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此文档是毕业设计外文翻译成品( 含英文原文+中文翻译),无需调整复杂的格式!下载之后直接可用,方便快捷!本文价格不贵,也就几十块钱!一辈子也就一次的事!外文标题:A Resource Allocation Scheme for Device-to-Device Communication over Ultra-Dense 5G Cellular Networks外文作者:J Gu , HW Yoon , J Lee , SJ Bae , YC Min文献出处:Applied Mechanics & Materials , 2018, 713-715 :1208-1215(如觉得年份太老,可改为近2年,毕竟很多毕业生都这样做)英文2655单词,15098字符(字符就是印刷符),中文3509汉字。AbstractWith the advance of the wireless technologies and mobile devices, the number of mobile devices in cellular system will explosively grow. According to this trend, a base station will face a heavy traffic loading and even cannot provide services for a large amount of mobile devices. To deal with this issue, device-to-device (D2D) technology is a promising solution to increase spectrum efficiency by reusing radio resource blocks. In this paper, we study a resource allocation problem with the objective of maximizing system capacity over ultra-dense 5G cellular systems and consider a scenario that the number of D2D users is more than that of cellular users. This paper observes that radio resource blocks should be firstly allocated to D2D users under the ultra-dense scenario. Then, we propose resource allocation methods to solve this problem. Simulation results agree our observation and show that the proposed scheme can significantly improve the system capacity and spectrum efficiencyIndex TermsD2D, cellular networks, resource allocationI. INTRODUCTIONWith the advance of mobile devices, mobile data traffic will explosively grow every year. In other words, each base station requires to serve more users and suffers a problem that radio resources are not sufficient to provide services for ultra-dense users. Device-to- device (D2D) communications is one of the solutions to offload the traffic loading of a base station. A pair of D2D devices can reuse a frequency, used by another pair of D2D devices, to increase spectrum efficiency and system capacity when the two pairs of D2D devices do not interfere with each other. In an ultra-dense environment, how to allocate radio resource blocks is an important problem and significantly affects the spectrum efficiency and the system capacity. This paper studies a radio resource block allocation problem under D2D communications over ultra-dense 5G cellular systems.Recently, several researches have studied radio resource allocation problem for D2D communications and can be classified into two directions. The first one considers that the number of cellular users (CUEs) is more than the number of D2D users (DUEs). 1 proposed a resource allocation algorithm that relies on an area controller and can be used for uplink and downlink. 26 further considered mode selection that a base station can select cellular transmission mode or D2D mode for a user. After determining the mode for each user, thepapers propose resource allocation algorithms with different considerations to allocate radio resource for each user.However, the above works do not consider a scenario that thenumber of cellular users is less than the number of D2D users so that the radio resources cannot be efficiently reused for a large amount of D2D users. Specifically, above works restrict that radio resource blocks used by a pair of D2D user can only be reused by a pair of D2D users.Although 2, 3 do not have the restriction, the time complexity of the proposed algorithms is extremely high and the proposed algorithm cannot be used in an ultra-dense environment.The second direction considers that the number of cellular users is less than the number of D2D users. 7 considered that users in a region cannot use the same radio resource block to avoid interference and proposed a coloring method to allocate radio blocks for each user. The related works firstly allocate radio resource blocks for cellular users and then considers D2D users to reuse the radio resource blocks. However, we observes that if we firstly allocate radio resource blocks for cellular users, a large amount of D2D users cannot efficiently reuse the same radio resource blocks in an ultra-dense environment. This is because the transmit power of cellular users is generally larger than that of D2D users so that a large amount of D2D user will be interfered and cannot reuse the same radio resource blocks.In this paper, we