Correlation-Based Power Allocation for Secure Transmission with Artificial Noise

We examine for the first time the impact of transmitter-side correlation on the secure transmission with artificial noise (AN), based on which a new power allocation strategy for AN is devised for physical layer security enhancement. Specifically, we design a correlation-based power allocation (CPA) for AN, of which the optimality in terms of achieving the minimum secrecy outage probability is analytically proved in the large system regime with the number of transmit antennas approaching infinity. Our numerical results demonstrate that the CPA is nearly optimal and can significantly outperform the widely-used uniform power allocation (UPA) even for a moderate (finite) number of correlated transmit antennas. Our numerical results also reveal a fundamental difference between the secrecy performance of the CPA and that of the UPA. When the number of correlated transmit antennas increases, we find that the secrecy outage probability of the CPA always reduces while the secrecy outage probability of the UPA suffers from a saturation point.ARC Discovery Projects Grant DP15010390

Transmission resource allocation in multi-antenna wireless communication systems with channel uncertainty

In this thesis we investigate the design of transmission resource allocation in current and future wireless communication systems. We focus on systems with multiple antennas and characterize their performance from an information-theoretic viewpoint. The goal of this work is to provide practical transmission and resource allocation strategies taking into account imperfections in estimating the wireless channel, as well as the broadcast nature of the wireless channel. In the first part of the thesis, we consider training-based transmission schemes in which pilot symbols are inserted into data blocks to facilitate channel estimation. We consider one-way training-based systems with and without feedback, as well as two-way training-based systems. Two-way training enables both the transmitter and the receiver to obtain the channel state information (CSI) through reverse training and forward training, respectively. In all considered cases, we derive efficient strategies for transmit time and/or energy allocation among the pilot and data symbols. These strategies usually have analytical closed-form expressions and can achieve near optimal capacity performance evidenced by extensive numerical analysis. In one-way training-based systems without feedback, we consider both spatially independent and correlated channels. For spatially independent channels, we provide analytical bounds on the optimal training length and study the optimal antenna con¯guration that maximizes an ergodic capacity lower bound. For spatially correlated channels, we provide simple pilot and data transmission strategies that are robust under least-favorable channel correlation conditions. In one-way training-based systems with feedback, we study channel gain feedback (CGF), channel covariance feedback (CCF) and hybrid feedback. For spatially independent channels with CGF, we show that the solutions to the optimal training length and energy coincide with those for systems without feedback. For spatially correlated channels with CCF, we propose a simple transmission scheme, taking into account the fact that the optimal training length is at most as large as the number of transmit antennas. We then provided solution to the optimal energy allocation between pilot and data transmissions, which does not depend on the channel spatial correlation under a mild condition. Our derived resource allocation strategies in CGF and CCF systems are extended to hybrid CCF-CGF systems. In two-way training-based systems, we provide analytical solutions to the transmit power distribution among the different training phases and the data transmission phase. These solutions are shown to have near optimal symbol error rate (SER) and capacity performance. We find that the use of two-way training can provide noticeable performance improvement over reverse training only when the system is operating at moderate to high signal-to-noise ratio (SNR) and using high-order modulations. While this improvement from two-way training is insignificant at low SNR or low-order modulations. In the second part of the thesis, we consider transmission resource allocation in security-constrained systems. Due to the broadcast nature of the wireless medium, security is a fundamental issue in wireless communications. To guarantee secure communication in the presence of eavesdroppers, we consider a multi-antenna transmission strategy which sends both an information signal to the intended receiver and a noise-like signal isotropically to confuse the eavesdroppers. We study the optimal transmit power allocation between the information signal and the artificial noise. In particular, we show that equal power allocation is a near optimal strategy for non-colluding eavesdroppers, while more power should be used to generate the artificial noise for colluding eavesdroppers. In the presence of channel estimation errors, we find that it is better to create more artificial noise than to increase the information signal strength

Exploiting Full-duplex Receivers for Achieving Secret Communications in Multiuser MISO Networks

We consider a broadcast channel, in which a multi-antenna transmitter (Alice) sends $K$ confidential information signals to $K$ legitimate users (Bobs) in the presence of $L$ eavesdroppers (Eves). Alice uses MIMO precoding to generate the information signals along with her own (Tx-based) friendly jamming. Interference at each Bob is removed by MIMO zero-forcing. This, however, leaves a "vulnerability region" around each Bob, which can be exploited by a nearby Eve. We address this problem by augmenting Tx-based friendly jamming (TxFJ) with Rx-based friendly jamming (RxFJ), generated by each Bob. Specifically, each Bob uses self-interference suppression (SIS) to transmit a friendly jamming signal while simultaneously receiving an information signal over the same channel. We minimize the powers allocated to the information, TxFJ, and RxFJ signals under given guarantees on the individual secrecy rate for each Bob. The problem is solved for the cases when the eavesdropper's channel state information is known/unknown. Simulations show the effectiveness of the proposed solution. Furthermore, we discuss how to schedule transmissions when the rate requirements need to be satisfied on average rather than instantaneously. Under special cases, a scheduling algorithm that serves only the strongest receivers is shown to outperform the one that schedules all receivers.Comment: IEEE Transactions on Communication

Secure Massive MIMO Transmission in the Presence of an Active Eavesdropper

In this paper, we investigate secure and reliable transmission strategies for multi-cell multi-user massive multiple-input multiple-output (MIMO) systems in the presence of an active eavesdropper. We consider a time-division duplex system where uplink training is required and an active eavesdropper can attack the training phase to cause pilot contamination at the transmitter. This forces the precoder used in the subsequent downlink transmission phase to implicitly beamform towards the eavesdropper, thus increasing its received signal power. We derive an asymptotic achievable secrecy rate for matched filter precoding and artificial noise (AN) generation at the transmitter when the number of transmit antennas goes to infinity. For the achievability scheme at hand, we obtain the optimal power allocation policy for the transmit signal and the AN in closed form. For the case of correlated fading channels, we show that the impact of the active eavesdropper can be completely removed if the transmit correlation matrices of the users and the eavesdropper are orthogonal. Inspired by this result, we propose a precoder null space design exploiting the low rank property of the transmit correlation matrices of massive MIMO channels, which can significantly degrade the eavesdropping capabilities of the active eavesdropper.Comment: To appear in ICC 1

Artificial-Noise-Aided Secure Multi-Antenna Transmission with Limited Feedback

We present an optimized secure multi-antenna transmission approach based on artificial-noise-aided beamforming, with limited feedback from a desired single-antenna receiver. To deal with beamformer quantization errors as well as unknown eavesdropper channel characteristics, our approach is aimed at maximizing throughput under dual performance constraints - a connection outage constraint on the desired communication channel and a secrecy outage constraint to guard against eavesdropping. We propose an adaptive transmission strategy that judiciously selects the wiretap coding parameters, as well as the power allocation between the artificial noise and the information signal. This optimized solution reveals several important differences with respect to solutions designed previously under the assumption of perfect feedback. We also investigate the problem of how to most efficiently utilize the feedback bits. The simulation results indicate that a good design strategy is to use approximately 20% of these bits to quantize the channel gain information, with the remainder to quantize the channel direction, and this allocation is largely insensitive to the secrecy outage constraint imposed. In addition, we find that 8 feedback bits per transmit antenna is sufficient to achieve approximately 90% of the throughput attainable with perfect feedback.Comment: to appear in IEEE Transactions on Wireless Communication