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1、Five Disruptive Technology Directions for 5GABSTRACT: New research directions will lead to fundamental changes in the design of future 5th generation (5G) cellular networks. This paper describes five technologies that could lead to both architectural and component disruptive design changes: device-c

2、entric architectures, millimeter Wave, Massive-MIMO, smarter devices, and native support to machine-2-machine. The key ideas for each technology are described, along with their potential impact on 5G and the research challenges that remain.I.INTRODUCTION:5G is coming. What technologies will define i

3、t? Will 5G be just an evolution of 4G, or will emerging technologies cause a disruption requiring a wholesale rethinking of entrenched cellular principles? This paper focuses on potential disruptive technologies and their implications for 5G. We classify the impact of new technologies, leveraging th

4、e Henderson-Clark model 1, as follows:1 .Minor changes at both the node and the architectural level, e.g., the introduction of codebooks and signaling support for a higher number of antennas. We refer to these as evolutions in the design.2 .Disruptive changes in the design of a class of network node

5、s, e.g., the introduction of a new waveform. We refer to these as component changes.3 .Disruptive changes in the system architecture, e.g., the introduction of new types of nodes or new functions in existing ones. We refer to these as architectural changes.4 .Disruptive changes that have an impact a

6、t both the node and the architecture levels. We refer to these as radical changes.We focus on disruptive (component, architectural or radical) technologies, driven by our belief that the extremely higher aggregate data rates and the much lower latencies required by 5G cannot be achieved with a mere

7、evolution of the status quo. We believe that the following five potentially disruptive technologies could lead to both architectural and component design changes, as classified in Figure 1.1 .Device-centric architectures.The base-station-centric architecture of cellular systems may change in 5G. It

8、may be time to reconsider the concepts of uplink and downlink, as well as control and data channels, to better route information flows with different priorities and purposes towards different sets of nodes within the network. We present device-centric architectures in Section IL2 .Millimeter Wave (m

9、mWave).While spectrum has become scarce at microwave frequencies, it is plentiful in the mmWave realm. Such a spectrum el Dorado5 has led to a mmWave gold rush in which researchers with diverse backgrounds are studying different aspects of discussed here is having a D2D dimension natively supported

10、in 5G.Average5-ththroughputpercentileFigure 5. Throughput gains obtained by incorporating the cfleets of nonlinear, intra and inter-ciustcr mtcrfcrencc-awarencss into devices, with N = 1, 2 and 4 antennas. Results are given in terms of gain (%) w.r.t. the single-base smgle-antcnna baseline. More det

11、ails can be found m 16.V.2 Local CachingThe current paradigm of cloud computing is the result of a progressive shift in the balance between data storage and data transfer: information is stored and processed wherever it is most convenient and inexpensive because the marginal cost of transferring it

12、has become negligible, at least on wireline networks 2. For wireless devices though, this cost is not always negligible. The understanding that mobile users are subject to sporadic abundance9 of connectivity amidst stretches of deprivation9 is hardly new, and the natural idea of opportunistically le

13、veraging the former to alleviate the latter has been entertained since the 1990s 3. However, this idea of caching massive amounts of data at the edge of the wireline network, right before the wireless hop, only applies to delay-tolerant traffic and thus it made little sense in voice-centric systems.

14、 Caching might finally make sense now, in data-centric systems 4.Thinking ahead, it is easy to envision mobile devices with truly vast amounts of memory. Under this assumption, and given that a substantial share of the data that circulates wirelessly corresponds to the most popular audio/video/socia

15、l content that is in vogue at a given time, it is clearly inefficient to transmit such content via unicast and yet it is frustratingly impossible to resort to multicast because the demand is asynchronous. We hence see local caching as an important alternative, both at the radio access network edge (

16、eg, at small cells) and at the mobile devices, also thanks to enablers such as mmWave and D2D.V.3 Advanced Interference RejectionIn addition to D2D capabilities and massive volumes of memory, future mobile devices may also have varying form factors. In some instances, the devices might accommodate s

17、everal antennas with the consequent opportunity for active interference rejection therein, along with beamforming and spatial multiplexing. A joint design of transmitter and receiver processing, and proper control and pilot signals, are critical to allow advanced interference rejection. As an exampl

18、e, in Fig. 5 we show the gains obtained by incorporating the effects of nonlinear, intra and inter-cluster interference awareness into devices with 1, 2 and 4 antennas.While this section has been mainly focused on analyzing the implications of smarter devices at a component level, in Section II we d

19、iscussed the impact at the radio access network architecture level. We regard smarter devices as having all the characteristic of a disruptive technology (cf. Section I) for 5G, and therefore we encourage researchers to further explore this direction.VLNATIVE SUPPORT FOR M2M COMMUNICATIONWireless co

20、mmunication is becoming a commodity, just like electricity or water 13. This commoditization, in turn, is giving rise to a large class of emerging services with new types of requirements. We point to a few representative such requirements, each exemplified by a typical service:1 .A massive number of

