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IEEE Transactions on Communications

Confidential Broadcasting via Linear Precoding in Non-Homogeneous MIMO Multiuser Networks

Nan Yang, Giovanni Geraci, Jinhong Yuan, Robert Malaney

Published Jun 6, 2014• 35 citations
Publisher

Abstract

We propose linear precoding with power control to achieve confidential broadcasting in multi-input-multi-output multiuser networks such that the base station (BS) with Ntantennas securely broadcasts messages to K users with Nrantennas each. We focus on the practical non-homogeneous scenario where the distances between the BS and the users are not equal. We first design a linear precoder based on regularized channel inversion, and derive new channel-independent expressions for the achievable secrecy sum-rate in the large system regime. With the aid of these expressions, we examine the impact of user dispersion, Nt, and K on the secrecy sum-rate. We then propose a power reduction strategy and power allocation algorithms to increase the secrecy sum-rate. We demonstrate that our power reduction strategy increases the secrecy sum-rate at high signal-to-noise ratios. We also show the secrecy sum-rate advantage of optimal power allocation over equal power allocation. Furthermore, we consider channel correlation and derive an easy-to-compute expression for the secrecy sum-rate to examine its impact on the secrecy performance.

DOI
10.1109/tcomm.2014.2329471

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We propose linear precoding with power control to achieve confidential broadcasting in multi-input-multi-output multiuser networks such that the base station (BS) with Ntantennas securely broadcasts messages to K users with Nrantennas each. We focus on the practical non-homogeneous scenario where the distances between the BS and the users are not equal. We first design a linear precoder based on regularized channel inversion, and derive new channel-independent expressions for the achievable secrecy sum-rate in the large system regime. With the aid of these expressions, we examine the impact of user dispersion, Nt, and K on the secrecy sum-rate. We then propose a power reduction strategy and power allocation algorithms to increase the secrecy sum-rate. We demonstrate that our power reduction strategy increases the secrecy sum-rate at high signal-to-noise ratios. We also show the secrecy sum-rate advantage of optimal power allocation over equal power allocation. Furthermore, we consider channel correlation and derive an easy-to-compute expression for the secrecy sum-rate to examine its impact on the secrecy performance.
We design a linear precoder based on the principles of the generalized regularized channel inversion (RCI) precoder that achieves confidential broadcasting in a two-cell network. In each cell of the network, an N-antenna base station (BS) communicates with K single-antenna users. We consider coordinated beamforming where the BSs in the two cells do not share messages but the users in the two cells feed back their channel state information to both BSs. In the precoder design, we determine the optimal regularization parameter that maximizes the secrecy sum rate. To this end, we derive new channel-independent expressions for the secrecy sum rate in the large-system regime, where K and N approach infinity with a fixed ratio μ = K/N. Moreover, we propose a power-reduction strategy that significantly improves the secrecy sum rate at high transmit signal-to-noise ratios when μ is higher than 0.5.
In this paper, we propose a linear precoder for the downlink of a multi-user MIMO system with multiple users that potentially act as eavesdroppers. The proposed precoder is based on regularized channel inversion (RCI) with a regularization parameter α and power allocation vector chosen in such a way that the achievable secrecy sum-rate is maximized. We consider the worst-case scenario for the multi-user MIMO system, where the transmitter assumes users cooperate to eavesdrop on other users. We derive the achievable secrecy sum-rate and obtain the closed-form expression for the optimal regularization parameter αLSof the precoder using large-system analysis. We show that the RCI precoder with αLSoutperforms several other linear precoding schemes, and it achieves a secrecy sum-rate that has same scaling factor as the sum-rate achieved by the optimum RCI precoder without secrecy requirements. We propose a power allocation algorithm to maximize the secrecy sum-rate for fixed α. We then extend our algorithm to maximize the secrecy sum-rate by jointly optimizing α and the power allocation vector. The jointly optimized precoder outperforms RCI with αLSand equal power allocation by up to 20 percent at practical values of the signal-to-noise ratio and for 4 users and 4 transmit antennas.
