Multiplexing Techniques for Scalable Wireless Interconnects at sub-THz Frequencies: Circuits-EM-Communication Codesign Approach

亚太赫兹频率可扩展无线互连的复用技术:电路-电磁-通信协同设计方法

基本信息

  • 批准号:
    1408490
  • 负责人:
  • 金额:
    $ 30万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2014
  • 资助国家:
    美国
  • 起止时间:
    2014-08-01 至 2018-07-31
  • 项目状态:
    已结题

项目摘要

Multiplexing Techniques for Scalable Wireless Interconnects at THz FrequenciesECCS-1408490PI: Kushik Sengupta, Princeton University This proposal aims to investigate and develop spatially multiplexed architectures for wireless interconnects at sub-THz frequencies as scalable, energy-efficient solution towards one terabit per second (1 Tb/s). As we enter the era of terra-scale computing, massive amounts of data crunching by these processors will require inordinately large amount of bandwidth, not currently served by either electrical or optical interconnect solutions. Current methods of scaling of electrical interconnects to higher data rates are either limited by the available bandwidth density (Gb/s/mm2), energy cost, the circuit complexities in driving high-speed data through the long and lossy physical traces, or by the maximum number of parallel physical traces possible to accommodate in a constrained form factor. Wireless interconnects near THz frequencies are promising , but wireless data rates of 10Gb/s and the high energy/bit requirement, falls way short of meeting the bandwidth requirements for future off-chip interconnects. In this proposal, we aim to investigate techniques where the capacity of the channel can be increased many-fold using communication theoretic spatial-domain multiplexing techniques. Under the same total power constraint, such architectures have orders of magnitude more channel capacity, thereby providing a scalable solution towards wireless Tb/s interconnects. A key component in this proposal is to combine seamlessly, high-frequency circuits and systems and antennas with communication-theoretic techniques to increase capacity and data-rates by orders of magnitude, not otherwise possible in a single directional partitioned approach. Metal-based interconnect traces on printed circuit boards(PCB) serve as the most common method of chip-chip interconnects. However, increasing need of computational power to crunch more and more data in specialized server systems, high-performance computing or even portable devices, requires that communication data-rate from the processor to the peripherals be scaled proportionately. In most cases, the number of input-output pins is limited by the form factor, which puts a bottleneck on communication capacity among all the processors. In this proposal, we investigate techniques to use very high-frequency electromagnetic waves located in the Terahertz portion of the spectrum (between microwaves and infra-red) to establish seamless wireless communication links among the chipsets. Moving to such high frequencies enables us to exploit orders of magnitude higher bandwidth needed for sustaining such high data rates. Additionally, we investigate techniques to increase the communication links capacity by another order through spatial multiplexing techniques in a short-range communication setting. The success of this project is envisioned to bring new forms of smart interconnect solutions for a host of various applications from high-performance computing to internet data centers. The results of this research effort are also expected to have major impact in advancing the field of THz electronics benefitting diverse applications such as imaging and sensing. In a broader vision, this will have major impacts in radically new technologies in communication and computation, which not only makes us a more connected society, but also fuel research in other areas of applied science. This research is also expected to train both graduate and undergraduate students in multi-disciplinary fields, which are vitally important for solving challenging research problems for the future.
用于太赫兹频率的可扩展无线互连的多路复用技术ECCS-1408490PI:Kushik Sengupta,普林斯顿大学该提案旨在研究和开发用于亚THz频率的无线互连的空间多路复用体系结构,作为可扩展、节能的解决方案,以达到每秒1太比特(1 TB/S)。随着我们进入陆地规模的计算时代,由这些处理器处理的海量数据将需要超大的带宽,目前电气或光学互连解决方案都无法满足这一要求。当前将电互连调整为更高数据速率的方法受限于可用带宽密度(GB/S/mm~2)、能量成本、通过长且有损耗的物理迹线来驱动高速数据的电路复杂性,或者受限于在受限的外形尺寸中可能容纳的并行物理迹线的最大数目。太赫兹频率附近的无线互连前景看好,但10 Gb/S的无线数据速率和较高的能量/比特要求,远远不能满足未来片外互连的带宽要求。在该方案中,我们的目标是研究使用通信理论空域多路复用技术可以将信道容量提高许多倍的技术。在相同的总功率限制下,这样的架构具有更大数量级的信道容量,从而为无线TB/S互连提供了可扩展的解决方案。这一提议的一个关键组成部分是将高频电路、系统和天线与通信理论技术无缝地结合在一起,以提高容量和数据速率数量级,这在单一方向分区方法中是不可能的。印刷电路板(PCB)上的金属基互连线是最常见的芯片互连方法。然而,在专用服务器系统、高性能计算甚至便携式设备中对计算能力的需求日益增长以处理越来越多的数据,这要求处理器到外围设备的通信数据速率按比例扩展。在大多数情况下,输入输出引脚的数量受到外形因素的限制,这对所有处理器之间的通信容量造成了瓶颈。在这项提案中,我们研究了使用位于频谱太赫兹部分(微波和红外线之间)的甚高频电磁波在芯片组之间建立无缝无线通信链路的技术。移动到如此高的频率使我们能够利用维持如此高的数据速率所需的数量级更高的带宽。此外,我们还研究了在短距离通信环境下通过空间复用技术将通信链路容量提高另一个数量级的技术。预计该项目的成功将为从高性能计算到互联网数据中心的各种应用程序带来新形式的智能互联解决方案。这项研究工作的结果预计也将对推进太赫兹电子领域产生重大影响,使成像和传感等各种应用受益。从更广泛的角度来看,这将对通信和计算领域的全新技术产生重大影响,这不仅使我们成为一个更紧密联系的社会,还将推动应用科学其他领域的研究。这项研究还有望培养多学科领域的研究生和本科生,这对解决未来具有挑战性的研究问题至关重要。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Kaushik Sengupta其他文献

