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系統識別號 U0002-3007201300133400
中文論文名稱 IEEE 802.16 無線寬頻網路中,提升頻寬資源利用率之排程演算法設計
英文論文名稱 Bandwidth Utilization Improvement Scheduling Algorithms for IEEE 802.16 Wireless Broadband Networks
校院名稱 淡江大學
系所名稱(中) 資訊工程學系博士班
系所名稱(英) Department of Computer Science and Information Engineering
學年度 101
學期 2
出版年 102
研究生中文姓名 蔣季陶
研究生英文姓名 Chi-Tao Chiang
學號 897410113
學位類別 博士
語文別 英文
口試日期 2013-05-31
論文頁數 101頁
口試委員 指導教授-石貴平
委員-陳裕賢
委員-陳宗禧
委員-張志勇
委員-廖文華
委員-游國忠
委員-王三元
委員-石貴平
中文關鍵字 頻寬分配演算法  IEEE 802.16  網狀網路  點對多點網路  無線寬頻網路  全球互通微波存取 
英文關鍵字 Bandwidth Allocation Algorithms  IEEE 802.16  Mesh Networks  Point-to-multipoint Networks  Wireless Broadband Networks  Worldwide Interoperability for Microwave Access (WiMAX) 
學科別分類 學科別應用科學資訊工程
中文摘要 在無線網路的環境中,增加頻寬利用率一直以來是一個很重要的議題之一,尤其是在 802.16 寬頻網路環境。其原因在於 802.16 使用的頻寬大小是有限的,同時,802.16 運作的頻譜必須透過付費授權才能夠使用。因此,對於一個電信業者而言,如何有效率的來使用這些有限的頻寬以最大化系統效能,是各大電信業者共同努力的目標。有鑑於此,本研究將分別就 802.16 支援的兩種網路環境:點對多點(Point-to-multipoint, PMP)與網狀網路(Mesh),來針對問題來進行深入的探討與研究。
在IEEE 802.16 點對多點網路,頻寬資源的分配基本單位是Burst,而每個Burst是由許多的Slot所構成的二維空間。本研究探討問題是Burst Allocation Problem (簡稱BAP),在BAP中,將決定每個Burst的形狀與位置,以最大化Downlink頻寬利用率。為了解決BAP,我們提出Burst Fragmentation, Packing and Scheduling Algorithm (簡稱 BFPA) 與 Burst Shifting Scheme (簡稱BSS)。BFPA主要可以分成3個Schemes,首先,在Burst Allocation Scheme中,BS會透過決定每個Burst在Downlink Subframe中的位置與排入的先後順序來解決外部碎裂的問題發生,然而,在Allocation的過程中,可能會有內部碎裂的問題發生,因此,在第二個Scheme中,將針對發生內部碎裂的Burst進行切割,釋放內部碎裂的空間給其他Burst使用,同時,所切割出來的Burst將填補部分外部碎裂的空間,最後,再透過Burst Packing的方式,將支援相同調變的Burst進行合併,降低DL-MAP Control Overhead。BSS的運作是在給定一組的Burst Allocation的情況, BSS 主要是利用Burst Overlapping概念,Burst Overlapping概念是讓相鄰兩有內度碎裂的Burst能夠透過調整內部碎裂在Burst中的位置,利用Burst平移,使相鄰兩Burst可以共用內部碎裂的Slots來減少Slot的浪費,進而增加頻寬利用率。
在IEEE 802.16 網狀網路的環境中,頻寬資源分配的基本單位是Minislots,本論文考量在IEEE 802.16 無線網狀網路傳輸環境中,針對規格書所定義的集中式排程 (Centralized Scheduling) 機制下提出一個分散式時槽排程機制。此機制的目標在於有效地分配Minislots資源使其能充分的利用,期望能夠使用最少的Minislots 來滿足網路中節點的需求。基於此目的,本論文先使用整數線性規劃 (Integer Linear Problem, ILP) 的方式來建構此排程問題的模型。此數學模型考慮傳輸對在不會互相影響的前提下,Minislot 的最佳使用數量及排程方式。然而ILP屬於NP-complete 之問題,因此本論文因而進一步探討分散式時槽分散式機制以符合IEEE 802.16 無線網狀網路之真實情況。本論文首先探討不當的選擇Minislot 將會衍生出的三大造成整體網路執行效能下降問題:資料傳輸碰撞 (Data Collision Problem) 、Flow內部Minislot不足問題 (Intra-flow Minislot Insufficient Problem, Intra-flow MIP) 及Flow間Minislot不足問題 (Inter-flow Minislot Insufficient Problem, Inter-flow MIP) 。有鑑於此,本論文對於網路中節點使用Minislots傳輸方式提出Minislots使用限制(Minislots Usage Constraints, MUCs)與Minislots決定政策(Minislots Decision Strategies, MDSs),並且同時考慮資料傳輸路徑上Minslots 的衝突問題及Minislot 的重覆使用,提出一分散式Minislot 時槽排程之機制。本論文預期透過此分散式MInislot排程機制之設計,致使多對傳輸對可在同時間內進行傳輸,並降低碰撞的機率,藉以提高頻寬利用率。
除了上述方法提出外,本論文亦透過模擬的方式來驗證方法的效能,同時並與相關研究進行比較,透過多項的效能評估,可以發現本研究提出的做法不管在網狀網路與點對多點網路,對於頻寬使用之提升均有很大的助益。