study a radio resource block allocation problem in an ultra-dense 5G cellular system and consider that the number of D2D users is more than the number of cellular users. The objective is to maximize the system capacity. Then, we propose a coloring algorithm to allocate radio resource blocks to each D2D and cellular user. The proposed algorithm will firstly allocate radio resource blocks to D2D users and then to cellular users such that each radio resource block can be efficiently reused. Simulation results show that the proposed scheme significantly improves the system throughput and spectrum efficiency. The remainder of this paper is organized as follows. SectionII describes system model. In Section III, we develop algorithms to solve the problem. Simulation results are presented in Section IV. Finally, Section V conclusions this paper.II. SYSTEM MODELIn this paper, we consider that there is a base station to serve a set C of cellular users (CUEs) and a set D of D2D users (DUEs). DT is used to represent the set of DUEs which transmits data and DUE d DT means that the DUE requires to transmit data. DR is used to represent the set of DUEs which receives data and dDR means that the DUE has to receive data. The base station has to determine that each user should operate on cellular mode or D2D mode. Then, the base station should allocate radio resource blocks (RBs) to each CUE and each pair of DUEs. The set of resource blocks allocated to CUEs and DUEs is respectively represented as RC and RD. When rc RC,it means that RB r is allocated to CUE c.rd RD means that RB r is allocated to DUE d. rc = rd means thatRB r is simultaneously used by CUE c and DUE d. When RB r is allocated to CUE c, the signal to interference ratio (SINR) for CUE c can be expressed aswhere PC is the transmit power of a CUE and PD is the transmit power of a DUE. GB,c is the channel gain between the base station and CUE c and Gd,d is the channel gain between DUE d and DUE d . N0 is the additive white Gaussian noise. The total data rate for all CUEs can be expressed aswhere W is the bandwidth of a RB. When RB r is allocated to DUE d, the SINR for DUE d can be expressed asThe total data rate for all DUEs isObjective: Our objective is to determine that each user should operate on cellular or D2D mode and decide that each RB should be allocated to which users such that the total system capacity can be maximized. The objective function is expressed asIII. ALGORITHM DESCRIPTIONIn a metropolitan environment with high density characteristics, our scheme is different from the traditional communication model and uses a large number of D2D communication mode to replace the original cellular communication mode.Thus, our scheme not only effectively reduces the load on the base station (BS). The device also reduces power consumption and increases data transmission rate. In addition, our scheme is no restrictions on the sharing of resources and chooses the best resource allocation depending on the situation to increase the flexibility of using resources. As a result, the overall spectrum utilization can also be effectively improved.To allocate the resource, if the CUE first selects the RB, it affectsthe surrounding DUEs, reduces the choice of resources, and even causes no resources to be chosen by DUEs. Therefore, the DUE has higher priority to obtain the RB so that it reduces the CUE selection resources to increase the spectrum utilization. Our proposed scheme is divided into two stages. In the first stage, it is the mode allocation algorithm. In the second stage, it is the resource selection algorithm. The proposed scheme is only for new devices so that we effectively reduce the number of processing users to shorten the calculation time.Algorithm 1 is the mode allocation algorithm. When a new deviceinto the service area of the BS to send a service request, the BS is in accordance with the use of resources at the time and refers to the surrounding devices for the new device. Thus, we decide what kinds of communication modes are used for a new device.If neighbor devices have the needed information for a new device, a new device directly uses the D2D mode to obtain the information from the neighbor device. Contrarily, if neighbor devices do not have the needed information, the system determines the mode according to the