Channel state information (CSI) at the transmitter is of importance to the performance of physical layer security based on multi-antenna networks. Specifically, CSI is not only beneficial to improve the capacity of the legitimate channel, but also can be used to degrade the performance of the eavesdropper channel. Thus, the secrecy rate increases accordingly. This letter focuses on the quantitative analysis of the ergodic secrecy sum-rate in terms of feedback amount of the CSI from the legitimate users in multiuser multi-antenna downlink networks. Furthermore, the asymptotic characteristics of the ergodic secrecy sum-rate in two extreme cases is investigated in some detail. Finally, our theoretical claims are confirmed by the numerical results.
Channel state information (CSI) at the transmitter is of importance to the performance of physical layer security based on multi-antenna networks. Specifically, CSI is not only beneficial to improve the capacity of the legitimate channel, but also can be used to degrade the performance of the eavesdropper channel. Thus, the secrecy rate increases accordingly. This letter focuses on the quantitative analysis of the ergodic secrecy sum-rate in terms of feedback amount of the CSI from the legitimate users in multiuser multi-antenna downlink networks. Furthermore, the asymptotic characteristics of the ergodic secrecy sum-rate in two extreme cases is investigated in some detail. Finally, our theoretical claims are confirmed by the numerical results.
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
This paper investigates the ergodic secrecy sum-rate for the downlink multiuser MIMO system with independent confidential messages, each of which is intended for one of the users and should keep secret from others. We adopt zero-forcing beamforming with limited channel state information (CSI) feedback at the transmitter, and derive the closed-form expression for the ergodic secrecy sum-rate. Moreover, we analyze some of its asymptotic characteristics, which provide guidance on secure transmission design. Finally, all theoretical results are validated by numerical simulations.
In this paper, we consider a multi-cell MISO downlink, where a multi-antenna base station (BS) sends messages to its intended user, while a passive eavesdropper tries to intercept the information in each cell. Physical layer security is employed in order to guarantee information security. Due to incomplete channel state information (CSI) at BSs, residue inter-cell interference exists even with coordinated beamforming, which exerts a great impact on the secrecy performance. In this paper, we conduct a unified performance analysis for physical layer security with incomplete CSI, and derives closed-form expressions of ergodic secrecy rate, secrecy outage probability, and interception probability, considering CSI estimation accuracy, transmit signal to noise ratio (SNR), and channel condition. We reveal some insights on the secrecy performance through asymptotic analysis. Furthermore, based on the derived theoretical results, we propose a CSI exchange amount allocation scheme. Finally, the simulations validate our theoretical claims.
Conventional beamforming transmission techniques can enhance physical layer secrecy performance while requiring the full channel state information (CSI) of legitimate users and even that of eavesdroppers at the transmitter. However, providing full CSI of legitimate users at the transmitter can be challenging in practice. Thus, it is of considerable interest to enhance secrecy performance with partial CSI of legitimate users at the transmitter. Random unitary beamforming (RUB) is a low‐complexity multiple antennas transmission scheme requiring limited CSI. In this study, the authors investigate the secrecy performance of RUB transmission over multiple‐input single‐output single‐eavesdropper and multiuser multiple‐input multiple‐output single‐eavesdropper channels. They also propose a novel RUB‐based artificial noise (AN) method for multiple antennas communication system. They derive the closed‐form expressions of the exact and the asymptotic ergodic secrecy rate and the secrecy outage probability for these transmission scenarios. Numerical results are presented to illustrate the trade‐off between performance and complexity of the resulting physical layer security design. They show that the deployment of RUB and RUB‐based AN offers an attractive solution for enhancing the security of wireless transmission systems.
In this paper, we investigate a multiuser MIMO downlink with imperfect channel state information (CSI) from the physical-layer security provision. In a classical transmitter (Alice)-legitimate receiver (Bob)-eavesdropper (Eve) model using artificial noise to disturb Eve's reception, we consider a general scenario where all nodes are equipped with multiple antennas, and Bob's CSI is acquired by pilot-assisted channel estimation. For designing the secure transmit beamforming, we utilize random matrix quantization (RMQ) to quantize Bob's channel estimate, and then Bob feeds it back to Alice. Due to the effects of imperfect CSI at Alice, the secrecy performance is upper bounded in the high signal-to-noise ratio (SNR) regions. In order to avoid the interference-limited phenomenon, we present a scaled strategy for the secrecy system utilizing derived upper bound on the secrecy rate loss. Moreover, it is shown that our derived results can be easily extended to a special case where both legitimate and eavesdropping receivers equip a single antenna each, where random vector quantization (RVQ) is utilized instead. By employing our proposed feedback strategy, the secrecy rate increases with transmit power, and the certain secrecy requirement can be guaranteed.
With the rapid development of wireless communications, security becomes extremely important. In many applications, each transmitter desires to send independent and confidential message to its intended receiver while ensuring mutual information-theoretic secrecy. In this dissertation, I study strategies for enhanced secrecy in wireless communication systems with limited rate feedback and transmitter cooperation. The two-user Gaussian channel model is considered under different scenarios. The transmitters both require channel state information (CSI), which is quantized at the receiver and fed back through the sum-rate-limited feedback channels. The quantization errors reduce the beamforming gain from the direct transmitter, and cause interference leakage from the cross transmitter. In the first scenario, I introduce the wiretap channel model where one receiver is a known eavesdropper, and a second transmitter is used to send a cooperative jamming signal to degrade the eavesdropper's channel. I consider two cases, one where no information about the eavesdroppers is available, and one where statistical CSI is available. With no information about the eavesdroppers, I show how to choose the allocation of feedback bits to the transmitters in order to maximize the amount of jamming power available to interfere with the eavesdroppers, subject to maintaining the lower bound on the rate at a minimum quality-of-service level. For the case of statistical CSI, I derive an approximate lower bound on the average secrecy rate, and optimize the bound to find a suitable bit allocation and the transmit power allocated to the transmitters. In the second scenario, I consider the interference channel model where the two transmitters are amenable to cooperation for improving the overall secrecy performance of the system. I derive an approximation for the average secrecy rate of each link, and optimize the sum secrecy rate over the transmit power and feedback bits allocated to the transmitters. Interestingly, increasing the transmit power beyond a certain point decreases the secrecy performance. When the transmitters have the same number of antennas, I derive the results in closed form. Simulations validate the theoretical analysis and demonstrate the significant performance gains that result from the use of optimal transmit power control and intelligent feedback bit allocation.