This paper describes a new approach to the problem of interception of wireless communication channels between the legitimate users. Physical PHY Layer Security (PLS) is new topic enhancing the secrecy performance of a Multi-User Multiple-Input-Multiple-Output (MU-MIMO) system for wireless communication from a single base-station to many users. Beamforming techniques such as "Pre-Maximum Ratio Combining (P-MRC) and Pre-Equal Gain Combining (P-EGC)" with assumption of perfect Channel State Information CSI is considered in order to achieve the perfect secure transmission between legitimate users. Along with beamforming, Artificial Noise (AN) is a technology that is being studied. The plotted achievable worst-case of secrecy rate down to the best secrecy rate value (threshold of secrecy rate) versus the power allocation fractions (The power splitting factor). The achieved threshold of secrecy rates for the implemented MU-MIMO were used by Matched Filter (MF) beamforming schemes (P-MRC) and (P-EGC) and suggested that the (P-MRC) is considered as an optimal beamforming technique in order to achieve a best secrecy rate or best threshold of secrecy rate for a nearest Information User (IU) to the Eavesdropper Eve.
This paper describes a new approach to the problem of interception of wireless communication channels between the legitimate users. Physical PHY Layer Security (PLS) is new topic enhancing the secrecy performance of a Multi-User Multiple-Input-Multiple-Output (MU-MIMO) system for wireless communication from a single base-station to many users. Beamforming techniques such as "Pre-Maximum Ratio Combining (P-MRC) and Pre-Equal Gain Combining (P-EGC)" with assumption of perfect Channel State Information CSI is considered in order to achieve the perfect secure transmission between legitimate users. Along with beamforming, Artificial Noise (AN) is a technology that is being studied. The plotted achievable worst-case of secrecy rate down to the best secrecy rate value (threshold of secrecy rate) versus the power allocation fractions (The power splitting factor). The achieved threshold of secrecy rates for the implemented MU-MIMO were used by Matched Filter (MF) beamforming schemes (P-MRC) and (P-EGC) and suggested that the (P-MRC) is considered as an optimal beamforming technique in order to achieve a best secrecy rate or best threshold of secrecy rate for a nearest Information User (IU) to the Eavesdropper Eve.
Recently, wireless security has been highlighted as one of the most important techniques for 6G mobile communication systems. Many researchers have tried to improve the Physical-Layer Security (PLS) performance such as Secrecy Outage Probability (SOP) and Secrecy Energy-Efficiency (SEE). The SOP indicates the outage probability that the data transmission between legitimate devices does not guarantee a certain reliability level, and the SEE is defined as the ratio between the achievable secrecy-rate and the consumed transmit power. In this paper, we consider a Multi-User Multi-Input Single-Output (MU-MISO) downlink cellular network where a legitimate Base Station (BS) equipped with multiple transmit antennas sends secure information to multiple legitimate Mobile Stations (MSs), and multiple potential eavesdroppers (EVEs) equipped with a single receive antenna try to eavesdrop on this information. Each potential EVE tries to intercept the secure information, i.e., the private message, from the legitimate BS to legitimate MSs with a certain eavesdropping probability. To securely receive the private information, each legitimate MS feeds back its effective channel gain to the legitimate BS only when the effective channel gain is higher than a certain threshold, i.e., the legitimate MSs adopt an Opportunistic Feedback (OF) strategy. In such eavesdropping channels, both SOP and SEE are analyzed as performance measures of PLS and their closed-form expressions are derived mathematically. Based on the analytical results, it is shown that the SOP of the OF strategy approaches that of a Full Feedback (FF) strategy as the number of legitimate MSs or the number of antennas at the BS increases. Furthermore, the trade-off between SOP and SEE as a function of the channel feedback threshold in the OF strategy is investigated. The analytical results and related observations are verified by numerical simulations.
Traditional cryptographic encryption techniques at higher layers require a certain form of information sharing between the transmitter and the legitimate user to achieve security. Besides, it also assumes that the eavesdropper has an insufficient computational capability to decrypt the ciphertext without the shared information. However, traditional cryptographic encryption techniques may be insufficient or even not suit- able in wireless communication systems. Physical layer security (PLS) can enhance the security of wireless communications by leveraging the physical nature of wireless transmission. Thus, in this thesis, we study the PLS performance in emerging wireless transmission systems. The thesis consists of two main parts. We first consider the PLS design and analysis for ground-based networks em- ploying random unitary beamforming (RUB) scheme at the transmitter. With RUB technique, the transmitter serves multiple users with pre-designed beamforming vectors, selected using limited channel state information (CSI). We study multiple-input single-output single-eavesdropper (MISOSE) transmission system, multi-user multiple-input multiple-output single-eavesdropper (MU-MIMOSE) transmission system, and massive multiple-input multiple-output multiple-eavesdropper (massive MI- MOME) transmission system. The closed-form expressions of ergodic secrecy rate and the secrecy outage probability (SOP) for these transmission scenarios are derived. Besides, the effect of artificial noise (AN) on secrecy performance of RUB-based transmission is also investigated. Numerical results are presented to illustrate the trade-off between performance and complexity of the resulting PLS design. We then investigate the PLS design and analysis for unmanned aerial vehicle (UAV)-based networks. We first study the secrecy performance of UAV-assisted relaying transmission systems in the presence of a single ground eavesdropper. We derive the closed-form expressions of ergodic secrecy rate and intercept probability. When multiple aerial and ground eavesdroppers are located in the UAV-assisted relaying transmission system, directional beamforming technique is applied to enhance the secrecy performance. Assuming the most general κ-μ shadowed fading channel, the SOP performance is obtained in the closed-form expression. Exploiting the derived expressions, we investigate the impact of different parameters on secrecy performance. Besides, we utilize a deep learning approach in UAV-based network analysis. Numerical results show that our proposed deep learning approach can predict secrecy performance with high accuracy and short running time.