resource usage. In other words, if the resource of the system does not be used by otherCUEs, the new device uses cellular mode.Otherwise, the system rejects the request of the new device.Our scheme allows the device to use the D2D mode to receive data, shortens the transmission time, and improves the overall system performance.Resource selection algorithm is also divided into two stages. In thefirst stage, we establish ”neighbor graph”. Neighbor graph is defined as the relationship among devices. In the neighbor graph, a node represents a device, and an edge connects two nodes which use the same resource block (RB) to cause excessive interference each other. The color represents the RB, and two nodes with the edge connected do not use the same color. The second stage is the selection of resources. It uses previously established neighbor graph to proceed graph coloring to finish the resource selection of all the devices.To establish the neighbor graph, how to select the radius of the node in the neighbor graph is an important issue. If the radius is too largeto cause a large number of devices in the cover area, the system cannot complete the resource selection of all the devices; on the contrary, if the radius is too small to cause the use of the same RB for devices causing too much interference. Therefore, in this paper, we calculates the best radius of the neighbor graph considering two basic angles of the graph coloring and SINR limitation. First, according to the graph coloring, the number of colors must be larger than the number of nodes. In other words, the number of RBs is larger than or equals the number of devices. Thus, we limit the upper bound of the radius l in the neighbor graph, and only the number of internal devices is smaller than the total number of RBs.In order to find the best l for establishing the neighbor graph, weuse the limitation of the graph coloring as the upper bound of the radius l and calculate the minimum acceptance value of SINR as lower bound. Hence, we use l to determine whether devices are the neighbor or not. When the distance between two devices are less than l, we set two devices as neighbors. All nodes establish their neighbor graph in turn and calculate the number of neighbors. When the number of neighbors exceeds the upper bound of l, the neighbor graph must be reestablished. The algorithm of the neighbor graph shows in Algorithm 2.Next, based on the graph coloring, the BS can use the established neighbor graph, and adjacent devices cannot use the same color to select the RB. When we allocate the RB, the DUE first selects resources and then CUE selects resources. Initially, each device removes RBs which are used by neighbor devices from the resource candidate list, and the CUE deletes RBs that have been used by other CUEs. After sorting, each device calculates the SINR for each candidate RBin order to select the suitable RB. In the sorting process, when two RBs provide the same SINR, we consider the current situation of the RB. In addition to achieving the highest system performance, we also improve the spectrum utilization. Thus, we use the number of users to select the RB, which is used by more devices. Users using the same RB can maintain above the acceptable SINR value as much as possible so that more users choose the same piece of RB to enhance the spectrum usage. Algorithm 3 shows the details of resource selection algorithm.IV. SIMULATION SETUPWe developed a simulation model to evaluate the performance of our proposed algorithm, denoted as mode allocation and resource selection (MARS) algorithm. The proposed algorithm is compared with an algorithm proposed in 7. The baseline is denoted as graph- coloring resource allocation (GOAL). The simulation settings are listed in Table I.V. SIMULATION RESULTSFig. 