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经典通信信号的量子化处理:现状与展望 被引量:3

Quantum Processing for Classical Communication Signals: Progress and Outlook
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摘要 随着通信技术的飞速发展,通信渗入并影响了人类生活的方方面面,同时与日俱增的用户量也对通信系统的连接密度以及频谱效率提出更高的要求。然而,经典通信中的信号处理方法面临着通信性能与计算复杂度之间相互制约的问题,这使得相关通信技术的推广和应用受到极大限制。量子计算,作为一种遵循量子力学规律实施计算的新型计算范式,在特定问题上能够带来远低于经典算法的计算复杂度,为解决经典通信信号处理的问题提供了全新的思路。为此,我们梳理并分析了经典通信信号的量子化处理的相关研究。本文梳理了经典通信信号的量子化处理研究随时间的发展进程,并按照所解决的问题进行分类详细介绍相关量子计算方法及其使用,包括信道估计,数据检测及多用户检测。最后,本文对量子计算的进一步应用进行了展望。 With the rapid development of communication technology,communication widely affects all aspects of human life,and the ever increasing user volume sets high level requirements on the connection density and spectrum efficiency of communication systems.However,the signal processing method in classical communication faces a problem of mutual restriction between communication performance and computing complexity,which makes the promotion and application of related communication technologies extremely limited.Quantum computing,as a new computing paradigm following the principles of quantum mechanics to perform computing,can reach a much lower computing complexity compared to classical algorithms on particular problems,paving a new way for solving the problem of classical communication signal processing.Hence,in this paper we combed and analyzed the related research on the quantum processing of classical communication signals.We summarizes the quantum computing method involved in the quantum processing of classical communication signals in chronological order,and introduces related methods in detail towards different solved problems,namely,the channel estimation,data detection and multi-user detection.In addition,the paper makes a prospect for the further use of quantum computing.
作者 方妍 郭欣 叶文景 陈巍 Fang Yan;Guo Xin;Ye Wenjing;Chen Wei(Department of Electronic Engineering,Tsinghua University,Beijing 100084,China;Lenovo Research,Beijing 100094,China)
出处 《信号处理》 CSCD 北大核心 2019年第10期1615-1625,共11页 Journal of Signal Processing
基金 国家自然科学基金(61671269,61971264) 北京市自然科学基金(4191001) 中组部“万人计划”的支持
关键词 信号处理 量子计算 量子搜索 信道估计 多用户检测 signal processing quantum computing quantum search channel estimation multiuser detection
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  • 1李飞,赵生妹,郑宝玉.量子神经元特性研究[J].电路与系统学报,2004,9(4):76-80. 被引量:3
  • 2胡程,刘志鹏,曾涛,符蓓蓓,朱宇.一种精确的地球同步轨道SAR成像聚焦方法[J].兵工学报,2010,31(S2):28-32. 被引量:6
  • 3曲卫 ,贾鑫 ,吴彦鸿 .基于通信卫星信号的星地双(多)基地雷达及关键技术[J].装备指挥技术学院学报,2004,15(6):68-71. 被引量:2
  • 4Graupe D, Principles of Artificial Neural Networks [ M ]. 2nd. River Edge, NJ, USA: World Scientific Publishing Co., Inc., 2007.
  • 5Purushothaman G, Karayiannis N B. Quantum neural net- works (QNNs) : inherently fuzzy feedforward neural net- works [ J ]. Neural Networks, IEEE Transactions on, 1997, 8(3) :679-693.
  • 6Karayiannis N B, Yaohua X. Training Reformulated Ra- dial Basis Function Neural Networks Capable of Identif- ying Uncertainty in Data Classification [ J ]. Neural Net- works, IEEE Transactions on, 2006, 17 (5) : 1222-1234.
  • 7Li J, Li P. Feature difference matrix and QNNs for facial expression recognition[ C]. Control and Decision Confer-ence 2008, Chinese.
  • 8Snyman J. Practical Mathematical Optimization[ M]. New York: Springer, 2005.
  • 9Yuhuan Z, Xiongwei Z, Jinming W, et al. Research on speaker feature dimension reduction based on CCA and PCA[ C]. Wireless Communications and Signal Process- ing (WCSP) , 2010 International Conference on, China.
  • 10ALTAISKY M V. Quantum neural network [EB/OL].http://xxx.lanl.gov/quant-ph/0107012, 2001.

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