英文摘要 Improving bandwidth utilization is one of the important research issues, especially in the IEEE 802.16 wireless broadband networks. The IEEE 820.16 standard supports two network topologies, the point-to-multipoint networks and mesh networks. In this dissertation, bandwidth utilization improving scheduling algorithms are proposed for these two supported networks, respectively.
For the point-to-multipoint networks, burst is an atomic bandwidth allocation unit for downlink and uplink transmissions in IEEE 802.16 orthogonal frequency division multiple access (OFDMA) systems. This dissertation investigates downlink burst scheduling problem in IEEE 802.16 OFDMA systems. Solving this problem with the objective of maximizing downlink bandwidth utilization, a burst fragmentation, packing and allocation algorithm is proposed to decide the position and shape of each burst in the downlink subframe. For further improving the downlink bandwidth utilization in an given burst allocation scenario, a burst shifting scheme is proposed to make neighboring bursts share and utilize wasted slots caused by the rectangular mapping constraint of bursts by means of arranging the position of the wasted slots in bursts.
For the mesh networks, minislot is an atomic bandwidth allocation unit for data transmissions among subscriber stations and base station. This dissertation overcomes minislot scheduling problem for IEEE 802.16 mesh networks and formulates this problem as an integer linear programming model. Due to the high computational complexity for solving integer linear programming model at subscriber stations and the degrade of bandwidth utilization resulted from data collision problems and minislot insufficient problems, this dissertation proposes a decentralized minislot scheduling protocol to make subscriber stations, rather than the base station, schedule minislot usage for throughput gains in the IEEE 802.16 mesh networks. The decentralized minislot scheduling protocol includes minislot usage constraints and minislot decision strategies to alleviate data collisions and minislot insufficient problems as well as to increase bandwidth utilization. The proposed protocol not only can accommodate to the IEEE 802.16 standard, but also make subscriber stations schedule minislots with the latest minislot usage information.
Based on the above mentions, this dissertation conducts a series of simulations to evaluate the performance of proposed bandwidth utilization improving scheduling algorithms for the two supported networks, respectively. The simulation results show that the proposed algorithms and protocol outperform related work in the bandwidth utilization.
