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IEEE Transactions on Signal Processing

Secure Communication in Multiantenna Cognitive Radio Networks With Imperfect Channel State Information

Yiyang Pei, Ying‐Chang Liang, Kah Chan Teh, Kwok Hung Li

Published Feb 16, 2011• 141 citations
Publisher

Abstract

In this paper, we address the issue of optimal transmitter design to achieve physical layer security for a multiple-input single-output (MISO) cognitive radio network (CRN), in which a secondary user transmitter (SU-Tx) sends confidential information to a SU receiver (SU-Rx) on the same frequency band with a primary user (PU) in the presence of an eavesdropper receiver (ED-Rx). It is assumed that all the channel state information (CSI) of the secondary, primary and eavesdropper channels is not perfectly known at the SU-Tx. The optimal transmitter design, under the restriction of Gaussian signaling without preprocessing of information, involves a nonconvex semiinfinite optimization problem which maximizes the rate of the secondary link while avoiding harmful interference to the PU and keeping the eavesdropper totally ignorant of the messages sent regardless of the uncertainties in the CSI. We propose two approaches to solve this challenging optimization problem. The first one relates the original problem to a sequence of semiinfinite capacity-achieving transmitter design problems in an auxiliary CRN without any eavesdropper, which can then be solved through transformations and using convex semidefinite programs (SDPs). The second approach explores the hidden convexity of the problem and hence transforms it into a single SDP, which significantly reduces the computational complexity. Furthermore, a few heuristic beamforming solutions for the ease of implementation are also introduced. Finally, simulation results are presented to evaluate the performance of the proposed optimal and suboptimal solutions.

