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IEEE Vehicular Technology Conference

Improving MIMO Secrecy Rate through Efficient Power Allocation

S Jyothsna, Lakshmi Narasimhan Theagarajan

Published Sep 1, 2022• 3 citations
Publisher

Abstract

We study the problem of maximizing the secrecy capacity in multiple input multiple output (MIMO) communication systems in the presence of an eavesdropper using optimal power allocation. One of the key bottlenecks arise in identifying the appropriate spatial streams to securely transmit data and the corresponding transmit powers to maximize capacity. We employ the generalized singular value decomposition (GSVD) technique to identify these spatial streams and propose a power allocation scheme over these spatial streams. We also present an upper bound for the maximum achievable secrecy rate under certain conditions. We show that the proposed power allocation technique not only achieves better secrecy, but also converges to the upper bound faster than those in the literature.

DOI
10.1109/vtc2022-fall57202.2022.10012982

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We study the problem of maximizing the secrecy capacity in multiple input multiple output (MIMO) communication systems in the presence of an eavesdropper using optimal power allocation. One of the key bottlenecks arise in identifying the appropriate spatial streams to securely transmit data and the corresponding transmit powers to maximize capacity. We employ the generalized singular value decomposition (GSVD) technique to identify these spatial streams and propose a power allocation scheme over these spatial streams. We also present an upper bound for the maximum achievable secrecy rate under certain conditions. We show that the proposed power allocation technique not only achieves better secrecy, but also converges to the upper bound faster than those in the literature.
This paper considers a multiple-input multiple-output (MIMO) Gaussian wiretap channel model, where there exists a transmitter, a legitimate receiver and an eavesdropper, each equipped with multiple antennas. Perfect secrecy is achieved when the transmitter and the legitimate receiver can communicate at some positive rate, while ensuring that the eavesdropper gets zero bits of information. In this paper, the perfect secrecy rate of the multiple antenna MIMO wiretap channel is maximized for arbitrary numbers of antennas under the assumption that the transmitter performs beamforming based on the generalized singular value decomposition (GSVD). More precisely, the optimal allocation of power for the GSVD-based precoder that maximizes the achievable secrecy rate is derived. Numerical results are presented to illustrate that the achievable secrecy rate of the GSVD-based precoding approach is nearly identical to that of the optimal scheme.
This paper considers a multiple-input multiple-output (MIMO) Gaussian wiretap channel model, where there exists a transmitter, a legitimate receiver and an eavesdropper, each equipped with multiple antennas. Perfect secrecy is achieved when the transmitter and the legitimate receiver can communicate at some positive rate, while ensuring that the eavesdropper gets zero bits of information. In this paper, the perfect secrecy capacity of the multiple antenna MIMO wiretap channel is found for aribtrary numbers of antennas under the assumption that the transmitter performs beamforming based on the generalized singular value decomposition (GSVD). More precisely, the optimal allocation of power for the GSVD-based precoder that achieves the secrecy capacity is derived. This solution is shown to have several advantages over prior work that considered secrecy capacity for the general MIMO Gaussian wiretap channel under a high SNR assumption. Numerical results are presented to illustrate the proposed theoretical findings.
A Gaussian multiple-input multiple-output wiretap channel in which the eavesdropper and legitimate receiver are equipped with arbitrary numbers of antennas and the transmitter has two antennas is studied in this paper. The input covariance matrix that achieves the secrecy capacity is determined. In particular, it is shown that the secrecy capacity of this channel can be achieved by linear precoding. Precoding and power allocation schemes that maximize the achievable secrecy rate, and thus achieve the secrecy capacity, are developed. The secrecy capacity is then compared with the achievable secrecy rate of generalized singular value decomposition (GSVD)-based precoding, which is the best previously proposed technique for this problem. Numerical results demonstrate that substantial gain can be obtained in secrecy rate between the proposed and GSVD-based precodings.
A Gaussian multiple-input multiple-output wiretap channel in which the eavesdropper and legitimate receiver are equipped with arbitrary numbers of antennas and the transmitter has two antennas is studied in this paper. It is shown that the secrecy capacity of this channel can be achieved by linear precoding. The optimal precoding and power allocation schemes achieving the secrecy capacity are developed subsequently, and the secrecy capacity is compared with the generalized singular value decomposition (GSVD)-based precoding, which is the best previously proposed precoding for this problem. Numerical results show that substantial gain can be obtained in secrecy rate between the proposed and GSVD-based precodings.
To improve the achievable secrecy rate in MIMO wiretap channel,a cooperative jamming strategy based on generalized singular value decomposition(GSVD) is proposed.Beamforming based on GSVD is employed both at the source node and helper node.The source node sends messages,while the helper transmits jamming signals independent of the source messages.The jamming signal is treated as noise at both the intended node and the eavesdropper node.Furthermore,joint optimal power allocation algorithm is designed between the source and the helper to maximize the achievable secrecy rate,under total power constraints.Compared with the existing optimal non-cooperative scheme,the numerical results demonstrated that the proposed strategy achieves a higher achievable secrecy rate in the high SNR.
In this paper, we consider the problem of power allocation in MIMO wiretap channel for secrecy in the presence of multiple eavesdroppers. Perfect knowledge of the destination channel state information (CSI) and only the statistical knowledge of the eavesdroppers CSI are assumed. We first consider the MIMO wiretap channel with Gaussian input. Using Jensen's inequality, we transform the secrecy rate max-min optimization problem to a single maximization problem. We use generalized singular value decomposition and transform the problem to a concave maximization problem which maximizes the sum secrecy rate of scalar wiretap channels subject to linear constraints on the transmit covariance matrix. We then consider the MIMO wiretap channel with finite-alphabet input. We show that the transmit covariance matrix obtained for the case of Gaussian input, when used in the MIMO wiretap channel with finite-alphabet input, can lead to zero secrecy rate at high transmit powers. We then propose a power allocation scheme with an additional power constraint which alleviates this secrecy rate loss problem, and gives non-zero secrecy rates at high transmit powers.