Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Electronics Letters

Precoding for secrecy rate maximisation in cognitive MIMO wiretap channels

Bing Fang, Zuping Qian, Zhong Wei, Wei Shao

Published Oct 1, 2015• 2 citations
Publisher

Abstract

The problem of physical layer security in a cognitive MIMO wiretap channel is studied. The problem is formulated as a secrecy rate maximisation (SRM) problem, and solved by a successive convex approximation (SCA) method. With the SCA method, the non‐convex part of the SRM problem is approximated by its first‐order Taylor expansion. Then, relying on solving a series of convexified optimisation problems, an iterative precoding algorithm is developed.

DOI
10.1049/el.2015.1486

Related papers

Iterative precoding for MIMO wiretap channels using successive convex approximation

Bing Fang, Zuping Qian, Zhong Wei +1 more

In this paper, we study the precoding problem for physical layer security in a general multiple-input multiple-output (MIMO) wiretap channel. Since the resultant secrecy capacity maximization (SCM) problem is nonconvex in general, we solve it by employing a successive convex approximation method, where the nonconvex part of the formulated problem is approximated by its first-order Taylor expansion. Thus, the SCM problem can be iteratively solved through convex programming of its convexified version. Finally, an iterative precoding algorithm with provable convergence is presented. Numerical simulations are also provided to verify the proposed algorithm.

IEEE Asia-Pacific Conference on Antennas and Propagation•Jun 1, 2015•10 citations

AN-Aided Secrecy Precoding for SWIPT in Cognitive MIMO Broadcast Channels

Bing Fang, Zuping Qian, Zhong Wei +1 more

In this letter, we study the secrecy precoding problem for simultaneous wireless information and power transfer (SWIPT) in a cognitive multiple-input multiple-output (MIMO) broadcast channel. We adopt an artificial noise (AN)-aided precoding scheme and formulate the problem as a secrecy rate maximization (SRM) problem, which is subject to both an interference power constraint imposed to protect the primary user (PU) and an energy harvesting constraint required by the secondary energy receiver (SER). Since the formulated SRM problem constitutes a difference convex (DC)-type programming problem, we solve it by employing a successive convex approximation (SCA) method. With the SCA method, the nonconvex part of the SRM problem can be locally linearized to its first-order Taylor expansion. Then, relying on solving a series of convexified optimization problems, an iterative precoding algorithm is developed. Numerical simulations are also provided to demonstrate the proposed algorithm. Results show that our algorithm can achieve a near-optimal performance with guaranteed convergence.

IEEE Communications Letters•Sep 1, 2015•54 citations

Comments on ‘Precoding for secrecy rate maximisation in cognitive MIMO wiretap channels’

Mahdi Khojastehnia, Sergey L. Loyka

Several gaps and errors in Fang et al. (2015) are identified. Their corrections as well as new results are reported. After these corrections, the successive convex approximation algorithm in Fang et al. (2015) is shown to generate an increasing, converging sequence of secrecy rates, which, for a degraded channel, converges to its secrecy capacity. The failure of the popular convex solver CVX to maximise secrecy rate is illustrated. Alternative algorithms are pointed out.

Electronics Letters•Jun 5, 2020•5 citations

Energy-efficient secrecy precoding for general MIMOME wiretap channels

Bing Fang, Zuping Qian, Zhong Wei +1 more

In this paper, we study the energy-efficient secrecy precoding problem for a general multiple-input multiple-output multiple-eavesdropper (MIMOME) wiretap channel. The system model considered here consists of a common transmitter, a legitimate receiver, and multiple eavesdroppers, all mounted with multiple antennas. In order to improve the energy efficiency (EE) performance of the proposed system, an artificial noise (AN)-aided precoding scheme is adopted. Because the formulated EE maximization problem is of huge nonconvex complexity, we solve it by employing a two-tier optimization structure. Although the outer-tier optimization problem is quite simple and can be efficiently solved by the famous golden section searching method, the inner-tier optimization problem turns out to be nonconvex and cannot be easily solved. To solve it, we relax it to a secrecy rate maximization (SRM) problem, which naturally constitutes a difference convex (DC)-type programming problem and can be iteratively solved by employing a successive convex approximation (SCA) method. Numerical simulations are further provided to demonstrate the proposed algorithms. Results show that our algorithms can converge fast to a near-optimal solution.

International Conference on Wireless Communications and Signal Processing (WCSP)•Oct 1, 2015•2 citations

Comments on “Precoding and Artificial Noise Design for Cognitive MIMOME Wiretap Channels”

Mahdi Khojastehnia, Sergey L. Loyka

Several gaps and errors in “Precoding and Artificial Noise Design for Cognitive MIMOME Wiretap Channels” by Fang et al. are identified and corrected. While accommodating these corrections, a rigours proof is given that the successive convex approximation algorithm of Fang et al. for secrecy rate maximization (SRM) does generate an increasing and bounded sequence of true secrecy rates and hence converges. It is further shown that its convergence point is a KKT point of the original SRM problem and, if the original problem is convex, this convergence point is globally-optimal, which is not necessarily the case in general. An interlacing property of the sequences of the true and approximate secrecy rates is established.

arXiv:2010.12938•IEEE Transactions on Vehicular Technology•Oct 28, 2020•1 citation

Precoder design for secrecy rate maximization in the DF-based MIMO relay networks