DOI
10.1109/tsp.2011.2105479

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In this paper, we address the issue of optimal transmitter design to achieve physical layer security for a multiple-input single-output (MISO) cognitive radio network (CRN), in which a secondary user transmitter (SU-Tx) sends confidential information to a SU receiver (SU-Rx) on the same frequency band with a primary user (PU) in the presence of an eavesdropper receiver (ED-Rx). It is assumed that all the channel state information (CSI) of the secondary, primary and eavesdropper channels is not perfectly known at the SU-Tx. The optimal transmitter design, under the restriction of Gaussian signaling without preprocessing of information, involves a nonconvex semiinfinite optimization problem which maximizes the rate of the secondary link while avoiding harmful interference to the PU and keeping the eavesdropper totally ignorant of the messages sent regardless of the uncertainties in the CSI. We propose two approaches to solve this challenging optimization problem. The first one relates the original problem to a sequence of semiinfinite capacity-achieving transmitter design problems in an auxiliary CRN without any eavesdropper, which can then be solved through transformations and using convex semidefinite programs (SDPs). The second approach explores the hidden convexity of the problem and hence transforms it into a single SDP, which significantly reduces the computational complexity. Furthermore, a few heuristic beamforming solutions for the ease of implementation are also introduced. Finally, simulation results are presented to evaluate the performance of the proposed optimal and suboptimal solutions.
In this paper, we address the physical-layer security issue of a secondary user (SU) in a spectrum-sharing cognitive radio network (CRN) from an information-theoretic perspective. Specially, we consider a secure multiple-input single-output (MISO) cognitive radio channel, where a multi-antenna SU transmitter (SU-Tx) sends confidential information to a legitimate SU receiver (SU-Rx) in the presence of an eavesdropper and on the licensed band of a primary user (PU). The secrecy capacity of the channel is characterized, which is a quasiconvex optimization problem of finding the capacity-achieving transmit covariance matrix under the joint transmit power and interference power constraints. Two numerical approaches are proposed to derive the optimal transmit covariance matrix. The first approach recasts the original quasiconvex problem into a single convex semidefinite program (SDP) by exploring its inherent convexity; while the second one explores the relationship between the secure CRN and the conventional CRN and transforms the original problem into a sequence of optimization problems associated with the conventional CRN, which helps to prove that beamforming is the optimal strategy for the secure MISO CR channel. In addition, to reduce the computational complexity, three suboptimal schemes are presented, namely, scaled secret beamforming (SSB), projected secret beamforming (PSB) and projected cognitive beamforming (PCB). Lastly, computer simulation results show that the three suboptimal schemes can approach the secrecy capacity well under certain conditions.
In the Cognitive Radio Network (CRN) with multiple multi-antenna eavesdroppers, to make the system security rate maximum, secure communication over the physical layer that is subjected to the interference power constraints at the Primary Users (PU) is provided by designing the transmit covariance optimization of Secondary User Transmitter (SU-Tx).When?the?Channel State?Information (CSI) is known, the properties of the matrices and Charnes-Cooper transformation are used, the non-convex function is converted to a Semi-Definite Programming (SDP) to get the optimization scheme of SU-Tx. Simulation results show that compared with the existing sub-optimal transmission designs, the proposed method improves the secrecy rate and has more advantages on the complexity.
In this paper, we consider multiple-input single-output multi-eavesdropper cognitive radio networks (MISOME-CRNs), where a secondary user (SU) aims to transmit confidential information to a legitimate SU receiver in the presence of a primary user (PU) and a multi-antenna passive eavesdropper in fast fading environments. For this system setting, we study beamforming with artificial noise (AN) for the SU to achieve confidential communications. We consider designing an AN-assisted optimal beamforming scheme, denoted cognitive beamforming (CB), which maximizes the ergodic secrecy rate. Moreover, we propose two suboptimal beamforming schemes, namely, scaled beamforming (SB) and projected beamforming (PB). We develop an analytical framework to assess the performance of the proposed schemes in a unified manner. First, we analyze the achievable ergodic secrecy rate of the three schemes. Second, we derive the optimal power allocation for the information and AN signals that maximizes the achievable ergodic secrecy rate in the large-antenna regime. Third, we study the performance of the three schemes in terms of the secrecy outage probability. Using numerical simulations, we validate our analytical results and show that CB achieves the best performance among the three proposed schemes. In addition, we provide insights into the effect of various system parameters on the secrecy performance. In particular, we show that the interference threshold at the PU plays an important role in the beamforming design.
The problem of optimal transmitter design to achieve the physical layer security for multi-antenna cognitive radio network (CRN) in the presence of an eavesdropper receiver (ED-Rx) is considered in this paper. The purpose of this problem is to maximize the security rate of the secondary user transmitter (SU-Tx) under the constraints of secondary user transmit power and interference limit at primary user (PU). In this paper, we propose an algorithm based on the Lagrange duality to solve this optimization problem. Compared with the existing algorithm, our proposed algorithm avoids several coarse conversions and obtains more rigorous formulas. Simulation results demonstrate that the performance of our algorithm is better than the existing algorithm distinctly when the channel covariance estimate errors stay at a high level.
This paper studies the robust beamforming design problem for a multiple-input single-output (MISO) secrecy channel with a single-antenna eavesdropper. Due to the illegal nature, the eavesdropper may try to hide itself from being caught; thus, it could be difficult for the secrecy transmitter (S-Tx) to obtain accurate channel state information (CSI) of the eavesdropping link between S-Tx and the eavesdropper. Assuming that the CSI of the eavesdropping link belongs to a known uncertain set, this paper designs the optimal transmit strategy for the secrecy user to maximize the transmit rate under the condition that the eavesdropper cannot decode the secrecy message for all possible channel realizations of the eavesdropping link. This robust design problem is non-convex and cannot be solved by existing algorithms in the literature. By exploiting the relationship between the secrecy MISO channel and the cognitive radio (CR) MISO channel, this problem is transformed into a robust CR beamforming design problem, which can be solved efficiently by the interior point method. Numerical examples are provided to illustrate the effectiveness of the proposed algorithm.
In recent years there has been growing interest in study of multi-antenna transmit designs for providing secure communication over the physical layer. This paper considers the scenario of an intended multi-input single-output channel overheard by multiple multi-antenna eavesdroppers. Specifically, we address the transmit covariance optimization for secrecy-rate maximization (SRM) of that scenario. The challenge of this problem is that it is a nonconvex optimization problem. This paper shows that the SRM problem can actually be solved in a convex and tractable fashion, by recasting the SRM problem as a semidefinite program (SDP). The SRM problem we solve is under the premise of perfect channel state information (CSI). This paper also deals with the imperfect CSI case. We consider a worst-case robust SRM formulation under spherical CSI uncertainties, and we develop an optimal solution to it, again via SDP. Moreover, our analysis reveals that transmit beamforming is generally the optimal transmit strategy for SRM of the considered scenario, for both the perfect and imperfect CSI cases. Simulation results are provided to illustrate the secrecy-rate performance gains of the proposed SDP solutions compared to some suboptimal transmit designs.