隨著物聯網的蓬勃發展，未來機械通訊的裝置數量將會大增。在無線網路系統LTE 中，原先的設計是以服務手機用戶為考量，因而把大量的資源規劃給資料資源，僅有少量的資源提供給控制資源；然而在機械通訊中，僅需要少量的資料資源，若大量的機械裝置有連線需求會造成目前LTE 系統控制資源不足，而導致後續的連線無法順利完成。在這篇論文中，為了解決控制資源不足的問題並提高LTE的連線效能，我們提出了兩個不同的情境做分析，第一個為通道間的動態資源分配系統，先運算出裝置連線所需的資源量，再透過連線裝置數量的估計方法，來適當的分配控制資源與資料資源，能達到穩定的成功率下並使資源能夠有效分配，另一個為考慮機械通訊與人對人通訊共存情形下的賽局理論分析，透過拍賣競標資源的方式，也能達到同樣的效益。在這兩個方法中我們都透過模擬方式驗證理論，並和標準文件中的解決方案做比較，驗證它的可行性。

According to the estimation, Machine-to-Machine(M2M) devices in the Internet of Things(IoT) would be boosted in the near future. LTE system is originally designed for human to human(H2H) communications. The most of radio resource is allocated to data channels but rarely less to control channels. Comparing M2M traffic with H2H traffic, M2M devices only have lightweight uplink packet to report their data. When numerous devices access the network, there are huge amount of the controlling signals would be sent. The overhead of control packets would be too high for the system to maintain the service when massive M2M device access the network. To resolve the problem and improve the performance of LTE system, two scenarios are analyzed. One is a inter-channel dynamic resource allocation scheme designed for massive devices. First, we calculate the resource requirement for each device and estimate the traffic of random access attempts, then allocate data resource and control resource properly in pursuit of high success transmission probability. The other is a game theoretic analysis to a hybrid scenario. We evaluate the performance and find that our proposed scheme in both scenario has better performance in terms of success probability and resource efficiency.

Contents
口試委員會審定書
誌謝
摘要
Abstract
1 Introduction 1
1.1 Goals and challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2 Contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2 Related Work 5
2.1 RACH Congestion Control Method . . . . . . . . . . . . . . . . . . . . 5
2.2 PDCCH Control Resource Constraint . . . . . . . . . . . . . . . . . . . 6
3 System Architecture 8
4 Analysis of LTE system 12
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
4.2 Uplink Capacity in LTE system . . . . . . . . . . . . . . . . . . . . . . . 12
4.3 Downlink Capacity in LTE system . . . . . . . . . . . . . . . . . . . . . 17
4.4 The analysis of LTE system capacity . . . . . . . . . . . . . . . . . . . . 20
5 Inter-channel Dynamic Resource Allocation 21
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
5.2 Estimate traffic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
5.2.1 Estimation Error . . . . . . . . . . . . . . . . . . . . . . . . . . 24
5.3 Calculate and allocate control and data resource . . . . . . . . . . . . . . 26
5.3.1 Uplink Capacity in dynamic resource allocation . . . . . . . . . . 27
5.3.2 Downlink capacity in dynamic resource allocation . . . . . . . . 31
5.4 The analysis of proposed dynamic resource allocation capacity . . . . . . 33
5.5 Broadcast the result to UEs . . . . . . . . . . . . . . . . . . . . . . . . . 33
5.6 Dynamic random backoff . . . . . . . . . . . . . . . . . . . . . . . . . . 34
6 Simulation 38
7 Coexistence with H2H/M2M resource allocation:A Game Theoretic Approach 47
7.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
7.2 Game Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
7.3 Mechanism Design and Result . . . . . . . . . . . . . . . . . . . . . . . 51
7.4 the properties of proposed auction model . . . . . . . . . . . . . . . . . . 53
7.5 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
8 Conclusion 63
Bibliography 63
List of Figures
3.1 The basic call flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
4.1 Maximum preamble number . . . . . . . . . . . . . . . . . . . . . . . . 14
4.2 The resource of PUCCH channel . . . . . . . . . . . . . . . . . . . . . . 14