1 shows the impacts of the number of D2D pairs on the total system capacity. When the number of D2D pairs increases, the total system capacity increases. The result is expected because more users can contribute more data rate when RBs can be efficiently reused by D2D users. Our proposed algorithm can increase more system capacity than the baseline when there are more D2D users. This is because our proposed algorithm considers ultra-dense environment and firstly allocates RBs for D2D users such that the RBs can be more efficiently reused.VI CONCLUSIONThis paper studies the resource allocation problem over ultra-dense5G cellular systems and considers that the number of D2D users is more than the number of cellular users. The objective is to maximizethe system capacity. This paper observes that RBs should be firstly allocated to D2D users when the number of D2D users is more thanthat of cellular users such that the RBs can be more efficiently reused. To solve the target problem, this paper proposes a mode selection todetermine that each user should operate on cellular mode or D2D mode. To allocate RBs for each user, this paper proposes a neighborgraph establishment and a resource selection algorithm. The simulation results confirm our motivation and shows that ourproposed algorithm can significantly increase the system capacity.REFERENCES1 F. Malandrino, Z. Limani, C. Casetti, and C. F. Chiasserini,“Interference-Aware Downlink and Uplink Resource Allocation inHetNets With D2D Support,” IEEE Transactions on WirelessCommunications, vol. 14, no. 5, pp. 27292741, May 2015.2 L. Lei, Y. Kuang, N. Cheng, X. S. Shen, Z. Zhong, and C. Lin,“Delay-Optimal Dynamic Mode Selection and Resource Allocation inDevice-to-Device CommunicationsPart I: Optimal Policy,” IEEETransactions on Vehicular Technology, vol. 65, no. 5, pp. 34743490,May 2016.3 , “Delay-Optimal Dynamic Mode Selection and ResourceAllocation in Device-to-Device CommunicationsPart II: PracticalAlgorithm,” IEEE Transactions on Vehicular Technology, vol. 65, no.5, pp. 34913505, May 2016.4 K. Zhu and E. Hossain, “Joint Mode Selection and SpectrumPartitioning for Device-to-Device Communication: A DynamicStackelberg Game,” IEEE Transactions on Wireless Communications,vol. 14, no. 3, pp. 14061420, March 2015.5 J. Zheng, R. Chen, and Y. Zhang, “Dynamic Resource Allocationbased on Service Time Prediction for Device-to-DeviceCommunication Underlaying Cellular Networks,” IETCommunications, vol. 9, no. 3, pp. 350358, Feb. 2015.6 H. Zhang, L. Song, and Z. Han, “Radio Resource Allocation forDevice-to-Device Underlay Communication Using HypergraphTheory,” IEEE Transactions on Wireless Communications, vol. 15,no. 7, pp. 48524861, March 2016.7 X. Cai, J. Zheng, and Y. Zhang, “A Graph-Coloring basedResource Allocation Algorithm for D2D Communication in CellularNetworks,” IEEE International Conference on Communications(ICC), pp. 54295434, September 2015.超密集设备对设备通信的资源分配方案-5G蜂窝网络摘要随着无线技术和移动设备的进步,蜂窝系统中的移动设备数量将爆炸式增长。根据这一趋势,基站将面临沉重的流量负载,甚至无法为大量移动设备提供服务。为了解决这个问题,设备到设备(D2D)技术是通过重新使用无线资源块来提高频谱效率的有希望的解决方案。在本文中,我们研究了一个资源分配问题,目标是在超密集5G蜂窝系统上最大化系统容量,并考虑D2D用户数量多于蜂窝用户的情况。本文观察到无线资源块应该首先分配给超密集场景下的D2D用户。然后,我们提出资源分配方法来解决这个问题。仿真结果符合我们的观察,并表明该方案可以显着提高系统容量和频谱效率索引术语 - D2D,蜂窝网络,资源分配一,导言随着移动设备的进步,移动数据流量将每年爆炸式增长。换句话说,每个基站需要为更多的用户提供服务,并且存在无线资源不足以为超密用户提供服务的问题。设备到设备(D2D)通信是卸载基站业务负载的解决方案之一。一对D2D设备可以重用另一对D2D设备使用的频率,以在两对D2D设备互不干扰时增加频谱效率和系统容量。在一个超密集的环境中,如何分配无线资源块是一个重要的问题,并且显着影响频谱效率和系统容量。本文研究了超密集5G蜂窝系统中D2D通信下的无线资源块分配问题。最近,一些研究已经研究了用于D2D通信的无线电资源分配问题,并且可以分为两个方向。第一个认为蜂窝用户(CUE)的数量多于D2D用户(DUE)的数量。 1提出了一种依赖于区域控制器的资源分配算法,可用于上行链路和下行链路。 2-6进一步考虑了基站可以为用户选择蜂窝传输模式或D2D模式的模式选择。确定每个用户的模式后,论文提出了具有不同考虑因素的资源分配算法,为每个用户分配无线资源。不过,上述作品并不考虑这种情况蜂窝用户的数量少于D2D用户的数量,无法为大量的D2D用户高效地重用无线资源。具体来说,上述工作限制了一对D2D用户使用的无线资源块只能由一对D2D用户重新使用。尽管2,3没有限制,但所提出的算法的时间复杂度非常高,并且所提出的算法不能用于超密集环境中。第二个方向认为蜂窝用户数量少于D2D用户数量。 7认为,一个地区的用户不能使用相同的无线资源块来避免干扰,并提出了一种着色方法来为每个用户分配无线块。相关工作首先为蜂窝用户分配无线资源块,然后考虑D2D用户重用无线资源块。然而,我们观察到,如果我们首先为蜂窝用户分配无线资源块,则大量的D2D用户不能在超密集环境中有效地重复使用相同的无线资源块。这是因为蜂窝用户的发射功率一般大于D2D用户的发射功率,使得大量的D2D用户会受到干扰,无法重用相同的无线资源块。在本文中,我们研究了超密集5G蜂窝系统中的无线资源块分配问题,并认为D2D用户的数量超过了蜂窝用户的数量。 目标是最大化系统容量。 然后,我们提出了一种着色算法来为每个D2D和蜂窝用户分配无线资源块。 该算法首先将无线资源块分配给D2D用户,然后分配给蜂窝用户,使得每个无线资源块可以被有效地重用。 仿真结果表明,该方案显着提高了系统吞吐量和频谱效率。本文的其余部分安排如下。 部分II描述了系统模型。 在第三节中,我们开发算法来解决这个问题。 第四节给出了仿真结果。 最后,本文第五节结论。I。 系统模型在本文中,我们认为有一个基站服务C组蜂窝用户(CUE)和D组D2D用户(DUE)。 DT用于表示传输数据的DUE的集合,DUE表示DUE表示DUE要求传输数据。 DR用于表示接收数据的DUE集合,dDR表示DUE必须接收数据。 基站必须确定每个用户应该在蜂窝模式或D2D模式下工作。 然后,基站应该为每个CUE和每对DUE分配无线资源块(RB)。 分配给CUE和DUE的资源块集合分别表示为RC和RD。 当rc RC时,表示RB r被分配给CUE c。rd RD表示RB r分配给DUE d。 rc = rd表示CUE c和DUE d同时使用RB r。 当RB r被分配给CUE c时,CUE c的信号干扰比(SINR)可以表示为PC是CUE的发射功率,PD是DUE的发射功率。 GB,c是基站和CUE c和Gd之间的信道增益,d是DUE d和DUE d之间的信道增益。 N0是加性高斯白噪声。 所有CUE的总数据速率可以表示为其中W是RB的带宽。 当RB r被分配给DUE d时,DUE d的SINR可以表示为所有DUE的总数据速率为目标:我们的目标是确定每个用户应该在蜂窝或D2D模式下运行,并决定每个RB应该分配给哪些用户,以使系统总容量最大化。 目标函数表
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