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CIF: Small: Fundamental limits and coding for massive wireless random-access

CIF：小：大规模无线随机访问的基本限制和编码

基本信息

批准号：
1717842
负责人：
Yury Polyanskiy
金额：
$ 45万
依托单位：
Massachusetts Institute of Technology
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-07-01 至 2022-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1717842&HistoricalAwards=false
关键词：
CIF Small Fundamental limits coding

项目摘要

The key expected innovation of the next generation of radio-access networks (such as cellular) is their ability to service vast numbers of active devices as envisioned in the so-called "Internet-of-Things". Unfortunately, current networks were designed with the human-type communication in mind, and this led to a focus on the operating regime of a (relatively) few simultaneously active users. More specifically, present systems employ centralized resource allocation, thus orthogonalizing the access from different users. This solution is not acceptable for machine-type communication, as it relies on a significant control-layer overhead thereby incurring a significant penalty in latency and energy efficiency. Consequently, there is a strong economical demand for a new solution in both the unlicensed spectrum (so called, low-power wide-area networks) and the licensed spectrum (5G).The goal of this work is to provide theoretical guidance for the design of the multiple-access layer in the next generation of wireless networks. Classical work on the topic lacks several specific details, making it inadequate: ignoring the control-layer overhead in network analytic literature, and ignoring delay in information theory. Consequently, this work aims to provide necessary contemporary modifications: (a) a gigantic number of idle (inactive) users; (b) a still large number of active users; (c) short packets; (d) high energy-efficiency (low energy-per-bit). This project introduces a new paradigm of random-access coding that separates data communication from user identification, for which fundamental limits are going to be derived and the low-complexity practical solutions studied. Performance of the currently available solutions will be contrasted with the non-asymptotic fundamental limits and new solutions developed. In addition to information-theoretic and communication-theoretic parts, the work involves a combinatorial-theoretic component in the form of constructing Sidon sets, B2-sequences and superimposed codes.

下一代无线接入网络（如蜂窝网络）的关键创新是它们能够为所谓的“物联网”所设想的大量有源设备提供服务。不幸的是，当前的网络在设计时考虑了人类类型的通信，这导致了对（相对）少数同时活跃用户的操作制度的关注。更具体地说，目前的系统采用集中的资源分配，从而使不同用户的访问正交化。对于机器类型的通信，这种解决方案是不可接受的，因为它依赖于大量的控制层开销，从而导致延迟和能源效率方面的重大损失。因此，在未授权频谱（所谓的低功耗广域网）和授权频谱（5G）中都存在对新解决方案的强烈经济需求。本研究的目的是为下一代无线网络的多址层设计提供理论指导。关于该主题的经典工作缺乏几个具体细节，使其不足：忽略了网络分析文献中的控制层开销，忽略了信息论中的延迟。因此，这项工作旨在提供必要的当代修改：(a)大量空闲（不活跃）用户；(b)仍然有大量的活跃用户；(c)短数据包；(d)高能效（低每比特能量）。该项目引入了一种新的随机访问编码范式，将数据通信与用户识别分开，将推导其基本限制并研究低复杂性的实际解决方案。现有解的性能将与非渐近基本极限和新解进行比较。除了信息理论和通信理论部分，这项工作还涉及到以构造西顿集、b2序列和叠加码的形式构成的组合理论部分。

项目成果

期刊论文数量（22）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Reconstruction on 2D Regular Grids

二维规则网格重建

DOI：
10.1109/isit45174.2021.9518174
发表时间：
2021
期刊：
IEEE International Symposium on Information Theory
影响因子：
0
作者：
Makur, Anuran;Mossel, Elchanan;Polyanskiy, Yury
通讯作者：
Polyanskiy, Yury

Almost Optimal Scaling of Reed-Muller Codes on BEC and BSC Channels

BEC 和 BSC 通道上 Reed-Muller 码的近乎最优缩放

DOI：
发表时间：
2018
期刊：
2018 IEEE Int. Symp. Inf. Theory (ISIT
影响因子：
0
作者：
Hassani, Hamed;Kudekar, Shrinivas;Ordentlich, Or;Polyanskiy, Yury;Urbanke, Rudiger
通讯作者：
Urbanke, Rudiger

List-Decodable Zero-Rate Codes

列表可解码零速率代码

DOI：
10.1109/tit.2018.2868957
发表时间：
2019
期刊：
IEEE Transactions on Information Theory
影响因子：
2.5
作者：
Alon, Noga;Bukh, Boris;Polyanskiy, Yury
通讯作者：
Polyanskiy, Yury

Stochastic block model entropy and broadcasting on trees with survey

随机块模型熵和树上的调查广播

DOI：
发表时间：
2021
期刊：
Proceedings of Machine Learning Research
影响因子：
0
作者：
Abbe, Emmanuel;Cornacchia, Elisabetta;Gu, Yuzhou;Polyanskiy, Yury
通讯作者：
Polyanskiy, Yury

Beta–Beta Bounds: Finite-Blocklength Analog of the Golden Formula

Beta-Beta 界：黄金公式的有限块长度模拟

DOI：
10.1109/tit.2018.2837104
发表时间：
2018
期刊：
IEEE Transactions on Information Theory
影响因子：
2.5
作者：
Yang, Wei;Collins, Austin;Durisi, Giuseppe;Polyanskiy, Yury;Poor, H. Vincent
通讯作者：
Poor, H. Vincent