21、 connected devices. Whereas current systems typically operate with, at most, a few hundred devices per base station, some M2M services might require over 104 connected devices. Examples include metering, sensors, smart grid components, and other enablers of services targeting wide area coverage.2 .V

22、ery high link reliability. Systems geared at critical control, safety, or production, have been dominated by wireline connectivity largely because wireless links did not offer the same degree of confidence. As these systems transition from wireline to wireless, it becomes necessary for the wireless

23、link to be reliably operational virtually all the time.3 .Low latency and real-time operation. This can be an even more stringent requirement than the ones above, as it demands that data be transferred reliably within a given time interval. A typical example is Vehicle-to-X connectivity, whereby tra

24、ffic safety can be improved through the timely delivery of critical messages (eg, alert and control).Fig. 5 provides a perspective on the M2M requirements by plotting the data rate vs. the device population size. This cartoon illustrates where systems currently stand and how the research efforts are

25、 expanding them. The area RI reflects the operating range of today9s systems, outlining the fact that the device data rate decreases as its population increases. In turn, R2 is the region that reflects current research aimed at improving the spectral efficiency. Finally, R5 indicates the region wher

26、e operation is not feasible due to fundamental physical and information-theoretical limits.data, rateFigure 6. Operating regions in terms of data rate vs. size of the population.Regions R3 and R4 correspond to the emerging services discussed in this section:R3 refers to massive M2M communication whe

27、re each connected machine or sensor transmits small data blocks sporadically. Current systems are not designed to simultaneously serve the aggregated traffic accrued from a large number of such devices. For instance, a current system could easily serve 5 devices at 2 Mbps each, but not 10000 devices

28、 each requiring 1 Kbps. R4 demarks the operation of systems that require high reliability and/or low latency, but with a relatively low average rate per device. The complete description of this region requires additional dimensions related to reliability and latency.There are services that pose simu

29、ltaneously more than one of the above requirements, but the common point is that the data size of each individual transmission is small, going down to several bytes. This profoundly changes the communication paradigm for the following reasons:Existing coding methods that rely on long codewords are n

30、ot applicable to very short data blocks. Short data blocks also exacerbate the inefficiencies associated with control and channel estimation overheads. Currently, the control plane is robust but suboptimal as it represents only a modest fraction of the payload data; the most sophisticated signal pro

31、cessing is reserved for payload data transmission. An optimized design should aim at a much tighter coupling between the data and control planes.As mentioned in Section II, the architecture needs a major redesign, looking at new types of nodes. At a system level, the frame-based approaches that are

32、at the heart of 4G need rethinking in order to meet the requirements for latency and flexible allocation of resources to a massive number of devices. From the discussion above, and from the related architectural consideration in Section II, and referring one last time to the Henderson-Clark model, w

33、e conclude that a native support of M2M in 5G requires radical changes at both the node and the architecture level. Major research work remains to be done to come up with concrete and interworking solutions enabling M2M-inside 5G systems.VILCONCLUSIONThis paper has discussed five disruptive research

34、 directions that could lead to fundamental changes in the design of cellular networks. We have focused on technologies that could lead to both architectural and component design changes: device-centric architectures, mmWave, massive-MIMO, smarter devices, and native support to M2M. It is likely that

35、 a suite of these solutions will form the basis of 5G.REFERENCES1 A. Afuah, Innovation Management: Strategies, Implementation and Profits, Oxford University Press, 2003.2 J. Zander and P. Mahonen, Riding the data tsunami in the cloud: myths and challenges in future wireless accessIEEE Comm. Magazine

36、, Vol. 51, No. 3, pp. 145-151, Mar. 2013.3 D. Goodman, J. Borras, N. Mandayam, R. D. Yates, Infestations: A new system model fbr data and messaging services/9 in Proc. IEEE Veh. Techn. Conf. (VTC), vol. 2, pp. 969-973, Rome, Italy, May 1997.4 N. Golrezaei, A. F. Molisch, A. G. Dimakis and G. Caire,

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38、ebbour, T. Nakamura and H. Ishii, “Future steps of LTE-A: evolution towards integration of local area and wide area systems/5 IEEE Wireless Communications, Vol. 20, No. 1, pp.12-18, Feb. 2013.7 “C-RAN: The road towards green RAN J China Mobile Res. Inst., Beijing, China, White P叩er, ver. 2.5, Oct. 2

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41、IEEE Access, vol. l9pp. 335349, 2013.12 R. W. Heath Jr., “What is the Role of MIMO in Future Cellular Networks: Massive? Coordinated? mmWavc?” ICC Workshop Plenary: Beyond LTE-A, Budapest,Hungary.Slidesavailableat: ath.pdf13 Mark Weiser, “The Computer fbr the 21st Century, Scientific American, Sept.

