隨著無線寬頻網路與行動通訊技術的蓬勃發展，各式各樣的行動裝置大量普及，促使消費者大量下載行動裝置上的載具與應用服務。多數消費者已習慣透過行動裝置處理各種生活層面的大小事，然而，核心網路漸漸無法負荷大量的網路資料與控制訊號，導致經常性的網路壅塞。因此，使用不透過基地台的裝置傳輸方式，逐漸受到重視。一般而言，裝置對裝置能夠增加頻譜的利用、整體的產出量以及改善消耗功率，但是在頻譜資源有限的情況下，頻寬的利用與分配顯得更加重要。
D2D通訊在支撐式下中央集權式的資源分配時，由於共用資源區塊的關係，當分配資源區塊給蜂巢式網路用戶與D2D使用者，會產生訊號干擾問題。因此，本論文著重於，多個D2D在同一個時間點互相競爭資源分配時，透過新的排程方式，以確保資源能夠適當且公平的分配。
為了解決上述問題，本論文提出以『匈牙利演算法』聯合『比例公平演算法』技術，以提供資源區塊的分享。匈牙利演算法會選擇最大的權重匹配，能夠提高系統的產出量，比例公平演算法在D2D傳輸資料率下降時，則可以拉高權重值，使傳輸速率低的D2D，有更大的機會去搶奪資源區塊。因此，在D2D共享CUE的資源區塊情況下，相對於其他演算法，綜合上述兩種演算法，更能兼顧D2D公平性且不犧牲整體產出量。

With the rapid development of wireless broadband networks and mobile communication technologies, a wide range of mobile devices have been popularized. In recent years, because of the increasing density of mobile devices, diversified vehicles and application services have made users become accustomed to using mobile devices to handle life, communication, entertainment and other aspects of life.
However, the data signal and control signals must be transmitted through the core network, which will cause the congestion of the core network.
Therefore, device to device (D2D) can transmit signals to each other over a direct link using the cellular resources instead of through a base station base station has been paid more and more attention gradually.
In general, device-to-device increases spectrum utilization, overall throughput, and power consumption. However, due to the limited spectrum available, bandwidth utilization and distribution are more important.
When D2D communication under the underlay mode resource allocation, because of the relationship between reusing the resource block, the allocation of resource blocks to cellular network users and D2D users, there will be signal interference problems. Therefore, this thesis focuses on how multiple D2Ds schedule when they compete with each other at the same time to ensure that the resources are properly and fairly allocated.
In order to solve the above problems, this thesis proposes to share the resource blocks by combining the Hungarian algorithm with the proportional fair algorithm. The Hungarian algorithm will choose the maximum weight matching, which can increase the system throughput. Proportional fair algorithm will pulled high the D2D weight when the D2D data rate drops. Therefore, the D2D with low transmission rate has a greater chance to grab the resource block. By combining the advantages of the two algorithms, our proposed algorithm compared to others can balance the D2D fairness without sacrificing overall throughput.

[1]Stefania Sesia, Issam Toufik, and Matthew Baker, "LTE - The UMTS Long Term Evolution: From Theory to Practice," John Wiley & Sons, 2009.
[2]LTE-Advanced Pro，進入 5G 市場的前哨站, https://benchlife.info/lte-advanced-pro-before-entry-5g-market-01252016/
[3]SC-FDMA, http://www.twwiki.com/wiki/SC-FDMA
[4]Difference between SC-FDMA and OFDMA, http://www.rfwireless-world.com/Articles/difference-between-SC-FDMA-and-OFDMA.html
[5]紓解行動網路流量LTE-TDD/FDD融合組網蔚成風, http://www.2cm.com.tw/technologyshow_content.asp?sn=1407290011
[6]LTE TDD, http://niviuk.free.fr/lte_tdd.php
[7]D2D通訊技術精進，近端服務應用加速普及, http://www.2cm.com.tw/technologyshow_content.asp?sn=1409230003
[8]Y. Cao, T. Jiang, C. Wang, "Cooperative device-to-device communications in cellular networks," IEEE Wireless Communications, vol. 22, no. 3, 2015, pp. 124-129
[9]C. Xu, "Efficiency resource allocation for device-to-device underlay communication systems: A reverse iterative combinatorial auction based approach," IEEE J. Sel. Areas Commun., vol. 31, no. 9, 2013, pp. 348-358
[10]R. Zhang, X. Cheng, L. Yang and B. Jiao, "Interference graph-based resource allocation (InGRA) for D2D communications underlaying cellular networks," IEEE Trans. Veh. Technol., vol. 64, no. 8, 2015, pp. 3844-3850

[11]Xiaohang Chen, Li Chen, Mengxian Zeng, Xin Zhang, and Dacheng Yang, "Downlink resource allocation for device-to-device communication underlaying cellular networks," Personal Indoor and Mobile Radio Communications (PIMRC), 2012 IEEE 23rd International Symposium, Sept. 9-12, 2012, pp. 232 -237
[12]Phond Phunchongharn, Ekram Hossain, Dong In Kim, "Resource allocation for device-to-device communications underlaying LTE-advanced networks," IEEE Wireless Commun., vol. 20, no. 4, Aug. 2013, pp. 91-100
[13]W. Zhou et al., "An Interference Coordination Mechanism Based on Resource Allocation for Network Controlled Device-to-Device Communication," Proc. IEEE/CICICCC, Xi’an, China, Aug. 12-14, 2013
[14]M. Zulhasnine, C. Huang, and A. Srinivasan, "Efficient Resource Allocation for Device-to-Device Communication Underlaying LTE Network," Proc. IEEE WiMob, Niagara Falls, Canada, Oct. 11-13, 2010, pp. 368-75
[15]F. Wang, L. Song, Z. Han, Q. Zhao, and X. Wang, "Joint scheduling and resource allocation for device-to-device underlay communication," In 2013 IEEE Wireless Communications and Networking Conference (WCNC), April 2013, pp. 134-139
[16]H. Sun, "Resource Allocation for Maximizing the Device-to-Device Communications Underlaying LTE-Advanced Networks," Proc. IEEE ICCC Wksps., Aug. 12-14, 2013, pp. 60-64
[17]Yuanye Wang, Klaus I. Pedersen, Troels B. Sorensen, Preben E. Mogensen, "Utility Maximization in LTE-Advanced System with Carrier Aggregation," In Vehicular Technology Conference (VTC Spring), 2011 IEEE, May 2011, pp. 1-5
[18]匈牙利算法, https://zh.wikipedia.org/wiki/匈牙利算法
[19]Burkard R E, Çela E. Handbook of Combinatorial Optimization[M]. Springer US, 1999:75-149.
[20]Thong Huynh, Tomoyuki Onuma, Kaori Kuroda, Mikio Hasegawa, Won-joo Hwang, "Joint Downlink and Uplink Interference Management for Device to Device Communication Underlaying Cellular Networks," Published in: IEEE Access ( Volume: 4 )
[21]Wei Zhou, Xiaodong Sun, Chuan Ma, Jianting Yue, Hui Yu, Hanwen Luo, "An Interference Coordination Mechanism Based on Resource Allocation for Network Controlled Device-to-Device Communication," Proc. IEEE/CIC ICCC, Xi’an, China, Aug. 12-14, 2013, pp. 109-114