論文目次 Contents
Chapter 1 Introduction 1
1.1 Network Topologies for IEEE 802.16 Standard 2
1.2 Bandwidth Utilization Improvement in PMP Networks 4
1.3 Bandwidth Utilization Improvement in Mesh Networks 7
1.4 Overview of Contributions 9
1.5 Organization of the Dissertation 10
Chapter 2 Related Work 11
2.1 Related Work in PMP Networks 11
2.2 Related Work in Mesh Networks 16
Chapter 3 Bandwidth Utilization Improvement for PMP Networks 20
3.1 Terminologies 20
3.2 Burst Fragment, Packing and Allocation Algorithm (BFPA) 21
3.2.1 Burst Allocation Scheme 22
3.2.2 Burst Fragmentation and Packing Scheme 26
3.2.3 Burst Swapping Scheme 29
3.3 Burst Shifting Scheme (BSS) 30
3.3.1 Feasibility of Burst Overlapping 31
3.3.2 Problem Formulation 33
3.3.3 Design Details 34
3.4 Performance Evaluations 40
3.4.1 Performance Evaluations of BFPA 40
3.4.2 Simulation I: Normal Subchannel Condition 41
3.4.3 Simulation II: Bad Subchannel Condition 45
3.4.4 Simulation III: Good Subchannel Condition 49
3.4.5 Performance Evaluations of BSS 53
Chapter 4 Bandwidth Utilization Improvement for Mesh Networks 57
4.1 Notations 57
4.2 Minislot Scheduling Problems (MSP) 59
4.2.1 Data Collision Problem 59
4.2.2 Minislot Insufficient Problems 60
4.3 Integer Linear Programming (ILP) Model for MSP 62
4.4 Decentralized Minislot Scheduling Protocol (DMSP) 66
4.4.1 Determination of the Validity of Minislots based on Minislot Usage Constraints 67
4.4.2 Collection of κ-hops Results of Minislot Usage Constraints 70
4.4.3 Determination of Minislot Usage for Data Transmissions based on Minislot Decision Strategies 71
4.5 Analysis of the Proposed Protocol 74
4.5.1 Time Complexity of DMSP 75
4.5.2 Message Complexity of DMSP 76
4.6 Performance Evaluations 77
4.6.1 Simulation I: Impact of κ 78
4.6.2 Simulation II: Comparisons with Other Protocols 79
Chapter 5 Conclusions 84
5.1 Contributions 84
5.2 Future Work 86
Bibliography 87
Publication List 99

List of Figures
Figure 1.1 Illustrations of (a) an IEEE 802.16 mesh network and (b) a routing tree. 3
Figure 1.2 An IEEE 802.16 OFDMA Frame Structure. 5
Figure 1.3 Demonstration of IEEE 802.16 mesh frame structure (t = 16, m = 256). 7
Figure 3.1 Example of (a) G P− 1 based on (b) the supported modulation levels of subchannels of each MS. 23
Figure 3.2 Types of the subchannel overlapping, (a)-(d) full overlapping (FO), (e) non-overlapping (NO) and (f)-(j) partial-overlapping (PO). 24
Figure 3.3 Example of the bursts allocations (a) before and (b) after fragmentation. 27
Figure 3.4 Types of relations among bursts for packing, (a), (b) and (c) are suitable for packing, and (s) and (d) are not. 29
Figure 3.5 Example of the bursts allocations (a) before and (b) packing. 30
Figure 3.6 Example of burst overlapping of two neighboring bursts. (a) The IF of b i places in the TR corner. (b) The IF of b i places in the BR corner. 33
Figure 3.7 Example of burst overlapping of b i and b j , where ∆y > 0. (a) y i < y j + h j < y i + h i . (b) y j + h j = y i + h i. 36
Figure 3.8 Example of burst overlapping of b i and b j , where ∆y < 0. (a) y j < y i + h i < y j + h j . (b) y i + h i = y j + h j. 37
Figure 3.9 Example of burst overlapping of b i and b j , where ∆y = 0. (a) h i > h j . (b) h i = h j . (c) h i < h j. 38
Figure 3.10 Illustrations of the network density on (a) the network throughput and (b) service ratio in the normal subchannel condition. 42
Figure 3.11 Illustrations of the network density on (a) the DL-MAP IE Efficiency and (b) average DL bandwidth utilization in the normal subchannel condition. 43
Figure 3.12 Illustrations of the network density on (a) the network throughput and (b) service ratio in the bad subchannel condition(25% subchannels are supported 64-QAM 3/4 for all MSs). 46
