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IEEE Transactions on Wireless Communications

Weighted Sum Rate Maximization of MIMO Broadcast and Interference Channels With Confidential Messages

Daeyoung Park

Published Oct 30, 2015• 29 citations
Publisher

Abstract

We consider two-user MIMO broadcast and interference channels in which confidential messages intended for each receiver are kept secret from the other receiver. The confidential secrecy rates are nonconvex functions of transmit covariance matrices, which makes it intractable to find optimal transmit covariance matrices analytically. In the MIMO broadcast channels, we prove the weighted secrecy sum rate maximization has zero duality gap and KKT conditions are necessary conditions for the optimal solution. We apply the block successive lower-bound maximization technique to nonconvex weighted secrecy sum rate maximization problems. We also derive numerical algorithms for MIMO interference channels and Gaussian wiretap channels with a cooperative jammer. Every limit point achieved by the proposed algorithms is a local optimal solution that satisfies the KKT conditions. Numerical results show that the proposed algorithms outperform existing suboptimal algorithms in terms of secrecy rates.

DOI
10.1109/twc.2015.2496236

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We consider two-user MIMO broadcast and interference channels in which confidential messages intended for each receiver are kept secret from the other receiver. The confidential secrecy rates are nonconvex functions of transmit covariance matrices, which makes it intractable to find optimal transmit covariance matrices analytically. In the MIMO broadcast channels, we prove the weighted secrecy sum rate maximization has zero duality gap and KKT conditions are necessary conditions for the optimal solution. We apply the block successive lower-bound maximization technique to nonconvex weighted secrecy sum rate maximization problems. We also derive numerical algorithms for MIMO interference channels and Gaussian wiretap channels with a cooperative jammer. Every limit point achieved by the proposed algorithms is a local optimal solution that satisfies the KKT conditions. Numerical results show that the proposed algorithms outperform existing suboptimal algorithms in terms of secrecy rates.
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This paper considers the problem of secret communication over a two-receiver multiple-input multiple-output (MIMO) Gaussian broadcast channel. The transmitter has two independent messages, each of which is intended for one of the receivers but needs to be kept asymptotically perfectly secret from the other. It is shown that, surprisingly, under a matrix power constraint both messages can be simultaneously transmitted at their respective maximal secrecy rates. To prove this result, the MIMO Gaussian wiretap channel is revisited and a new characterization of its secrecy capacity is provided via a new coding scheme that uses artificial noise (a prefix channel) and random binning.
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This paper considers the problem of secret communication over a two-receiver multiple-input multiple-output (MIMO) Gaussian broadcast channel. The transmitter has two independent messages, each of which is intended for one of the receivers but needs to be kept asymptotically perfectly secret from the other. It is shown that, surprisingly, under a matrix power constraint, both messages can be simultaneously transmitted at their respective maximal secrecy rates. To prove this result, the MIMO Gaussian wiretap channel is revisited and a new characterization of its secrecy capacity is provided via a new coding scheme that uses artificial noise (an additive prefix channel) and random binning.
Secure communication over two related multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) networks is investigated. Both networks consist of two legitimate (internal) users and an eavesdropper (external user). In one network, in addition to the external eavesdropper, one of the internal users is also seen as an eavesdropper to the other internal user, resulting in layered confidentiality. The secrecy capacity expressions of these networks are composed of nonconvex functions of transmit covariance matrices, which makes it intractable to find optimal transmit covariance matrices. To overcome this challenge, we form a weighted sum-rate maximization problem for each network and apply the block successive maximization method. This method updates the primal variable blocks successively by maximizing local lower-bounds of the original problem, followed by an update for the dual variable in a closed form. The solutions for these problems design covariance matrices corresponding to the transmitted messages such that they are transmitted securely and reliably. Numerical results illustrate the efficacy of the proposed signaling design for both MIMO-NOMA networks.
We study the optimality of linear precoding for the two-receiver multiple-input multiple-output (MIMO) Gaussian broadcast channel (BC) with confidential messages. Secret dirty-paper coding (S-DPC) is optimal under an input covariance constraint, but there is no computable secrecy capacity expression for the general MIMO case under an average power constraint. In principle, for this case, the secrecy capacity region could be found through an exhaustive search over the set of all possible matrix power constraints. Clearly, this search, coupled with the complexity of dirty-paper encoding and decoding, motivates the consideration of low complexity linear precoding as an alternative. We prove that for a two-user MIMO Gaussian BC under an input covariance constraint, linear precoding is optimal and achieves the same secrecy rate region as S-DPC if the input covariance constraint satisfies a specific condition, and we characterize the corresponding optimal linear precoders. We then use this result to derive a closed-form sub-optimal algorithm based on linear precoding for an average power constraint. Numerical results indicate that the secrecy rate region achieved by this algorithm is close to that obtained by the optimal S-DPC approach with a search over all suitable input covariance matrices.