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IET International Conference on Wireless, Mobile and Multimedia Networks (ICWMMN)

Optimal Secure Transmission with Artificial-noise-aided Beamforming in Multi-cell Networks

Sixue Shi, Shenghui Wang, Tong Wu, Tingling Chai, Lili Wan

Published Jan 1, 2017• 2 citations
Publisher

Abstract

Safe and reliable wireless transmission services are needed in multi-cell massive MIMO mobile communication networks. Physical layer security technology is effective to solve wireless networks transmission security issues. It uses the channel characteristics of wireless to encrypt information so as to improve confidentiality security of communication. Combined with multi-cell cooperation, this paper proposes optimal secure transmission with artificial-noise-aided beamforming, which applies base station selection, in multi-cell massive MIMO networks. In the proposed secure transmission scheme, the optimal base station among all cells is selected which assists generating artificial noise to deteriorate the channel quality of eavesdroppers. The multi-cell communication models under two different base station selections are considered and the lower bounds of the ergodic secrecy rate of the two selections are derived respectively. The genetic algorithm is utilized to optimize the power allocation by maximizing the lower bound of the ergodic secrecy rate. Simulation results show the effectiveness of the proposed transmission scheme.

DOI
10.1049/cp.2017.0592

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Safe and reliable wireless transmission services are needed in multi-cell massive MIMO mobile communication networks. Physical layer security technology is effective to solve wireless networks transmission security issues. It uses the channel characteristics of wireless to encrypt information so as to improve confidentiality security of communication. Combined with multi-cell cooperation, this paper proposes optimal secure transmission with artificial-noise-aided beamforming, which applies base station selection, in multi-cell massive MIMO networks. In the proposed secure transmission scheme, the optimal base station among all cells is selected which assists generating artificial noise to deteriorate the channel quality of eavesdroppers. The multi-cell communication models under two different base station selections are considered and the lower bounds of the ergodic secrecy rate of the two selections are derived respectively. The genetic algorithm is utilized to optimize the power allocation by maximizing the lower bound of the ergodic secrecy rate. Simulation results show the effectiveness of the proposed transmission scheme.
In this paper, we consider a multi-cell massive MIMO system with matched-filter precoding and artificial noise (AN) generation at the base station (BS) for secure downlink transmission in the presence of multi-antenna passive eavesdroppers. We derive two tight lower bounds for the achievable ergodic secrecy rate and a tight upper bound on the secrecy outage probability of the considered system. The analytical results are used to optimize the amount of power allocated for AN generation. Our results reveal that AN generation is not required in massive MIMO systems as long as the number of BS antennas is much larger than the number of eavesdropper antennas. However, as the number of eavesdropper antennas increases relative to the number of BS antennas, AN becomes beneficial and the amount of power optimally allocated to AN generation increases with the number of eavesdropper antennas.
In this paper, we consider secure communications in a multi-cell downlink multi-antenna system, where each multi-antenna base station (BS) sends confidential messages to one intended legitimate user (LU) with a passive multi-antenna eavesdropper trying to intercept the messages in this cell. To enhance the secure communications of the cell-edge users, the multiple BSs employ coordinated beamforming with the aid of artificial-noise (AN) beamforming. We conduct a mathematically rigorous secrecy performance analysis of the considered system and obtain new accurate closed-form expressions of a lower bound on the ergodic rate of each LU and an upper bound of the ergodic rate of each eavesdropper without assuming asymptotes for any system parameter (except for the “worst-case” scenario with zero noise power). Then, a lower bound on the ergodic secrecy rate (ESR) of each LU follows. Based on the derived analytical results, we propose a low-complexity algorithm to optimize the channel sate information (CSI) feedback bits allocation for the channels of target signal link and inter-cell interference links. Furthermore, we develop explicit sufficient conditions on the set of system parameters under which there are at least two BSs to coordinated secure transmission. Through both theoretical analysis and numerical results, we can verify that the obtained analytical lower bound on ESR of each LU as a function of the set of power allocation coefficients is generallyneither convex nor concave. Thus, we propose to employ some numerical method to find a sub-optimal power allocation solution. Finally, numerical results are also provided to validate our theoretical results and the proposed feedback bits and power allocation methods.
