Optical ISAC: Fundamental Performance Limits and Transceiver Design

Alireza Ghazavi Khorasgani, Mahtab Mirmohseni, Ahmed Elzanaty
{"title":"Optical ISAC: Fundamental Performance Limits and Transceiver Design","authors":"Alireza Ghazavi Khorasgani, Mahtab Mirmohseni, Ahmed Elzanaty","doi":"arxiv-2408.11792","DOIUrl":null,"url":null,"abstract":"This paper characterizes the optimal capacity-distortion (C-D) tradeoff in an\noptical point-to-point (P2P) system with single-input single-output for\ncommunication and single-input multiple-output for sensing (SISO-SIMO-C/S)\nwithin an integrated sensing and communication (ISAC) framework. We introduce\npractical, asymptotically optimal maximum a posteriori (MAP) and maximum\nlikelihood estimators (MLE) for target distance, addressing nonlinear\nmeasurement-to-state relationships and non-conjugate priors. Our results show\nthese estimators converge to the Bayesian Cramer-Rao bound (BCRB) as sensing\nantennas increase. We also demonstrate that the achievable rate-CRB (AR-CRB)\nserves as an outer bound (OB) for the optimal C-D region. To optimize input\ndistribution across the Pareto boundary of the C-D region, we propose two\nalgorithms: an iterative Blahut-Arimoto algorithm (BAA)-type method and a\nmemory-efficient closed-form (CF) approach, including a CF optimal distribution\nfor high optical signal-to-noise ratio (O-SNR) conditions. Additionally, we\nextend and modify the Deterministic-Random Tradeoff (DRT) to this optical ISAC\ncontext.","PeriodicalId":501215,"journal":{"name":"arXiv - STAT - Computation","volume":"34 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - STAT - Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.11792","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This paper characterizes the optimal capacity-distortion (C-D) tradeoff in an optical point-to-point (P2P) system with single-input single-output for communication and single-input multiple-output for sensing (SISO-SIMO-C/S) within an integrated sensing and communication (ISAC) framework. We introduce practical, asymptotically optimal maximum a posteriori (MAP) and maximum likelihood estimators (MLE) for target distance, addressing nonlinear measurement-to-state relationships and non-conjugate priors. Our results show these estimators converge to the Bayesian Cramer-Rao bound (BCRB) as sensing antennas increase. We also demonstrate that the achievable rate-CRB (AR-CRB) serves as an outer bound (OB) for the optimal C-D region. To optimize input distribution across the Pareto boundary of the C-D region, we propose two algorithms: an iterative Blahut-Arimoto algorithm (BAA)-type method and a memory-efficient closed-form (CF) approach, including a CF optimal distribution for high optical signal-to-noise ratio (O-SNR) conditions. Additionally, we extend and modify the Deterministic-Random Tradeoff (DRT) to this optical ISAC context.
光学 ISAC:基本性能限制和收发器设计
本文描述了在集成传感和通信(ISAC)框架内,单输入单输出通信和单输入多输出传感(SISO-SIMO-C/S)的光学点对点(P2P)系统中的最佳容量-失真(C-D)权衡。我们为目标距离引入了实用、渐进最优的最大后验(MAP)和最大似然估计(MLE),解决了测量与状态之间的非线性关系和非共轭先验问题。我们的研究结果表明,随着传感天线的增加,这些估计器会向贝叶斯克拉默-拉奥边界(BCRB)收敛。我们还证明,可实现速率-CRB(AR-CRB)可作为最优 C-D 区域的外部界限(OB)。为了优化 C-D 区域帕累托边界上的输入分配,我们提出了两种算法:一种是迭代布拉赫特-阿里莫托算法(BAA)类型的方法,另一种是内存效率闭式(CF)方法,包括针对高光信噪比(O-SNR)条件的 CF 最佳分配。此外,我们还对确定性-随机权衡(DRT)进行了扩展和修改,以适应这种光学 ISACcontext。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信