Figure 3.13 Illustrations of the network density on (a) the DL-MAP IE Efficiency and (b) average DL bandwidth utilization in the bad subchannel condition(25% subchannels are supported 64-QAM 3/4 for all MSs). 47
Figure 3.14 Illustrations of the network density on (a) the network throughput and (b) service ratio in the good subchannel condition(75% subchannels are supported 64-QAM 3/4 for all MSs). 50
Figure 3.15 Illustrations of the network density on (a) IE Efficiency and (b) average DL bandwidth utilization in the good subchannel condition(75% subchannels are supported 64-QAM 3/4 for all MSs). 51
Figure 3.16 Illustrations of the network density on (a) the network throughput and (b) bandwidth utilization. 54
Figure 4.1 Examples of the intra-flow minislot insufficient problem: minislot usage of f 12..0 before adjustment and after adjustment. 62
Figure 4.2 Example of the inter-flow minislot insufficient problem: minislot usage of (a) f 0..11 , (b) f 12..0 before adjustment and (c) f 12..0 after adjustment. 63
Figure 4.3 Examples for (a) the determination of the validity of minislots for p 10 → 6 based on minislot usage constraints, and (b) the determination of minislot usage for SS 12 ’s data transmissions based on minislot decision strategies. 68
Figure 4.4 Impacts of the network density and κ on (a) the network throughput and (b) the control overhead. 80
Figure 4.5 Impacts of the network density on (a) the network throughput and (b) control overhead. 81
Figure 4.6 Impacts of the network density on (a) the packet delay and (b) minislot utilization. 83

List of Tables
Table 2.1 Comparisons of Related Work in PMP Networks. 12
Table 2.2 Comparisons of Related Work in Mesh Networks. 17
Table 3.1 Simulation Parameters and Values for BFPA and BSS. 56
Table 4.1 Simulation Parameters and Values for DMSP. 78
參考文獻 [1] IEEE Standard for Air Interface for Broadband Wireless Access Systems. IEEE Std 802.16-2012 (Revision of IEEE Std 802.16-2009), pages 1–2542, 2012.
[2] A. I. Adedapo, M. Mzyece, and G. Noel. Performance Evaluation of Variable Rates Raptor Codes in Mobile WiMAX. In Proceedings of the IEEE International Conference on Industrial Technology, pages 1371–1376, 2013.
[3] I. Ahmed, A. Mohammed, and H. Alnuweiri. On the Fairness of Resource Allocation in Wireless Mesh Networks: a Survey. Wireless Networks, pages 1–18, 2013. Article in Press.
[4] S. A. Ahson and M. Ilyas. WiMAX Handbook. Auerbach Publication, 2007.
[5] Y. Alpert, J. Segev, and O. Sharon. Coupled PHY, MAC and Repetition Scheduling in IEEE 802.16 WiMAX Systems. Physical Communication, 7(1):14–29, 2013.
[6] A. M. Alsahag, B. M.Ali, N. K.Noordin, and H. Mohamad. Fair Uplink Bandwidth Allocation and Latency Guarantee for Mobile WiMAX Using Fuzzy Adaptive Deficit Round Robin. Journal of Network and Computer Applications, 2013. Article in Press.
[7] J. G. Andrews, A. Ghosh, and R. Muhamed. Fundamentals of WiMAX: Understanding Broadband Wireless Networking. Prentice Hall Communications Engineering and Emerging Technologies, 2007.
[8] A. Bachmutsky, M. Katz, and F. Fitzek. WiMAX Evolution: Emerging Technologies and Applications. Wiley, 2009.
[9] J.-Y. Baek and Y.-J. Suh. Heuristic Burst Construction Algorithm for Improving Downlink Capacity in IEEE 802.16 OFDMA Systems. IEEE Transactions on Mobile Computing (TMC), 11(1):155–168, January 2012.
[10] M. Cao, V. Raghunathan, and P.R.Kumar. A Tractable Algorithm for Fair and Efficient Uplink Scheduling of Multi-hop WiMAX Mesh Networks. In Proceeding of the IEEE Workshop on Wireless Mesh Networks (WiMesh), pages 93–100, September 2006.