In this paper, we consider physical layer security provisioning in multi-cell massive multiple-input multiple-output (MIMO) systems. Specifically, we consider secure downlink transmission in a multi-cell massive MIMO system with matched-filter precoding and artificial noise (AN) generation at the base station (BS) in the presence of a passive multi-antenna eavesdropper. We investigate the resulting achievable ergodic secrecy rate and the secrecy outage probability for the cases of perfect training and pilot contamination. Thereby, we consider two different AN shaping matrices, namely, the conventional AN shaping matrix, where the AN is transmitted in the null space of the matrix formed by all user channels, and a random AN shaping matrix, which avoids the complexity associated with finding the null space of a large matrix. Our analytical and numerical results reveal that in multi-cell massive MIMO systems employing matched-filter precoding (1) AN generation is required to achieve a positive ergodic secrecy rate if the user and the eavesdropper experience the same path-loss, (2) even with AN generation secure transmission may not be possible if the number of eavesdropper antennas is too large and not enough power is allocated to channel estimation, (3) for a given fraction of power allocated to AN and a given number of users, in case of pilot contamination, the ergodic secrecy rate is not a monotonically increasing function of the number of BS antennas, and (4) random AN shaping matrices provide a favourable performance/complexity tradeoff and are an attractive alternative to conventional AN shaping matrices.
For the single-cell massive multiple-input multiple-output (MIMO) downlink transmission, we investigate an artificial noise (AN) assisted secure transmission strategy where the base station has only access to statistical channel state information (CSI) of the legitimate user terminals and the eavesdropper. By maximizing a lower bound of the ergodic secrecy sum rate, we figure out the eigenvectors of the optimal secrecy signal and AN transmit covariance matrices in the closed-form. Notably, such a solution reveals that it is more favorable to transmit both the secrecy signals and the AN in the beam domain, by which we translate the original problem into a simpler power allocation problem in the beam domain. Building on the approaches of sequential optimization and the deterministic equivalent, we further propose an iterative algorithm for power allocation with guaranteed convergence to a local optimum. Numerical results show the superior performance of the proposed approach compared with the traditional one without AN.
With the development of wireless communication, one of the critical demands is secure transmission especially in downlink communication. In this paper, downlink secure transmission in two-cell base station cooperation multiuser network is studied. The two base stations are fully cooperated and an artificial noise (AN) is added to degrade the eavesdropper(EVE)'s channel. Perfect channel state information (CSI) of all users is known by the base stations and regularized channel inversion (RCI) precoding is used. The close form expression of secrecy sum rate is derived in the large system regime. The regularization parameter and the power allocation ratio are optimized based on larger system regime results. From analysis, base station cooperation network could serve more users per cell in secure transmission than single cell network. The numerical results show large system regime results are accurate even in finite case. In the simulation figures, the analytical optimal results can well approximate to the simulation results.
In this letter, we consider the problem of secure communication in the downlink of a multi-cell multiple-input multiple-output (MIMO) system under imperfect channel state information (CSI) at the base stations (BSs). The passive eavesdroppers are considered, whose CSI are unavailable at the BSs. Coordinated Beamforming (CBf) and artificial noise (AN) are employed for secrecy enhancement. Based on regularized channel inversion (RCI) precoding, we derive a novel closed-form expression of secrecy sum-rate in the large-system regime. Based on the result, the regularization parameter and the power allocation ratio between the information signal and AN are optimized. Compared to the perfect CSI case, it shows that the channel estimation error can drastically reduce the secrecy sum-rate, and more power needs to be allocated for AN when the channel estimation error grows larger. The analytical results are validated with the finite-size system by simulation.