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NeTS: Small: Mobile mmWaves: Addressing the Cellular Capacity Crisis with 60 GHz Picocells

NeTS: Small: Mobile mmWaves: Addressing the Cellular Capacity Crisis with 60 GHz Picocells
NeTS:小型:移动毫米波:利用 60 GHz 微微蜂窝解决蜂窝容量危机
批准号:
1317153
负责人:
Upamanyu Madhow
金额:
$50.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-10-01 至 2017-09-30

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中文摘要
翻译
智能手机和平板电脑使消费者能够在旅途中享受丰富的音频和视频内容,但这种日益复杂的移动设备的激增给移动运营商带来了容量危机。据估计,为快速增长的移动用户提供富媒体内容,需要将蜂窝网络容量增加1000倍,而目前的蜂窝频段根本无法支持这一点。在这笔拨款下进行的研究探索了蜂窝数据的另一种可能的转型方法,使用60ghz频段的未经许可频谱,其可用带宽比现有系统中使用的带宽高几个数量级,在移动设备的下行链路上达到每秒千兆比特的吞吐量水平。设想网络的基站将随机部署(例如,在灯柱和屋顶上)。由于载波波长小,许多具有非常大数量(例如,1000个)元素的天线阵列可以内置到不大于典型WiFi接入点的基站中。这种天线阵列可用于将铅笔波束指向移动用户,峰值数据速率可达每秒千兆位的数倍(比目前可用的最高WiFi数据速率高一个数量级)。然而,较小的载波波长也意味着无线电波很容易被建筑物、墙壁和人等障碍物阻挡,包括携带移动设备的人的身体。为了应对传播环境的快速变化,人们开发了多种基站协调的新技术,使它们能够调整其波束以保持与给定移动设备的连接,并确保发送给移动设备的数据跟随它。采用了一种新颖的非对称网络架构,下行链路采用低带宽60ghz信标和多gbps数据,上行链路采用LTE反馈和低速数据。基站采用压缩信号处理,根据手机反馈进行快速信道估计和波束自适应。为实现基站或路径的无缝切换,开发了分布式基站协调机制。该架构最大限度地降低了移动设备的复杂性和功耗:设备的60 GHz无线电只需要接收,设备不需要切换。移动宽带容量危机是目前移动运营商面临的最大挑战,因此这个项目的成功将影响到一个价值数十亿美元的产业。为了最大限度地发挥影响的潜力,研究结果和模型将广泛传播给工业界和学术界。调查人员计划在招募和指导女本科生和研究生方面做出重大努力,围绕一个关怀社区的概念组织起来。
英文摘要
Smart phones and tablets enable consumers to enjoy rich audio and video content on the go, but the proliferation of such increasingly sophisticated mobile devices has created a capacity crisis for mobile operators. It is estimated that supporting rich media content for a rapidly increasing fraction of mobile users requires a 1000-fold increase in cellular network capacity, which current cellular bands simply cannot support. The research pursued under this grant explores an alternative, and potentially transformational, approach to cellular data, using unlicensed spectrum in the 60 GHz band, where the available bandwidth is orders of magnitude higher than those used in existing systems, at the level of multiple Gigabits per second throughput on the downlink to the mobile devices. Base stations for the envisioned network will be deployed opportunistically (e.g., on lampposts and rooftops). Due to the small carrier wavelength, many antenna arrays with a very large number (e.g., 1000) of elements can be built into base stations which are no larger than a typical WiFi access point. Such antenna arrays can be used to direct pencil beams at mobile users, with peak data rates of multiples of Gigabits per second (order of magnitude higher than the highest WiFi data rates available today). However, the small carrier wavelength also implies that the radio waves are easily blocked by obstacles such as buildings, walls, and humans, including the body of the person carrying the mobile device. In order to handle such rapid changes in the propagation environment, novel techniques are developed for multiple base stations to coordinate, such that they can adapt their beams to maintain connectivity with a given mobile device, and can ensure that the data destined for the mobile follows it around. A novel asymmetric network architecture is employed, with low-bandwidth 60 GHz beaconing and multi-Gbps data on the downlink, and LTE feedback and lower-speed data on the uplink. The base stations employ compressive signal processing for rapid channel estimation and beam adaptation, based on the feedback from the mobiles. Distributed base station coordination mechanisms are developed for seamlessly switching base stations or paths. The architecture minimizes complexity and power consumption in the mobile device: the device's 60 GHz radio only needs to receive, and the device is oblivious of handoffs.The mobile broadband capacity crisis is the greatest challenge facing cellular providers today, hence the success of this project can impact a multi-billion dollar industry. In order to maximize the potential for impact, the results and models will be widely disseminated to both industry and academia. The investigators plan significant efforts for recruitment and mentoring of female undergraduate and graduate students, organized around the concept of a caring community.
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会议论文
RINGS: Massive Extended-Array Transceivers for Robust Scaling of All-Digital mmWave MIMO
EAGER: Towards robust, interpretable deep learning via communication theory and neuro-inspiration
Collaborative Research: CNS Core: Large: 4D100: Foundations and Methods for City-scale 4D RF Imaging at 100+ GHz
NeTS: Large: Collaborative Research: GigaNets: A Path to Experimental Research in Millimeter Wave Networking
国内基金
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