Terahertz Beam Steering: from Fundamentals to Applications
Role Conflict, Role Balance and Affect: A Model of Well-being of the Working Student
角色冲突、角色平衡与影响:在职学生的幸福感模型
Analysis of mechanical property of electrically assisted friction stir welding to enhance the efficiency of joints
分析电辅助搅拌摩擦焊的机械性能以提高接头效率
  • DOI:
    10.1016/j.matpr.2020.06.321
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Kaushik Sengupta;Dilip Kr Singh;A. K. Mondal;D. Bose;B. Ghosh
  • 通讯作者:
    B. Ghosh
mmWAVE and Signal Processing
毫米波和信号处理
  • DOI:
    10.1109/fnwf58287.2023.10520461
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Tim Lee;Ramesh Gupta;H. Krishnaswamy;Paolo Gargini;Earl McCune;Harrison Chang;Alberto Valdes;Kamal Samantha;Kaushik Sengupta;Masood Ur;Imran Mehdi;Anding Zhu
  • 通讯作者:
    Anding Zhu
Dentin-derived alveolar bone graft for alveolar augmentation: A systematic review
用于牙槽增量的牙本质源性牙槽骨移植:系统评价
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Dedy Agoes Mahendra;Kavanila Bilbalqish;Alexander Patera Nugraha;A. Cahyanto;Kaushik Sengupta;Ankur Razdan;Kamal Hanna;N. Hariyani
  • 通讯作者:
    N. Hariyani

Kaushik Sengupta的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Kaushik Sengupta', 18)}}的其他基金

Collaborative Research: CNS Core: Medium: Access, Mobility, and Security above 100 GHz
合作研究:CNS 核心:中:100 GHz 以上的访问、移动性和安全性
  • 批准号:
    2211617
  • 财政年份:
    2022
  • 资助金额:
    $ 30万
  • 项目类别:
    Continuing Grant
RINGS: Resilient mmWave Networks via Distributed In-Surface Computing (mmRISC)
RINGS:通过分布式表面计算 (mmRISC) 的弹性毫米波网络
  • 批准号:
    2148271
  • 财政年份:
    2022
  • 资助金额:
    $ 30万
  • 项目类别:
    Continuing Grant
Collaborative Research: A Microfluidic-CMOS Cross-cut Approach enabling Tri-Modal Biorecognition for Highly Accurate Viral Diagnostics
合作研究:一种微流控-CMOS 横切方法,可实现三模态生物识别,实现高精度病毒诊断
  • 批准号:
    1711067
  • 财政年份:
    2017
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
Portable, fluorescence-based bio-molecular sensor on CMOS chip with integrated nano-optics for massively multiplexed assays
CMOS 芯片上的便携式荧光生物分子传感器,具有集成纳米光学器件,适用于大规模多重分析
  • 批准号:
    1610761
  • 财政年份:
    2016
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
Integrated THz Spectroscopy exploiting On-chip Scattering and Device Nonlinearity
利用片上散射和器件非线性的集成太赫兹光谱
  • 批准号:
    1509560
  • 财政年份:
    2015
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant