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 thesis, we study the physical layer security in downlink multi-user wireless networks. Traditionally, security has been addressed by cryptography at the higher layers of the communication stack. Security at the physical layer has been a major research topic in recent years. We study two different precoder designs alongside artificial noise (AN) to mitigate multi-user interference and deteriorate reception at the eavesdropper (Eve). We study the large scale analysis to calculate the secrecy sum-rate for these two cases and analyze the effect of AN on the system. First, we consider the worst case scenario, when eavesdropper's (Eve's) rate is not deteriorated by the interference caused by the legitimate users. Later, we investigate how interference from legitimate users would affect the large scale security sum rate. At the end, we assume more practical situation where the channel state information at the transmitter is not perfect due to feedback limitation and estimation error. We first study block diagonalization (BD) precoding. We derive the asymptotic secrecy sum-rate of BD for physical layer security in downlink multi-user wireless networks using artificial noise (AN). We first derive the secrecy sum-rate assuming that the channel of the eavesdropper is not known at the transmitter and derive the asymptotic secrecy sum-rate. Then we derive the optimum power allocation for asymptotic secrecy sum-rate. We design the system based on large scale analysis for different special cases. Simulation results show that the proposed precoders outperform channel inversion (CI) and regularized channel inversion (RCI) schemes at all SNRs. We also show that as the number of receive antennas of each user increases, the sum-rate gap between the proposed scheme and existing methods increases. We, then, study two methods of regularized block diagonalization (RBD) precoding using artificial noise (AN) for physical layer security in downlink multi-user MIMO wireless networks. We compare the complexity analysis of these two methods in terms of floating point operations per second (FLOPS). We derive the secrecy and asymptotic secrecy sum-rates for these schemes. We also derive closed form expressions for the asymptotic optimal power allocation to the AN signal and legitimate users. Simulations show RBD precoding outperform regularized channel inversion (RCI) in terms of secrecy sum-rate with a margin of 0.5 bits/s/Hz. Also, simulation results show our closed-form asymptotic secrecy sum-rates matches closely with the simulations for perfect and imperfect CSIT. We also study the effect of interference on BD precoding scheme. In the first two studies the worst case scenarios was considered and the effect of interference was not considered at the eavesdropper. We first derive the closed-form secrecy and asymptotic secrecy sum-rates for this scheme. Then, we derive the optimum power allocation. Using the derived optimum power allocation, we determine the conditions under which adding AN helps. We also investigate the optimum number of users, number of antennas at the eavesdropper, and the number of transmit antennas to fully study the conditions where using AN improves performance. We show that as the number of users increases or the number of receive antennas at the eavesdropper decreases, improved performance is achieved by allocating a smaller fraction of the total power to transmit the AN. The closed form expressions for the secrecy sum rate (SSR) and optimum power allocation closely match our simulation results. In Chapter 5, we study the effect of imperfect channel state information at the transmitter (CSIT) for each case studied in earlier chapters. We first study the effect of imperfect CSIT for BD precoding in both scenarios when interference does and does not exist at eavesdropper. We show that the imperfect CSI play the same role as interference for the desired users. Then, we study the effect of imperfect CSIT for RBD precoding when interference does not exist at eavesdropper. We show as channel estimation error increases, the secrecy sum-rate decreases. This is due to the fact that channel estimation error just affects the desired users' rate and has no effect on eavesdropper's performance. Finally, in the last chapter, we conclude our thesis and provide some road map for future--Author's abstract
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.
Physical layer security (PLS) has grown in popularity as it guarantees secure and reliable communication between wireless devices without restricting the ability of data analysts to eavesdrop. PLS benefits from the randomization property of the wireless channel, which improves immunity and protects against many dangers of information breaches from eavesdroppers. MIMO and Massive MIMO, which use numerous antennas at the transmitter and receiver ends, are fundamental technologies for improving efficiency in 5G and future network systems. The PLS still requires a significant amount of work before it can be employed in practical systems. The interception of eavesdroppers can be made difficult by adding artificial noise. This paper focuses on the physical layer security considering maximal ratio combining, and artificial noise with beamforming techniques to further enhance the secrecy rate. The proposed work demonstrates that the use of transmitter beamforming with artificial noise can significantly improve the degree of confidentiality of information being transmitted between a transmitter and an intended receiver while making it more difficult for eavesdroppers to intercept. The simulation results in terms of bit error rate show that the proposed method has a significant impact on the error rate performance of the eavesdropper.