In massive multiple-input multiple-output (MIMO) systems, idle users may passively overhear the signal transmitted to the intended user, known as internal eavesdroppers. In order to improve the secrecy performance, artificial noise (AN) is used jointly with maximum ratio transmission (MRT) precoding. Since the idle users can be anywhere in the cell, we investigate the secrecy outage probability for the legitimate user by taking an expectation over the positions of all internal eavesdroppers. Furthermore, according to the secrecy performance of the legitimate user in the given location, we define a new concept Secrecy Area centered on the base station (BS) where all the legitimate users satisfy the secrecy quality-of-service (QoS) requirements i.e. secrecy outage probability. Then, in order to achieve the maximum Secrecy Area under the given secrecy QoS requirements, we derive the optimal power allocation factor for AN, which is irrelevant to the channel state information (CSI) of both the legitimate user and the eavesdropper. The analytical and simulation results show that, by AN-assisted MRT precoding, the secrecy performance is significantly improved and the Secrecy Area can be efficiently enlarged with a modest increase of the transmit power.
In massive multiple-input multiple-output (MIMO) systems, idle users may passively overhear the signal transmitted to the intended user, known as internal eavesdroppers. In order to improve the secrecy performance, artificial noise (AN) is used jointly with maximum ratio transmission (MRT) precoding. Since the idle users can be anywhere in the cell, we investigate the secrecy outage probability for the legitimate user by taking an expectation over the positions of all internal eavesdroppers. Furthermore, according to the secrecy performance of the legitimate user in the given location, we define a new concept Secrecy Area centered on the base station (BS) where all the legitimate users satisfy the secrecy quality-of-service (QoS) requirements i.e. secrecy outage probability. Then, in order to achieve the maximum Secrecy Area under the given secrecy QoS requirements, we derive the optimal power allocation factor for AN, which is irrelevant to the channel state information (CSI) of both the legitimate user and the eavesdropper. The analytical and simulation results show that, by AN-assisted MRT precoding, the secrecy performance is significantly improved and the Secrecy Area can be efficiently enlarged with a modest increase of the transmit power.
The secrecy performance of forward link multi-user massive multiple-input multiple-output (MIMO) system is investigated in this paper. The base station (BS) equipped with a large number of transmit antennas sends mutually independent datas to multiple single-antenna legitimate users simultaneously. A passive multi-antenna eavesdropper is placed in the scenario to intercept the signals. We consider the case that the number of legitimate users and eavesdropper antennas increases proportionally with the number of BS antennas. Maximum ratio transmission (MRT) is used as linear precoder at the BS. Lower bounds on the ergodic achievable rate of legitimate users and upper bounds of the eavesdropper are derived. By minimizing the upper bounds on the achievable rates of the eavesdropper while satisfying the rate constraints of legitimate users, we present the corresponding optimal radiated power scaling (RPS) factor. In the limit of an infinite number of BS antennas, we prove that the optimal RPS factor converge to a different constant limit with that of the case in which the number of legitimate users and eavesdropper antennas is finite. We show that when the number of BS antennas grows large, the secrecy performance is mainly determined by the ratios between the number of BS antennas, legitimate users and eavesdropper antennas. A number of simulation results are presented to visualize the analysis.
This paper considers a massive MIMO network that includes one multiple-antenna base station, one multiple-antenna eavesdropper, and K single-antenna users. The eavesdropper operates in passive mode and tries to overhear the confidential information from one of the users in the down-link transmission. In order to secure the confidential information, two artificial noise (AN)-aiding schemes are proposed. In the first scheme, AN is injected into the downlink training signals to prevent the eavesdropper from obtaining the correct channel state information of the eavesdropping link. In the second scheme, AN is deployed in both downlink training phase and payload data transmission phase to further degrade the eavesdropping channel. Analytical expressions and tight approximations of the achievable secrecy rate of the considered systems are derived with taking imperfect channel estimation and two types of precoding, i.e., maximum-ratio-transmission and zero-forcing, into consideration. Optimization algorithms for power allocation are proposed to enhance the secrecy performance of the proposed AN-aiding schemes. The results reveal that deploying AN in the downlink training phase of massive MIMO networks does not affect the downlink channel estimation process at users while enabling the system to suppress the downlink channel estimation process at eavesdropper. As a consequence, the proposed AN-aided schemes improve the system performance significantly. Furthermore, implementing AN in both phases allows the considered system having a flexible solution to maximize its secrecy performance at the price of higher complexity.
In this study, we consider the physical layer security in the downlink of a Massive MIMO system employing one-bit quantization at the base station (BS). We assume an active eavesdropper that attempts to spoiling the channel estimation acquisition at the BS for a legitimate user, whereas overhearing on downlink transmission. We consider the two most widespread methods for degrading the eavesdropper's channel, the nullspace artificial noise (NS-AN) and random artificial noise (R-AN). Then, we present a lower bound on the secrecy rate and asymptotic performance, considering zero-forcing beamforming (ZF-BF) and maximum-ratio transmission beamforming (MRT-BF). Our results reveal that even when the eavesdropper is close enough to the intercepted user, a positive secrecy rate -which tends to saturation with increasing the number of BS antennas N-is possible, as long as the transmit power of eavesdropper is less than that of the legitimate user during channel training. We show that ZF-BF with NS-AN provides the best performance. It is found that MRT-BF and ZF-BF are equivalent in the asymptotic limit of N and hence the artificial noise technique is the performance indicator. Moreover, we study the impact of power-scaling law on the secrecy rate. When the transmit power of BS is reduced proportional to 1/N, the performance is independent of artificial noise asymptotically and hence the beamforming technique is the performance indicator. In addition, when the BS's power is reduced proportional to 1/√N, all combinations of beamforming and artificial noise schemes are equally likely asymptotically, independent of quantization noise. We present various numerical results to corroborate our analysis.
Massive Multiple-Input Multiple-Output (MIMO) has become a crucial enabling technology for 5G and beyond, providing previously unheard-of increases in energy and spectrum efficiency. It is still difficult to guarantee secure communication in these systems, particularly when it comes to passive eavesdroppers whose base station is unaware of their channel state information. By taking advantage of the inherent randomness of wireless channels, Physical Layer Security (PLS) offers a promising paradigm; however, its efficacy in massive MIMO is heavily reliant on resource allocation and transmission strategies. In this work, the performance of secure transmission schemes, such as Maximum Ratio Transmission (MRT), Zero-Forcing (ZF), and Artificial Noise (AN)-aided beamforming, is examined when passive eavesdroppers are present. This work will use extensive Monte Carlo simulations to assess important performance metrics such as energy efficiency, secrecy outage probability, and secrecy sum rate under different system parameters (e.g., number of antennas, Signal-to-Noise Ratio (SNR), power allocation). The results aim to provide comparative insight into the strengths and limitations of different PLS strategies and to highlight open research directions to design scalable, energy-efficient, and robust secure transmission techniques in future 6G networks.
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.
In this paper, we consider physical layer security provisioning in multicell massive multiple-input-multiple-output (MIMO) systems. Specifically, we consider secure downlink transmission in a multicell massive MIMO system with matched-filter precoding and artificial noise (AN) generation at the base station (BS) in the presence of a passive multiantenna 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 the following, in multicell 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 favorable performance/complexity tradeoff and are an attractive alternative to conventional AN shaping matrices.