Cognitive radio-based framework and self-optimizing temporal-spectrum block scheduling for QoS provisioning in WiMAX
Introduction
Recently, broadband wireless access becomes ubiquitous. This makes the already heavily crowded radio spectrum much scarcer [1]. Cognitive radio (CR) is a promising technology to alleviate the increasing stress on the fixed radio spectrum. In cognitive radio based opportunistic spectrum access (OSA) networks, the secondary (unlicensed) users can periodically sense and identify available channels which are referred to as white spaces (WS) as the parts of the spectrum not in active use by the primary users. Based on the results of spectrum sensing, the secondary users dynamically tune its transceivers to the identified WSs to access the wireless channel without disturbing the communications of the primary users.
Broadband wireless access networks, e.g. WiMAX [2] systems, have received a lot of attention from academic and industrial researchers in the last few years as WiMAX systems have the ability to provide broadband wireless access and the potential ability to compete with existing wired and wireless networks. WiMAX can support four different QoS levels. QoS provisioning to such heterogeneous traffic with integrated real-time and non-real-time traffic is an important issue in the deployment of WiMAX systems. To tackle the QoS provisioning issue, one of the important QoS support mechanisms is the scheduling scheme. However, the detail of scheduling scheme has been left undefined in the IEEE 802.16d standard.
Scheduling scheme is essential in the provisioning of guaranteed QoS parameters, such as packet delay, packet loss rate and throughput. To design a scheduling scheme in WiMAX systems is especially challenging because a wireless communication channel has a high variable link error rate and a scarce capacity. The medium access control (MAC) protocol and scheduling solutions have to be developed specially in a cross-layer approach for this environment [3]. A few cross-layer MAC and opportunistic scheduling designs tailored for WiMAX have been proposed recently. With the help of several additional parameters for the preference metrics which are the priority of connections or users to be determined by the opportunistic scheduler for its transmission service, the proposed schemes were shown to have the capability to achieve satisfactory performance in the given network conditions.
However, those scheduling decisions are made based solely on bandwidth requirements, system capacity, QoS of connections and Physical (PHY) time-varying channel without considering the mapping constraint. Actually, Downlink (DL) and Uplink (UL) resource scheduling are done in two steps in WiMAX OFDMA systems. In the first step, those proposed schedulers decide the number of sub-carriers and the number of slots in units of symbol-duration to be allocated to each subscriber station (SS) and those allocated sub-carriers and symbol-durations are further distributed to each connection at the SS. In the second step, the mapping algorithms allocate the scheduled UL data bursts from each SS into two-dimensional rectangular “areas” [2] whereby the length of the area is the number of sub-carriers and the width is the number of OFDM symbols.
The two-dimensional rectangular mapping problem is a variation of bin-packing problem. We define this two-dimensional bin as a temporal-spectrum block (TSB). Now, we have a “tiling” problem where the objective is to fill a given area with TSBs. This packing problem is known to be NP-complete [4]. There have been many proposals to tackle this problem. However, there is no easy way to achieve optimality with simple computation.
Autonomic computing (AC) is supposed to be a novel way to reduce the computational complexity of the scheduling and bin-packing problem. The overarching goal of AC is to realize computer, software systems and applications that can manage themselves in accordance with high-level guidance from humans [5].
The existing state-of-the-art scheduling solutions and mapping strategies tackle the issue of QoS provisioning separately. From the system’s point of view, sub-carrier allocation scheme, symbol-duration scheduling scheme and mapping strategy have to be considered collaboratively based on the PHY radio conditions in order to provide much more efficient QoS provisioning to the heterogeneous traffic in WiMAX systems.
Motivated by the technology of CR to tackle fixed spectrum-allocation problem; inspired by the self-optimizing function of AC to manage complexity, in this paper, we propose a novel cross-layer CR-based QoS support framework and a cross-layer CR-based joint sub-carrier allocation and symbol-duration scheduling cum a mapping scheme to provide QoS to heterogeneous traffic in WiMAX PMP OFDMA system.
The proposed framework has two outstanding modules, which are the CR-based intelligent spectrum management module (ISMM) and Autonomic Self-optimizing Scheduling cum Mapping Module.
With a cross-layer approach, the proposed ISMM uses the adaptive and cooperative sensing scheme as suggested in paper [6]. It periodically senses unused portions of the spectrum. It can intelligently exploit unused spectrums and spreads over them. Thus, the WiMAX system can operate under more than one frequency to improve the system capacity significantly and provide better QoS to real-time traffic in the system.
To the best of our knowledge, the proposed solution is the first piece of the solution with the following features in the literature. The proposed Autonomic Self-optimizing Scheduling cum Mapping Module can perform sub-carrier allocation, symbol-duration scheduling and TSB mapping collaboratively by an intelligent self-optimizing approach. Our proposal can guarantee QoS requirements for different types of service classes while expanding the capacity of the system. We have the following major contributions in this work.
- (1)
The proposed framework is equipped with a CR-based ISMM at the PHY layer. It exploits unused portions of the spectrum. If the BS or an SS transmits a packet belonging to BE service class, the packet could be transmitted in WS. As a result, the system throughput can be improved significantly.