相似国自然基金

EstimatingLarge Demand Systems with MachineLearning Techniques
  • 批准号:
  • 批准年份:
    2024
  • 资助金额:
    万元
  • 项目类别:
    外国学者研究基金

相似海外基金

CNS Core: Small: Core Scheduling Techniques and Programming Abstractions for Scalable Serverless Edge Computing Engine
CNS Core:小型:可扩展无服务器边缘计算引擎的核心调度技术和编程抽象
  • 批准号:
    2322919
  • 财政年份:
    2024
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
Development of advanced scalable 3D spatial techniques for multi-spectral LiDAR point cloud modeling of boreal forest inventory attributes, above-ground carbon, and wildfire fuel.
开发先进的可扩展 3D 空间技术,用于北方森林库存属性、地上碳和野火燃料的多光谱 LiDAR 点云建模。
  • 批准号:
    570298-2022
  • 财政年份:
    2022
  • 资助金额:
    $ 30万
  • 项目类别:
    Alexander Graham Bell Canada Graduate Scholarships - Doctoral
Advanced error control coding techniques for scalable blockchains
可扩展区块链的高级错误控制编码技术
  • 批准号:
    DP200100731
  • 财政年份:
    2020
  • 资助金额:
    $ 30万
  • 项目类别:
    Discovery Projects
Novel Decomposition Techniques Enabling Scalable Computational Frameworks for Large-Scale Nonlinear Optimization Problems
新颖的分解技术为大规模非线性优化问题提供可扩展的计算框架
  • 批准号:
    2012410
  • 财政年份:
    2020
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
CAREER: Modern nonconvex optimization for machine learning: foundations of geometric and scalable techniques
职业:机器学习的现代非凸优化:几何和可扩展技术的基础
  • 批准号:
    1846088
  • 财政年份:
    2019
  • 资助金额:
    $ 30万
  • 项目类别:
    Continuing Grant
Distributed and Scalable Privacy-Preserving Data Mining Techniques for Big Data
分布式、可扩展的大数据隐私保护数据挖掘技术
  • 批准号:
    RGPIN-2014-04520
  • 财政年份:
    2019
  • 资助金额:
    $ 30万
  • 项目类别:
    Discovery Grants Program - Individual
Distributed and Scalable Privacy-Preserving Data Mining Techniques for Big Data
分布式、可扩展的大数据隐私保护数据挖掘技术
  • 批准号:
    RGPIN-2014-04520
  • 财政年份:
    2018
  • 资助金额:
    $ 30万
  • 项目类别:
    Discovery Grants Program - Individual
Distributed and Scalable Privacy-Preserving Data Mining Techniques for Big Data
分布式、可扩展的大数据隐私保护数据挖掘技术
  • 批准号:
    RGPIN-2014-04520
  • 财政年份:
    2017
  • 资助金额:
    $ 30万
  • 项目类别:
    Discovery Grants Program - Individual
CAREER: Scalable Techniques for Visualizing Very Large Graphs
职业:可视化超大图形的可扩展技术
  • 批准号:
    1652846
  • 财政年份:
    2017
  • 资助金额:
    $ 30万
  • 项目类别:
    Continuing Grant
Distributed and Scalable Privacy-Preserving Data Mining Techniques for Big Data
分布式、可扩展的大数据隐私保护数据挖掘技术
  • 批准号:
    RGPIN-2014-04520
  • 财政年份:
    2017
  • 资助金额:
    $ 30万
  • 项目类别:
    Discovery Grants Program - Individual
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了