5.1 The flow chart of the proposed system model . . . . . . . . . . . . . . . 22
5.2 PUCCH DMRS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
5.3 PUSCH DMRS SRS . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
5.4 The illustration of the capacity of each channel . . . . . . . . . . . . . . 29
5.5 LTE resource grid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
5.6 Downlink calculator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
5.7 The Calculation of backoff window size . . . . . . . . . . . . . . . . . . 35
5.8 Maximum backoff times . . . . . . . . . . . . . . . . . . . . . . . . . . 37
6.1 The ratio of UEs finishing the RACH proceudre in 1 min . . . . . . . . . 39
6.2 The ratio of UEs successfully transmit a packet in 1 min . . . . . . . . . 40
6.3 The ratio of UE successfully transmit a packet given finishing the RACH
procedure in 1 min . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
6.4 Number of packets are received by eNB in 1 min . . . . . . . . . . . . . 42
6.5 Number of UEs failed in DL band . . . . . . . . . . . . . . . . . . . . . 43
6.6 Number of UEs failed in UL band . . . . . . . . . . . . . . . . . . . . . 44
6.7 Number of UEs failed in PHICH . . . . . . . . . . . . . . . . . . . . . . 45
6.8 Number of unused DL resource . . . . . . . . . . . . . . . . . . . . . . . 45
6.9 Number of unused UL resource . . . . . . . . . . . . . . . . . . . . . . . 46
6.10 Number of unused PHICH resource . . . . . . . . . . . . . . . . . . . . 46
7.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
7.2 An example of resource allocation . . . . . . . . . . . . . . . . . . . . . 52
7.3 Incentive compatible of winner . . . . . . . . . . . . . . . . . . . . . . . 56
7.4 Incentive compatible of loser . . . . . . . . . . . . . . . . . . . . . . . . 57
7.5 Individual rationality . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
7.6 Weakly budget balanced . . . . . . . . . . . . . . . . . . . . . . . . . . 59
7.7 Number of packets are received by eNB in 10s . . . . . . . . . . . . . . 61
7.8 unused resource in 10s . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
List of Tables
3.1 TR 37.868 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
4.1 NAS: Authentication Response . . . . . . . . . . . . . . . . . . . . . . . 16
4.2 NAS: Security Mode Complete . . . . . . . . . . . . . . . . . . . . . . . 16
4.3 Uplink data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
4.4 NAS: Security Mode Command . . . . . . . . . . . . . . . . . . . . . . 18
4.5 NAS: Authentication Request . . . . . . . . . . . . . . . . . . . . . . . . 19
4.6 Downlink data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
5.1 Uplink data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
5.2 Downlink data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
5.3 resource amount in DL . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Bibliography
[1] Cisco. Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2015-2020”, Feb. 2016. Feb. 2016.
[2] Nokia Siemens Networks. 2020: Beyond 4G Radio Evolution for the Gigabit Experience. 2011.
[3] Alex X. Liu Jeffrey Pang Jia Wang M. Zubair Shafiq, Lusheng Ji. A First Look at Cellular Machine-to-Machine Traffic - Large Scale Measurement and Characterization. ACM SIGMETRICS, pages 65–76, 2012.
[4] http : //www:sharetechnote:com/html/basiccallflowlte:html/:.
[5] 3GPP TS 36.868 V11.0.0. Study on RAN Improvements for Machinetype Communications. Sept. 2011.
[6] Yuan-Chi Pang ; Guan-Yu Lin ; Hung-Yu Wei. Evaluation of LTE access class barring mechanism for IoT. International Conference on Consumer Electronics, IEEE, pages 300–301, 2015.
[7] Yuan-Chi Pang ; Guan-Yu Lin ; Hung-Yu Wei. Context-aware Dynamic Resource Allocation for Cellular M2M Communications. Internet of Things Journal, IEEE, page 1, 2015.
