人为噪声
隐蔽的
计算机科学
基站
传输(电信)
吞吐量
噪音(视频)
计算机网络
发射机功率输出
蜂窝网络
天线阵
数据传输
误码率
天线(收音机)
电子工程
频道(广播)
发射机
电信
无线
工程类
人工智能
哲学
图像(数学)
语言学
作者
Jiang Yu'e,Liangmin Wang,Hsiao-Hwa Chen
出处
期刊:IEEE Transactions on Vehicular Technology
[Institute of Electrical and Electronics Engineers]
日期:2020-01-14
卷期号:69 (3): 2980-2992
被引量:18
标识
DOI:10.1109/tvt.2020.2966538
摘要
Due to its high speed and low latency, D2D communication plays an important role in providing proximity data services in 5G systems, which may contain privacy sensitive data. Covert communication is useful to protect the privacy of user data against adversaries. In a D2D underlaying cellular network, an antenna array can be used at a base station (BS) to transmit artificial noise to confuse adversaries that try to detect D2D covert signals. Based on the numbers of antennas at BS, two covert schemes are presented in this work and their performances are evaluated in terms of D2D covert throughput, i.e., maximum achievable D2D data rate with the given covertness requirements. As only channel distribution information (CDI) of adversary links is known to the BS, the average minimum error probability (AMEP) is used as a metric to measure the covertness performance. In the proposed schemes, closed-form expressions of the minimum AMEP and achievable D2D data rate are derived. It is shown that the derivation of minimum AMEP can be simplified if either one or massive antennas are allocated for sending artificial noise. The analytical results are compared to Monte-Carlo simulation results to verify the feasibility of the proposed schemes. It is also revealed that covert throughput can be further improved by setting system parameters properly, e.g., the number of antennas at BS and artificial noise transmit power.
科研通智能强力驱动
Strongly Powered by AbleSci AI