[11] S.-I. Chakchai, R. Jain, and A.-K. Tamimi. eOCSA: An Algorithm for Burst Mapping with Strict QoS Requirements in IEEE 802.16e Mobile WiMAX Networks. In Proceedings of the IFIP conference on Wireless days, pages 204–208, December 2009.
[12] S.-I. Chakchai, R. Jain, and A.-K. Tamimi. Scheduling in IEEE 802.16e Mobile WiMAX Networks: Key Issues and a Survey. IEEE Journal on Selected Areas in Communications (JSAC), 27(2):156–171, February 2009.
[13] J. Chen, C. Caixia, and Q. Guo. An Odd-even Alternation Mechanism for Centralized Scheduling in WiMAX Mesh Networks. In Proceeding of the IEEE Global Telecommunications Conference (GLOBECOM), pages 1–6, November 2006.
[14] L.-W. Chen, Y.-C Tseng, Y.-C. Wang, D.-W. Wang, and J.-J. Wu. Exploiting Spectral Reuse in Routing, Resource Allocation, and Scheduling for IEEE 802.16 Mesh Networks. IEEE Transactions on Vehicular Technology, 58(1):301–313, January 2009.
[15] S. Chieochan and E. Hossain. Adaptive Radio Resource Allocation in OFDMA systems: A survey of the State-of-the-art Approaches. Wireless Communications and Mobile Computing, 9(4):513–527, 2009.
[16] T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein. Introduction to Algorithms. McGraw-Hill Higher Education, 2 edition, 2002.
[17] Q. Dayou, N. Cvijetic, J. Hu, and T. Wang. Optical OFDM Transmission in Metro/Access Networks. In Proceedings of Conference on Optical Fiber Communication, Technical Digest Series, 2009.
[18] A. Erta, C. Cicconetti, and L. Lenzini. A Downlink Data Region Allocation Algorithm for IEEE 802.16e OFDMA. In Proceedings of the International Conference on Information, Communications and Signal Processing (ICICS), pages 1–5, December 2007.
[19] D. Feng, C. Jiang, G.Lim, and G.Feng. A Survey of Energy-efficient Wireless Communications. IEEE Communications Surveys and Tutorials, 15(1):167–178, 2013.
[20] L. Fu, Z. Cao, and P. Fan. Spatial Reuse in IEEE 802.16 Based Wireless Mesh Networks. In Proceedings of the IEEE International Symposium on Communications and Information Technology (ISCIT), volume 2, pages 1358–1361, October 2005.
[21] S. Gilani, A. Nazir, E. Ullah Munir, M. Rehan, M. Nauman, W. Anwar, and W.Nasir. Hierarchical Model of IEEE 802.21 Media Independent Information Service (MIIS).
Research Journal of Applied Sciences, Engineering and Technology, 5(22):5142–5147, 2013.
[22] H. Gowda, R. Lakshmaiah, M. Kaur, C. Mohanram, M.Singh, and S. Dongre. A Slot Allocation Mechanism for Diverse QoS Types in OFDMA Based IEEE 802.16e Systems. In Proceedings of the IEEE International Conference on Advanced Communication Technology (ICACT), pages 13–17, February 2007.
[23] A. S. Hamza, S. S. Khalifa, H. S. Hamza, and K.Elsayed. A Survey on Inter-Cell Interference Coordination Techniques in OFDMA-Based Cellular Networks. IEEE Communications Surveys and Tutorials, 2013. Article in Press.
[24] B. Han, W. Jia, and L. Lin. Performance Evaluation of Scheduling in IEEE 802.16 Based Wireless Mesh Networks. Computer Communications, 30(4):782–792, February 2007.
[25] F. Jin, A. Arora, J. Hwang, and H.-A Cho. Routing and Packet Scheduling for Throughput Maximization in IEEE 802.16 Mesh Networks. In Proceeding of the IEEE International Confrence on Broadband Communications, Networks and Systems (BROADNETS), pages 574–582, September 2007.