Bing Fang, Zuping Qian, Zhong Wei +1 more

In this paper, we study the precoder design problem for secrecy rate maximization in a decode-and-forward (DF)-based multiple-input multiple-output (MIMO) relay network. The system model considered here consists of a source, a trusted relay, a legitimate receiver and an eavesdropper, all mounted with multiple antennas. Our objective is to maximize the achievable secrecy rate of this DF-based MIMO relay wiretap system subject to a total transmit power constraint. Since the formulated secrecy rate maximization (SRM) problem is nonconvex in general, we solve it by employing a successive convex approximation (SCA) method. With the SCA method, the nonconvex part of the formulated problem is linearized to its first-order Taylor expansion. Then, the nonconvex SRM problem can be iteratively solved through successive convex programming of its convexified version, and thus an iterative precoding algorithm is developed. Moreover, the theoretical result is further extended to the case when multiple eavesdroppers are simultaneously present. Finally, numerical simulations are provided to evaluate the performance of the proposed algorithm. Results show that our algorithm can converge fast to a near-optimal solution.

International Conference on Wireless Communications and Signal Processing (WCSP)•Oct 1, 2015•1 citation
The problem of physical layer security in a cognitive MIMO wiretap channel is studied. The problem is formulated as a secrecy rate maximisation (SRM) problem, and solved by a successive convex approximation (SCA) method. With the SCA method, the non‐convex part of the SRM problem is approximated by its first‐order Taylor expansion. Then, relying on solving a series of convexified optimisation problems, an iterative precoding algorithm is developed.
In this paper, we study the precoding problem for physical layer security in a general multiple-input multiple-output (MIMO) wiretap channel. Since the resultant secrecy capacity maximization (SCM) problem is nonconvex in general, we solve it by employing a successive convex approximation method, where the nonconvex part of the formulated problem is approximated by its first-order Taylor expansion. Thus, the SCM problem can be iteratively solved through convex programming of its convexified version. Finally, an iterative precoding algorithm with provable convergence is presented. Numerical simulations are also provided to verify the proposed algorithm.
In this letter, we study the secrecy precoding problem for simultaneous wireless information and power transfer (SWIPT) in a cognitive multiple-input multiple-output (MIMO) broadcast channel. We adopt an artificial noise (AN)-aided precoding scheme and formulate the problem as a secrecy rate maximization (SRM) problem, which is subject to both an interference power constraint imposed to protect the primary user (PU) and an energy harvesting constraint required by the secondary energy receiver (SER). Since the formulated SRM problem constitutes a difference convex (DC)-type programming problem, we solve it by employing a successive convex approximation (SCA) method. With the SCA method, the nonconvex part of the SRM problem can be locally linearized to its first-order Taylor expansion. Then, relying on solving a series of convexified optimization problems, an iterative precoding algorithm is developed. Numerical simulations are also provided to demonstrate the proposed algorithm. Results show that our algorithm can achieve a near-optimal performance with guaranteed convergence.
In this paper, we study the energy-efficient secrecy precoding problem for a general multiple-input multiple-output multiple-eavesdropper (MIMOME) wiretap channel. The system model considered here consists of a common transmitter, a legitimate receiver, and multiple eavesdroppers, all mounted with multiple antennas. In order to improve the energy efficiency (EE) performance of the proposed system, an artificial noise (AN)-aided precoding scheme is adopted. Because the formulated EE maximization problem is of huge nonconvex complexity, we solve it by employing a two-tier optimization structure. Although the outer-tier optimization problem is quite simple and can be efficiently solved by the famous golden section searching method, the inner-tier optimization problem turns out to be nonconvex and cannot be easily solved. To solve it, we relax it to a secrecy rate maximization (SRM) problem, which naturally constitutes a difference convex (DC)-type programming problem and can be iteratively solved by employing a successive convex approximation (SCA) method. Numerical simulations are further provided to demonstrate the proposed algorithms. Results show that our algorithms can converge fast to a near-optimal solution.
Several gaps and errors in “Precoding and Artificial Noise Design for Cognitive MIMOME Wiretap Channels” by Fang et al. are identified and corrected. While accommodating these corrections, a rigours proof is given that the successive convex approximation algorithm of Fang et al. for secrecy rate maximization (SRM) does generate an increasing and bounded sequence of true secrecy rates and hence converges. It is further shown that its convergence point is a KKT point of the original SRM problem and, if the original problem is convex, this convergence point is globally-optimal, which is not necessarily the case in general. An interlacing property of the sequences of the true and approximate secrecy rates is established.
In this paper, we study the precoder design problem for secrecy rate maximization in a decode-and-forward (DF)-based multiple-input multiple-output (MIMO) relay network. The system model considered here consists of a source, a trusted relay, a legitimate receiver and an eavesdropper, all mounted with multiple antennas. Our objective is to maximize the achievable secrecy rate of this DF-based MIMO relay wiretap system subject to a total transmit power constraint. Since the formulated secrecy rate maximization (SRM) problem is nonconvex in general, we solve it by employing a successive convex approximation (SCA) method. With the SCA method, the nonconvex part of the formulated problem is linearized to its first-order Taylor expansion. Then, the nonconvex SRM problem can be iteratively solved through successive convex programming of its convexified version, and thus an iterative precoding algorithm is developed. Moreover, the theoretical result is further extended to the case when multiple eavesdroppers are simultaneously present. Finally, numerical simulations are provided to evaluate the performance of the proposed algorithm. Results show that our algorithm can converge fast to a near-optimal solution.