- (2)
The proposed scheduling algorithm takes the mapping constraint into consideration. It has a unique feature which is the associative cooperation of the scheduling and mapping scheme.The mapping scheme can influence the scheduling decision, in other words, it can fine-tune the scheduling decision by the self-optimizing function of AC. The complexity of scheduling and mapping can be reduced significantly. The QoS requirements of real-time traffic can be satisfied while higher system throughput can be achieved.
The rest of the paper is organized as follows. In Section 2, we describe the research background, various aspects of the MAC and PHY layers of WiMAX system and the existing proposals related to our work. In Section 3, we describe our proposed cross-layer CR-based QoS support framework and CR-based self-optimizing joint sub-carrier allocation and symbol-duration scheduling cum mapping scheme. In Section 4, we present a channel model and a queueing model to analyze the average packet delay theoretically. In Section 5, we present our simulation model design and the simulation results. Finally, in Section 6, we conclude the paper with a summary.
Section snippets
Research background
The main technical background that relates to our work is presented in this Section, which includes the introduction of WiMAX system, Intelligent Spectrum Management, AC and existing opportunistic scheduling schemes and mapping strategies. An overview of WiMAX networks is briefly described with their features outlined. Moreover, the concept of Intelligent Spectrum Management and AC are conceptually explained. Various existing self-optimizing schemes are surveyed. The self-optimizing scheme
Proposed solution
The IEEE 802.16d standard has left the details of scheduling algorithm and the mapping algorithm undefined. The existing proposed scheduling schemes operate under the fixed spectrum allocation (FSA) scheme with a pre-defined fixed spectrum and a fixed channel bandwidth without consideration on the mapping constraints. In order to overcome the shortcomings, a CR-based ISMM has to be designed to embed in the current QoS architecture in WiMAX WirelessHUMAN™-OFDMA systems. A new interface of White_
Queueing analytical model
To analyze a packet-level QoS in real-time and non-real-time data transmission, the network performance parameters such as average packet delay and throughput need to be investigated. A queueing analytical model can be used to obtain the network performance parameters. In this section, we perform a queueing model analysis of the WiMAX OFDMA/TDD system under study in order to obtain the effective data transmission rate of sub-carriers and the average packet delay of UGS and rtPS service classes.
Performance analysis
We have carried out a series of simulation experiments to evaluate the performance of the proposed cross-layer CR-based QoS support framework and SOS2M scheduling scheme in the UL channel of the WiMAX WirelessHUMAN™ OFDMA/TDD system. We compare the performances of the JPCAS proposal in [27] with that of our scheduling scheme. The average packet delays of service classes obtained by quantitative analysis of the queueing model are further compared and validated with the simulation results. The
Conclusion
In this paper, we have proposed the novel CR-based QoS support framework and CR-based self-optimizing TSB scheduling which is a joint sub-carrier allocation and symbol-duration scheduling cum mapping scheme (SOS2M) in WiMAX PMP WirelessHUMAN™ OFDMA/TDD systems. With the cross-layer approach by applying AMC to the sub-carriers in wireless channel, the proposed SOS2M can improve the performance of the WiMAX system. Based on QoS requirement parameters like MSTR and packet loss rate of rtPS service
Victor LU Jinchang received his BE in Information and Communication Engineering from Zhejiang University in 1989. He received his MS in Information Studies from Nanyang Technological University in 2005. He is currently a Ph.D. candidate working toward his Ph.D. degree in the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore.
His research interests include QoS support mechanisms and algorithms in WiMAX networks, cognitive radio networks & cognitive
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Cited by (0)
Victor LU Jinchang received his BE in Information and Communication Engineering from Zhejiang University in 1989. He received his MS in Information Studies from Nanyang Technological University in 2005. He is currently a Ph.D. candidate working toward his Ph.D. degree in the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore.
His research interests include QoS support mechanisms and algorithms in WiMAX networks, cognitive radio networks & cognitive Digital TV over WiMAX and WRAN networks and bioinformatics Self-organization & Self-optimization autonomic networks.
Maode Ma received his BE degree in computer engineering from Tsinghua University in 1982, ME degree in computer engineering from Tianjin University in 1991 and Ph.D. degree in computer science from Hong Kong University of Science and Technology in 1999. Dr. Ma is an Associate Professor in the School of Electrical and Electronic Engineering at Nanyang Technological University in Singapore. He has extensive research interests including wireless networking, optical networking, grid computing, bioinformatics, and so forth. He has been a member of the technical program committee for more than 80 international conferences. He has been a technical track chair, tutorial chair, publication chair, and session chair for more than 40 international conferences. Dr. Ma has published more than 130 international academic research papers on wireless networks and optical networks. He currently serves as an Associate Editor for IEEE Communications Letters, an Editor for IEEE Communications Surveys and Tutorials, and an Associate Editor for International Journal of Wireless Communications and Mobile Computing, Security and Communication Networks, International Journal of Vehicular Technology, Journal of Network and Computer Applications, and Journal of Computer Systems, Networks, and Communications.