[8] S. Duan, V. Shah-Mansouri, and V. W. S. Wong. Dynamic access class barring for m2m communications in lte networks. In 2013 IEEE Global Communications Conference (GLOBECOM), pages 4747–4752, Dec 2013.
[9] A. Amokrane, A. Ksentini, Y. Hadjadj-Aoul, and T. Taleb. Congestion control for machine type communications. In 2012 IEEE International Conference on Communications (ICC), pages 778–782, June 2012.
[10] V. W. S. Wong M. Tavana, V. Shah-Mansouri. Congestion Control for Bursty M2M Traffic in LTE Networks. Internation Conference on Communications(ICC), IEEE, pages 5815–5820, 2015.
[11] M. H. Fong R. Vannithamby U. Phuyal, A. T. Koc. Controlling Access Overload and Signaling Congestion in M2M Networks. Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), IEEE, pages 591–595, 2012.
[12] S. Lien, T. Liau, C. Kao, and K. Chen. Cooperative Access Class Barring for Machine-to-Machine Communications. Wireless Communications, IEEE Transactions on, pages 27–32, 2012.
[13] M. Hasan, E. Hossain, and D. Niyato. Random access for machine-to-machine communication in LTE-advanced networks: issues and approaches. IEEE Communications Magazine, pages 86–93, 2013.
[14] A. Laya, L. Alonso, and J. Alonso-Zarate. Is the random access channel of lte and lte-a suitable for m2m communications? a survey of alternatives. IEEE Communications Surveys Tutorials, pages 4–16, 2014.
[15] A. Lo, Y. Law, M. Jacobsson, and M. Kucharzak. Enhanced lte-advanced randomaccess mechanism for massive machine-to-machine (m2m) communications. In 27th World Wireless Research Forum (WWRF) Meeting, pages 1–5, 2011.
[16] M. Cheng, G. Lin, H. Wei, and A. Hsu. Overload control for Machine-Type-Communications in LTE-advanced system. IEEE Communication Magazine, pages 38–45, 2012.
[17] M. Cheng, G. Lin, H. Wei, and C. Hsu. Performance evaluation of radio access network overloading from machine type communications in LTE-A networks. pages 248–252, 2012.
[18] C. Wei, R. Cheng, and S. Tsao. Performance Analysis of Group Paging for Machinetype Communications in LTE Networks. IEEE Transactions on Vehicular Technology, pages 1–1, 2013.
[19] A. Larmo and R. Susitaival. Ran overload control for machine type communications in lte. IEEE Globecom Workshops, pages 1626–1631.
[20] P. ; Aalto S. ; Larmo Osti, P. ; Lassila. Analysis of PDCCH Performance for M2M Traffic in LTE. Transactions on Vehicular Technology, IEEE, pages 4357–4371, 2014.
[21] G. Lin, S. Chang, and H. Wei. Estimation and adaptation for bursty lte random access. IEEE Transactions on Vehicular Technology, pages 1–1, 2015.
[22] D.T. Wiriaatmadja and Kae W. C. Hybrid random access and data transmission protocol for machine-to-machine communications in cellular networks. IEEE Transactions on Wireless Communications, pages 33–46, 2015.
[23] 3GPP TS 36.321 V10.2.0. E-UTRA Medium Access Control (MAC) protocol specification. Jun. 2011.
[24] 3GPP TS 36.213 V10.2.0. E-UTRA Physical layer procedures. Jun. 2011.
[25] 3GPP TR 23.887 V12.0.0. Technical Specification Group Services and System Aspects; Study on Machine-Type Communications (MTC) and other mobile data application communications enhancements. Dec. 2013.
[26] 3GPP TR 37.869 V12.0.0. Study on Enhancements to Machine-Type Communications (MTC) and other Mobile Data Application; Radio Access Network (RAN) aspectss. Sept. 2013.
[27] 3GPP TS 24.301 V13.3.0. Non-Access-Stratum(NAS) Protocol for Evolved Packet System (EPS). Sept. 2015.