[26] X. Jin, J. Zhou, J. Hu, J. Shi, and Y. Sun. An Efficient Downlink Data Mapping Algorithm for IEEE 802.16e OFDMA Systems. In Proceeding of the IEEE Global Telecommunications Conference (GLOBECOM), pages 1–5, December 2008.
[27] E. Kofidis, D. Katselis, A. Rontogiannis, and S. Theodoridis. Preamble-based Channel Estimation in OFDM/OQAM Systems: A Review. Signal Processing, 93(7):2038–2054, 2013.
[28] C. Kosta, B. Hunt, A. U.Quddus, and R. Tafazolli. On Interference Avoidance through Inter-Cell Interference Coordination (ICIC) Based on OFDMA Mobile Systems. IEEE Communications Surveys and Tutorials, 2012. Article in Press.
[29] A. Kumar and D. Manjunath. A Tutorial Survey of Topics in Wireless Networking: Part I. Sadhana - Academy Proceedings in Engineering Sciences, 32(6):619–643, 2007.
[30] A. Kumar and D. Manjunath. A Tutorial Survey of Topics in Wireless Networking: Part II. Sadhana - Academy Proceedings in Engineering Sciences, 32(6):645–681, 2007.
[31] R. Kumari and S. K. Behera. Mushroom-shaped Dielectric Resonator Antenna for WiMAX Applications. Microwave and Optical Technology Letters, 55(6):1360–1365, 2013.
[32] T. D. Lagkas, P. Sarigiannidis, and M. Louta. On Analyzing the Intra-frame Power Saving Potentials of the IEEE 802.16e Downlink Vertical Mapping. Computer Networks, 57(7):1656–1673, 2013.
[33] T. D. Lagkas, P. G. Sarigiannidis, M.Louta, and P. Chatzimisios. Exploring the Intra-frame Energy conservation Capabilities of the Horizontal Simple Packing Algorithm in IEEE 802.16e Networks: An Analytical Approach. Wireless Networks, 19(4):547–558, 2013.
[34] Y.-C. Lai and Y.-H. Chen. A Best Block Exploring Algorithm for Two-dimensional Downlink Burst Construction in IEEE 802.16 Networks. Journal of Network and Computer Applications (JNCA), 35(6):2092–2104, November 2012.
[35] B. G. Lee. Broadband Wireless Access and Local Networks: Mobile WiMAX and WiFi. Artech House, 2008.
[36] T.-H. Lee, C.-H. Liu, A. Soleiy, G. Campbell, and Y.-W. Kuo. A Data Mapping Algorithm for Two-Level Requests in WiMAX Systems. In Proceedings of the IEEE Vehicular Technology Conference (VTC), pages 1–5, May 2012.
[37] T.-H. Lee, C.-H. Liu, J. Yau, and Y.-W Kuo. Maximum Rectangle-Based Down-Link Burst Allocation Algorithm for WiMAX Systems. In Proceeding of the IEEE Region 10 Conference (TENCON), pages 530 – 534, November 2011.
[38] F. Li, D. Zhang, and M. Wang. Multiuser Multimedia Communication over Orthogonal Frequency-division Multiple Access Downlink Systems. Concurrency Computation Practice and Experience, 25(9):1081–1090, 2013.
[39] J. Liang, H. Yin, X. Zhang, T. Zhou, and L. Feng. Two Novel High Spectral Efficient Frequency Reuse Schemes in OFDMA Cellular Relay Networks. Journal of Information and Computational Science, 10(6):1777–1787, 2013.
[40] S. Liu, S. Feng, W. Ye, and H. Zhuang. Slot Allocation Algorithms in Centralized Scheduling Scheme for IEEE 802.16 Based Wireless Mesh Networks. Computer Communications, 32(5):943 – 953, March 2009.
[41] Y. Lu and G. Zhang. Maintaining Routing Tree in IEEE 802.16 Centralized Scheduling Mesh Networks. In Proceedings of the International Conference on Computer Communications and Networks (ICCCN), pages 240–245, August 2007.
