Low-resolution converters reduce the power consumption of wireless devices and help enable large energy-efficient arrays. In this letter, we evaluate the secrecy rate for the extreme case of 1-bit single-user multiple-input multiple-output systems following two signaling approaches. In the first method, the system uses discrete signaling. In the second, the system combines Gaussian signaling with artificial noise alongside power allocation. In the first case, we give a closed-form expression of the secrecy rate and propose an algorithm that provides near-optimal results for low signal-to-noise ratios (SNRs). In the second scenario, depending on the channel state information, we suggest different precoding plans and derive a secrecy rate lower bound. At low SNR, power is allocated to the main signal. Only at high SNR is optimal power allocation effective. Moreover, knowing the eavesdropper channel greatly improves the system’s secrecy.
Low-resolution converters reduce the power consumption of wireless devices and help enable large energy-efficient arrays. In this letter, we evaluate the secrecy rate for the extreme case of 1-bit single-user multiple-input multiple-output systems following two signaling approaches. In the first method, the system uses discrete signaling. In the second, the system combines Gaussian signaling with artificial noise alongside power allocation. In the first case, we give a closed-form expression of the secrecy rate and propose an algorithm that provides near-optimal results for low signal-to-noise ratios (SNRs). In the second scenario, depending on the channel state information, we suggest different precoding plans and derive a secrecy rate lower bound. At low SNR, power is allocated to the main signal. Only at high SNR is optimal power allocation effective. Moreover, knowing the eavesdropper channel greatly improves the system’s secrecy.
In this paper, we investigate secure transmission in a massive multiple-input multiple-output system adopting low-resolution digital-to-analog converters (DACs). Artificial noise (AN) is deliberately transmitted simultaneously with the confidential signals to degrade the eavesdropper's channel quality. By applying the Bussgang theorem, a DAC quantization model is developed which facilitates the analysis of the asymptotic achievable secrecy rate. Interestingly, for a fixed power allocation factor φ, low-resolution DACs typically result in a secrecy rate loss, but in certain cases, they provide superior performance, e.g., at low signal-to-noise ratio (SNR). Specifically, we derive a closed-form SNR threshold which determines whether low-resolution or high-resolution DACs are preferable for improving the secrecy rate. Furthermore, a closed-form expression for the optimal φ is derived. With AN generated in the null-space of the user channel and the optimal φ, low-resolution DACs inevitably cause secrecy rate loss. On the other hand, for random AN with the optimal φ, the secrecy rate is hardly affected by the DAC resolution because the negative impact of the quantization noise can be compensated by reducing the AN power. All the derived analytical results are verified by numerical simulations.
This paper investigates the power allocation problem for artificial noise (AN) secure precoding systems, and proposes closed-form solutions for maximizing the achievable secrecy rate. It is assumed that the transmitter knows the full channel information at the legitimate receiver, and knows only the statistics of the channel information at the eavesdropper. Lower bounds are derived for the secrecy rates in multiple-input single-output channels with single or multiple eavesdroppers and multiple-input multiple-output channels with multiple eavesdroppers. When the number of transmit antennas is sufficiently large, the bounds are tight, and closed-form solutions can be derived from these bounds. The analytical results suggest simple and yet informative solutions as follows: Let the numbers of receive antennas at the legitimate receiver and at the eavesdropper beNrandNr,e, respectively. The system should distributeNr,e/(Nr+Nr,e)of the power to AN in the high SNR regime, and distribute zero power to AN in the low SNR regime; the rate loss due to the eavesdropper is−Nrlog(Nr/(Nr+Nr,e))−Nr,elog(Nr,e/(Nr+Nr,e))bits/sec/Hz in the high SNR regime and nearly negligible in the low SNR regime. The derived results also show that equal power and water-filling power allocations lead to similar solutions and rate loss. Simulation results corroborate the theoretical results.
In this paper we study the secrecy performance of a downlink massive multiple-input multiple-output (MIMO) system in the presence of pilot spoofing attack (PSA). Specifically, the base station (BS), which is equipped with low-resolution analog-to-digital converters (ADCs) and digital-to-analog converters (DACs), exploits the low-complexity random artificial noise (AN) to improve secrecy. With the aid of the additive quantization noise model, the ergodic secrecy rate is derived. Based on the derived results, we study the impact of ADCs' and DACs' resolutions on the secrecy performance for the two different scenarios: the scenarios with and without the knowledge of the PSA power. The optimal power allocation parameter, which allocates power between the information-bearing signal and AN, is derived for the scenario with the knowledge of the PSA power. For ADCs, our theoretical results indicate that high-resolution ADCs are always favorable for improving secrecy, regardless of the availability of the PSA power. However, the impact of DACs' resolution is related to the knowledge of the PSA power. For the scenario without the PSA power, enhancing the resolution of DACs does not necessarily improve the secrecy performance due to the inappropriate power allocation. For the scenario with the PSA power, DACs with different resolutions can achieve the same ergodic secrecy rate in most cases, since the optimal power allocation can make a balance between mitigating the rate loss due to coarse quantization and injecting AN for anti-eavesdropping. Only in the case where the PSA power is small, high-resolution DACs achieve a higher ergodic secrecy rate. Finally, we propose a PSA detection method and study the effect of low-resolution ADCs on the detection performance. It is found that the resolution of ADCs has little effect on the performance of PSA detection.
Since the requirement of secure transmission for massive multiple-input–multiple-output (mIMO) is high, we consider a secure massive MIMO system in presence of multiple digital to analog converters (DACs). We deal with complicated performance analysis of the proposed system including a base station, a legitimate user, and an eavesdropper while these nodes are equipped with multiple antennas. In particular, we intend to present the closed-form expression for the ergodic secrecy rate of the system and also calculate the optimal power allocation for better performance gain. The simulation analysis shows that quantization bits, transmit signal to noise ratio at the base station, and power allocation plays a major role in enhancing the performance of the system.
In this letter, the performance of a secure massive multiple-input multiple-output (MIMO) system adopting low-resolution digital-to-analog converters (DACs) is analyzed over spatially correlated wireless channels. A tight lower bound for the achievable secrecy rate is derived with artificial noise (AN) transmitted in the null space of the user channels. Using the analytical results, the impact of spatial correlation on the secrecy rate is explicitly evaluated in the presence of low-resolution DACs. The analytical observations reveal that using low-resolution DACs can be beneficial to the secrecy performance compared with ideal DACs, when the channels are strongly correlated and optimal power allocation is not employed.
At present, there has been a large amount of research on secrecy rate optimization. However, the reliability analysis of secure transmission is equally important although relatively less attention has been dedicated to. Therefore, this paper proposes a secure transmission method with artificial noise for the physical layer security issues in the transmission process of Multiple Input Multiple Output (MIMO) wireless communication systems. Firstly, we establish an artificial noise assisted MIMO systems model. Then, the channel state information (CSI) matrix is subjected to singular value decomposition to obtain the reasonable precoding and artificial noise matrices. Finally, the impact of artificial noise on the bit error rate performance of potential eavesdropper is analyzed, and based on the analysis, the problem of maximizing the system secrecy rate is established. The concave-convex procedure (CCCP) method is used to obtain the optimal power allocation, which significantly improves the security of MIMO systems. The simulation results show that using the null space of CSI matrix and artificial noise for signal encryption effectively improves the bit error rate of potential eavesdropping nodes. In addition, the secrecy rate obtained by the CCCP algorithm is consistent with the performance obtained by the particle swarm optimization algorithm, which verifies the effectiveness of the proposed algorithm.