel conditions but also queue status of each user as well as different qos requirements. In the proposed framework, the problem of power allocation is solved analytically while the subchannel/prb allocation is solved using integer programming exhaustive search. The simulation and numerical results obtained in this thesis have shown improved system performance as compared to other optimization schemes known in literature