[42] A. Maeder and N. Zein. OFDMA in the Field: Current and Future Challenges. Computer Communication Review, 40(5):71–76, 2010.
[43] A. Maeder and N. Zein. OFDMA in the Field: Current and Future Challenges. In Proceedings of the SIGCOMM 2010 Conference, pages 71–76, 2010.
[44] L. Nuaymi. WiMAX: Technology for Broadband Wireless Access. Auerbach Publication, 2007.
[45] T. Nunome and S. Tasaka. The Effectiveness of Adaptive Capacity Allocation on QoE of Audio-video IP Transmission over the IEEE 802.16 BE Service. IEICE Transactions on Communications, 9(2):441–450, 2013.
[46] A. Nusairat and X.-Y. Li. WiMAX/OFDMA Burst Scheduling Algorithm to Maximize Scheduled Data. IEEE Transactions on Mobile Computing (TMC), 11(11):1692–1705, November 2012.
[47] F. Ohrtman. WiMAX Handbook : Building 802.16 Networks. McGraw-Hill Professional, 2005.
[48] T. Ohseki, M. Morita, and T. Inoue. Burst Construction and Packet Scheme for OFDMA Downlinks in IEEE 802.16 Systems. In Proceeding of the IEEE Global Telecommunications Conference (GLOBECOM), pages 4307–4311, November 2007.
[49] A. Oliveira, S. Lucena, C. Campos, and A. De A. Rocha. Packet Dispersion Techniques over WiMAX Links: Challenges and Problems. IEEE Communications Magazine, 51(3):154–159, 2013.
[50] D. Pareek. WiMAX: Taking Wireless to the MAX. Auerbach Publications, 2012.
[51] D. Park, H. Kim, Y. Kim, and W. Ryu. Performance Analysis of Multicast Service Using MBS Region in Mobile WiMAX System. In Proceedings of the International Conference on Advanced Communication Technology (ICACT), pages 949–952, 2013.
[52] R. Prasad and F. J. Velez. WiMAX Networks: Techno-Economic Vision and Challenges. Springer, 2010.
[53] P.Trivedi and A.Verma. The Signal to Noise and Distortion Ratio for Sigma Delta ADC for SDR 3G/4G Mobile Receivers. In Proceedings of SPIE - The International Society for Optical Engineering, volume 8760, 2013.
[54] S. Ray, I. Demirkol, and W. Heinzelman. Supporting Bursty Traffic in Wireless Sensor Networks through a Distributed Advertisement-based TDMA Protocol (ATMA).Ad Hoc Networks, 11(3):959–974, 2013.
[55] M. Salem, A. Adinoyi, M. Rahman, H. Yanikomeroglu, D. Falconer, and E. Kim. An Overview of Radio Resource Management in Relay-enhanced OFDMA-based Networks. IEEE Communications Surveys and Tutorials, 12(3):422–438, 2010.
[56] K. Sankarasubramaniam and S. Subramanian. A Performance Study of Uplink Scheduling in WiMAX Network. In Proceedings of the International Conference on Recent Trends in Information Technology (ICRTIT), pages 377–382, 2012.
[57] F. S.Chu and K. C.Chen. Radio Resource Management of Self-organizing OFDMA Wireless Mesh Networks. Wireless Communications and Mobile Computing, 11(3):306–320, 2011.
[58] H. Shetiya and V. Sharma. Algorithms for Routing and Centralized Scheduling to Provide QoS in IEEE 802.16 Mesh Networks. In Proceedings of the ACM Workshop on Wireless Multimedia Networking and Performance Modeling (WMuNeP), pages 140–149, October 2005.
[59] H. Shetiya and V. Sharma. Algorithms for Routing and Centralized Scheduling in IEEE 802.16 Mesh Networks. In Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC), pages 147–152, April 2006.
[60] Y. B. Shimol, I. Kitroser, and Y. Dinitz. Two dimensional Mapping for Wireless OFDMA Systems. IEEE Transactions on Broadcasting, 52(3):388–396, September 2006.
