Joint communication and computation design for secure integrated sensing and semantic communication system  

作　　者：Jianxin DAI Hui FAN Zhouxiang ZHAO Yongjun XU Zhaohui YANG Xu GAN Zhaoyang ZHANG 

机构地区：[1]School of Science,Nanjing University of Posts and Telecommunications,Nanjing 210023,China [2]College of Information Science and Electronic Engineering,Zhejiang University,Hangzhou 310058,China [3]Zhejiang Provincial Laboratory of Multi-Modal Communication Networks and Intelligent Information Processing,Hangzhou 310027,China [4]School of Communications and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China [5]National Mobile Communications Research Laboratory,Southeast University,Nanjing 210096,China

出　　处：《Science China(Information Sciences)》2025年第3期350-366,共17页中国科学(信息科学)(英文版)

基　　金：supported in part by National Mobile Communications Research Laboratory,Southeast University(Grant No.2023D03);National Key R&D Program of China(Grant No.2023YFB2904804);National Natural Science Foundation of China(Grant Nos.62394292,62394290)。

摘　　要：As a new communication paradigm,semantic communication(SC)differs from conventional communication based on bit transmission by transmitting semantic information,which demonstrates enormous potential in improving communication efficiency.To ensure transmission security,this paper investigates the secure resource allocation problem of integrated sensing and semantic communication(ISSC)systems in the scenario involving multiple eavesdroppers considering cases of both perfect and imperfect channel state information(CSI).Specifically,the concept of secure semantic rate(SSR)is first put forward to measure the reliability of user information acquisition,and then an optimization problem is formulated to maximize the secure semantic efficiency(SSE),which is defined as the ratio of the sum of SSRs to total transmit power.To work out this problem,the optimization problem is first decoupled into two subproblems,i.e.,beamforming optimization subproblem and semantic parameter optimization subproblem.For the beamforming optimization subproblem,this paper simplifies the objective function by utilizing the Dinkelbach algorithm with given semantic parameters and proposes an alternating algorithm to solve a series of convex subproblems iteratively.For the semantic parameter subproblem,the monotonically decreasing property of the objective function with respect to the semantic parameter is revealed mathematically under a given beamforming vector.Finally,simulation results verify the theoretical analysis.

关 键 词：integrated sensing and semantic communication(ISsC) resource allocation beamforming design security robust optimization 

分 类 号：TN929.5[电子电信—通信与信息系统] TP18[电子电信—信息与通信工程]