Joint Secure Transmission and Interference Mitigation in Cooperative MIMO Systems: A Feasibility Study

To enhance physical layer security (PLS) and mitigate interference at legitimate receivers, artificial noise (AN) assisted interference alignment (IA) is explored in cooperative multiple-input multiple-output (MIMO) systems. The feasibility of traditional leakage minimization (LM) based IA is analyzed. We show that there exist two drawbacks which are not discussed in traditional LM based IA: 1) the necessary condition for the feasibility of IA is loose, and 2) the secret signal cancellation may occur at the desired receiver, which makes secure transmission infeasible. We analyze the reason and establish a condition under which either the secret signal cancellation is inevitable or IA is infeasible. Then a modified IA is proposed. Compared with the traditional LM based IA, a tighter necessary condition is established and the secret signal is protected against cancellation. Moreover, we prove that the proposed condition guarantees the properness of system, which is a rigorous characterization of necessary conditions for achieving IA. Under assumption that the modified IA is feasible, we provide a secrecy enhancing design to maximize the secrecy rate. subject to a secrecy outage constraint. We also establish a condition under which a positive secrecy rate is feasible. Numerical results validate the effectiveness of the proposed approach.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Vehicular Technology
Published
2024-10-24
DOI
https://doi.org/10.1109/tvt.2024.3486295
Primary Topic
Wireless Communication Security Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Joint Secure Transmission and Interference Mitigation in Cooperative MIMO Systems: A Feasibility Study

Huanhuan Song, Jinsong Wu, Hong Wen, Jie Tang et al.
IEEE Transactions on Vehicular Technology
Wireless Communication Security Techniques
article

Joint Secure Transmission and Interference Mitigation in Cooperative MIMO Systems: A Feasibility Study

Huanhuan Song, Jinsong Wu, Hong Wen, Jie Tang, Lin Hu, Qianbin Chen, Jiabing Fan
article en

Abstract

To enhance physical layer security (PLS) and mitigate interference at legitimate receivers, artificial noise (AN) assisted interference alignment (IA) is explored in cooperative multiple-input multiple-output (MIMO) systems. The feasibility of traditional leakage minimization (LM) based IA is analyzed. We show that there exist two drawbacks which are not discussed in traditional LM based IA: 1) the necessary condition for the feasibility of IA is loose, and 2) the secret signal cancellation may occur at the desired receiver, which makes secure transmission infeasible. We analyze the reason and establish a condition under which either the secret signal cancellation is inevitable or IA is infeasible. Then a modified IA is proposed. Compared with the traditional LM based IA, a tighter necessary condition is established and the secret signal is protected against cancellation. Moreover, we prove that the proposed condition guarantees the properness of system, which is a rigorous characterization of necessary conditions for achieving IA. Under assumption that the modified IA is feasible, we provide a secrecy enhancing design to maximize the secrecy rate. subject to a secrecy outage constraint. We also establish a condition under which a positive secrecy rate is feasible. Numerical results validate the effectiveness of the proposed approach.

IEEE Transactions on Vehicular TechnologyVol. 74(3)
Chongqing University of Posts and Telecommunications (CN), University of Electronic Science and Technology of China (CN), Guilin University of Electronic Technology (CN)
Openalex Percentile: Top 84%
Wireless Communication Security Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.