[61] K. Sumathi and M. L. Valarmathi. Resource allocation in multiuser OFDM systems-A survey. In Proceedings of the 2012 3rd International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2012.
[62] A. Syed, S. A. Ahson, and M. Ilyas. WiMAX: Applications. CRC Press, 2012.
[63] T.H. Szymanski. Interference and Power Minimization in TDMA-OFDMA Infrastructure Wireless Mesh Networks. In Proceedings of International Conference on Systems and Networks Communications (ICSNC), pages 348–355, 2010.
[64] T.H. Szymanski. Provisioning Backhaul Traffic Flows in TDMA/OFDMA Infrastructure Wireless Mesh Networks with Near-perfect QoS. In Proceedings of IEEE Sarnoff Symposium, 2010.
[65] J. Tao, F. Liu, Z. Zeng, and Z. Lin. Throughput Enhancement in WiMAX Mesh Networks Using Concurrent Transmission. In Proceedings of International Conference on Wireless Communications, Networking and Mobile Computing (WCNM), volume 2, pages 871–874, September 2005.
[66] J. Vanderpypen and L. Schumacher. Treemap-based Burst Mapping Algorithm for Downlink Mobile WiMAX Systems. In Proceeding of the IEEE Vehicular Technology Conference (VTC), pages 1–5, September 2011.
[67] H. Viswanathan and S. Mukherjee. Throughput-range Tradeoff of Wireless Mesh Backhaul Networks. IEEE Journal on Selected Areas in Communications (JSAC),24(3):593–602, March 2006.
[68] V.Tralli, P. Henarejos, and P. Neira. A Low Complexity Scheduler for Multiuser MIMO-OFDMA Systems with Heterogeneous Traffic. In Proceedings of the International Conference on Information Networking (ICOIN), pages 251–256, 2011.
[69] N. Vuong, N. Agoulmine, E. Cherkaoui, , and L. Toni. Multicriteria Optimization of Access Selection to Improve the Quality of Experience in Heterogeneous Wireless Access Networks. IEEE Transactions on Vehicular Technology, 62(4):1785–1800, 2013.
[70] H. Wang and W.Jia. An Optimized Scheduling Scheme in OFDMA WiMAX Networks. International Journal of Communication Systems, 23(1):23–3
[71] H.-Y. Wei, S. Ganguly, R. Izmailov, and Z. J. Haas. Interference-aware IEEE 802.16 WiMAX Mesh Networks. In Proceedings of the IEEE Vehicular Technology Conference (VTC), volume 5, pages 3102–3106, May 2005.9, 2010.
[72] W. Wei, D. Xu, D. Qian, P. N. Ji, T. Wang, and C. Qiao. Demonstration of an Optical OFDMA Metro Ring Network with Dynamic Sub-carrier Allocation. In Proceedings of Conference on Optical Fiber Communication, Technical Digest Series, 2009.
[73] Q. Xiong, W. Jia, C. Wu, and G. Ye. Throughput Enhancement with Bidirectional Concurrent Transmission in IEEE 802.16 Mesh Networks. In Proceedings of International Conference on Communications and Networking in China (CHINACOM), pages 947–951, August 2007.
[74] E. Yaacoub and Z. Dawy. A Survey on Uplink resource Allocation in OFDMA Wireless Networks. IEEE Communications Surveys and Tutorials, 14(2):322–337, 2012.
[75] S. Yousefi, S. Bastani, M. Mazoochi, and A. Ghiamatyoun. Genetic Algorithm approach for QoS-based Tree Topology Construction in IEEE 802.16 Mesh Networks. Science China Information Sciences, 56(3):1–17, 2013.
[76] Y. Zhang and H.-H Chen. Mobile WiMAX: Toward Broadband Wireless Metropolitan Area Networks. Auerbach Publication, 2012.
[77] X. Zhen and Y. Wenzhong. Bandwidth-aware Routing for TDMA-based Mobile Ad Hoc Networks. In Proceedgings of the International Conference on Information Networking, pages 637–642, 2013.
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