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43、3.5G的五个颠覆性技术方向摘要：新的研究方向将带来未来的第五代（5G）蜂窝网络的设计发生根本性变化。 本文介绍了五种可能带来体系架构和构件颠覆性设计变化的技术：以设备为中心 的体系结构、毫米波、大规模天线技术、更智能的设备以及机器对机器通讯的本 地支持。本文描述了每种技术的关键构想以及它们对5G的潜在影响和仍然存在 的研究挑战。一，弓I言：5G,技术即将到来。用什么技术来定义它？ 5G仅仅是4G的演进，还是新兴技术 会引起颠覆性变化，而这需要彻底重新思考根深蒂固的蜂窝原则？本文重点关注 其潜在的颠覆性技术及其对5G的影响。我们利用亨德森-克拉克模型1对新技 术的影响进行分类，如下所示：1,在

44、节点和架构级别上的微小变化，例如引入密码本和对更多天线的信令支持, 我们将这些称为设计中的演变。2, 一类网络节点设计的颠覆性变化，例如新波形的引入。我们将这些称为组件 变化。3,系统架构的颠覆性变化，例如在现有节点中引入新类型的节点或新功能。我 们将这些称为体系架构变化。4,对节点和体系架构都有影响的颠覆性变化。我们称这些为根本性的变化。我们专注于颠覆性（组件、架构或基础技术）技术，这是因为我们相信，仅凭现 有的发展就无法实现5G所要求的极高的总数据速率和更低的延迟。我们认为， 名下五种潜在的颠覆性技术可能会带来体系架构和组件设计的变化，如图1所 示O1 .以设备为中心的架构蜂窝系统以基站为

45、中心的架构可能会在5G中发生变化。现在应该重新考虑上行 链路和下行链路以及控制和数据信道的概念，以更好地将具有不同优先级和目的 的信息流路分布到网络中的不同节点。我们将在第二部分介绍以设备为中心的体 系架构。2 .毫米波（mmWave）。尽管频谱在微波频率下已经变得很稀缺，但在毫米波领域中却很丰富。这种“ el Dorado”光谱带来了 “毫米波热”，其中背景不同的研究人员正在研究毫米波传 输的不同方面。尽管尚未完全了解，但毫米波技术已针对短距离服务（IEEE802. Had）进行了标准化，并已部署到小型应用（如小蜂窝回程）中。在第三部 分中，我们讨论了毫米波在5G中更广泛应用的潜力。3 .大

46、规模天线技术Massive-MIMOl建议利用大量天线在每个时频资源上多路复用多个设备的消息， 将辐射能量集中在预期方向上，同时最大程度地减小小区间和小区间干扰。大规 模MIMO可能需要进行重大的架构更改，尤其是在宏基站的设计中，并且还可能 导致新的部署类型。我们将在第四部分讨论大规模MIMO。4 .更智能的设备2G-3G-4G蜂窝网络是在对基础架构进行完全控制的设计前提下构建的。我们认 为5G系统应放弃此设计假设，并在协议栈的不同层中在设备端利用智能，例如 通过允许设备到设备（D2D）连接或在移动端利用智能缓存。尽管此设计原理主 要要求在节点级别进行更改（组件更改）,但在体系结构级别上也具有

47、含义。我 们在第五节中主张使用更智能的设备。5,机器对机器（M2M）通讯的本地支持5G中M2M通信的native2包含满足与不同类别的低数据速率服务相关的三个根 本不同的要求：支持大量低速率设备，几乎在所有情况下都维持最小数据速率, 以及-低延迟数据传输。要满足5G的这些要求，就需要在组件和架构级别上都采 用新的方法和思想，这就是第六节的重点。COMPONENT (node) disrupt.Node-centric networksNative support of M2M servicesQLms.p 山 anlo山1_工。工4Massive-MIMOS ma rter-de vicesm

48、m WaveFigure 1. The five disruptive directions for 5G considered in this paper, classified according to theHenderson-Clark model.二、以设备为中心的架构蜂窝设计在历史上一直依靠“小区”作为无线接入网中基本单元的公理角色。在 这样的设计假设下，设备通过建立下行链路和上行链路连接来获得服务，同时承 载控制和数据业务，基站命令该设备所在的小区。在过去的几年中，不同的趋势 已经表明这种以细胞为中心的结构受到了其颠覆性：1 ,由于异构网络的兴起，基站密度正在迅速增加。虽然异构网

49、络已经在4G中实 现了标准化，但该体系结构并不是为支持它们而设计的。网络密集化可能需要对 5G进行一些重大更改。例如，部署具有极大不同的发射功率和覆盖区域的基站 需要以允许相应信息流经不同节点集的方式来分离下行链路和上行链路5。2 .对额外频谱的需求将不可避免地导致在同一系统中具有完全不同的传播特性 的频段并存。在这种情况下，6提出了一个“幻像单元”的概念，其中数据和 控制平面是分开的：控制信息是由高功率节点以微波频率发送的，而有效载荷数 据是由低功率节点以微波频率发送的。毫米波频率。（请参阅第三节。）3 .出现了一种新的概念，称为与云无线电接入网概念相关的集中式基带（参见 7）,其中虚拟化导致节点与分配用于处理与该节点相关联的处理的硬件之间 的解耦。例如，