In this paper, we study the performance of regularized channel inversion (RCI) precoding in large MISO broadcast channels with confidential messages (BCC). We obtain a deterministic approximation for the achiev-able secrecy sum-rate which is almost surely exact as the number of transmit antennas M and the number of users K grow to infinity in a fixed ratio β = K/M. We derive the optimal regularization parameter ξ and the optimal network load β that maximize the per-antenna secrecy sum-rate. We then propose a linear precoder based on RCI and power reduction (RCI-PR) that significantly increases the high-SNR secrecy sum-rate for 1 < β < 2. Our proposed precoder achieves a per-user secrecy rate which has the same high-SNR scaling factor as both the following upper bounds: (i) the rate of the optimum RCI precoder without secrecy requirements, and (ii) the secrecy capacity of a single-user system without interference. Furthermore, we obtain a deterministic approximation for the secrecy sum-rate achievable by RCI precoding in the presence of channel state information (CSI) error. We also analyze the performance of our proposed RCI-PR precoder with CSI error, and we determine how the error must scale with the SNR in order to maintain a given rate gap to the case with perfect CSI. Index Terms Physical layer security, broadcast channel, random matrix theory, linear precoding, multi-user systems. ar X iv
This paper studies secure precoding and power allocation for the two-user multiple-input multiple-output broadcast channel (MIMO-BC) with common and confidential messages. In this setting, the base station provides three services: A public service (a multicast or common message) to serve both users and two confidential messages to serve each of the two users secretly. The capacity region of this channel is characterized using secret dirty-paper coding. This scheme is, however, prohibitively complex for practical implementations. Under this scenario, a linear precoding method based on a power splitting scheme among the three services is proposed to optimize the corresponding rate equations in a separated manner by decomposing the MIMO-BC into two wiretap channels and a multicast channel. This approach leverages the wiretap channel solutions to design a precoder for the above channel. Particularly, alternative optimization is applied to the modified wiretap channels. For the multicast channel, analytical solutions together with a nonlinear random search are developed in different cases. Numerical results illustrate the efficacy of the proposed linear precoding and power allocation method. The proposed method also outperforms existing solutions over related problems such as the MIMO-BC with one confidential broadcasting and multicasting, etc.
In this paper, we consider the broadcast channel with confidential messages and external eavesdroppers (BCCE), where a multi-antenna base station simultaneously communicates to multiple potentially malicious users, in the presence of randomly located external eavesdroppers. Using the proposed model, we study the secrecy rates achievable with regularized channel inversion (RCI) precoding by performing a large-system analysis that combines results from stochastic geometry and random matrix theory, where the number of users K and the number of transmit antennas N both grow to infinity in a fixed ratio. We obtain explicit expressions for the probability of secrecy outage and an upper bound on the rate loss due to the presence of external eavesdroppers. We show that both these quantities scale as \fraclambda_esqrt{N} as the density of external eavesdroppers λ_e grows, irrespective of their collusion strategy. Furthermore, we derive a practical rule for the choice of the regularization parameter, which is agnostic of channel state information and location of eavesdroppers, and yet provides close to optimal performance.
Multiuser multiple-input multiple-output (MIMO) wireless techniques have received tremendous attention as a way to achieve high spectral efficiency in current mobile communication systems such as Long Term Evolution (LTE) [1]. Due to the broadcast nature of the physical medium, wireless multiuser communications are very susceptible to eavesdropping, and it is critical to secure the transmitted information. In this work, consider the broadcast channel with confidential messages and external eavesdroppers (BCCE), where a multi-antenna base station [2] simultaneously communicates to multiple potentially malicious users, in the presence of randomly located external eavesdroppers. The secrecy capacity is measured in terms of outage probability and provides a complete characterization of the maximum transmission rate at which the eavesdropper is unable to decode any information. Using the proposed model, the secrecy rates is achieved with regularized channel inversion (RCI) precoding and analyzed by performing a large-system analysis where the number of users K and the number of transmit antennas N both grow to infinity in a fixed ratio. Finally an explicit expression for the probability of secrecy outage and the system performance is analyzed in the presence of both colluding and non-colluding eavesdroppers.