Covert Wireless Communication with a Poisson Field of Interferers

In this paper, we study covert communication in wireless networks consisting of a transmitter, Alice, an intended receiver, Bob, a warden, Willie, and a Poisson field of interferers. Bob and Willie are subject to uncertain shot noise due to the ambient signals from interferers in the network. With the aid of stochastic geometry, we analyze the throughput of the covert communication between Alice and Bob subject to given requirements on the covertness against Willie and the reliability of decoding at Bob. We consider non-fading and fading channels. We analytically obtain interesting findings on the impacts of the density and the transmit power of the concurrent interferers on the covert throughput. That is, the density and the transmit power of the interferers have no impact on the covert throughput as long as the network stays in the interference-limited regime, for both the non-fading and the fading cases. When the interference is sufficiently small and comparable with the receiver noise, the covert throughput increases as the density or the transmit power of the concurrent interferers increases

Regularized Channel Inversion for Simultaneous Confidential Broadcasting and Power Transfer: A Large System Analysis

We propose for the first time new transmission schemes based on linear precoding to enable simultaneous confidential broadcasting and power transfer (SCBPT) in a multiuser multi-input single-output (MISO) network, where a BS with N antennas simultaneously transmits power and confidential messages to K single-antenna users. We first design two transmission schemes based on the rules of regularized channel inversion (RCI) for both power splitting (PS) and time switching (TS) receiver architectures, namely, RCI-PS and RCI-TS schemes. For each scheme, we derive channel-independent expressions to approximate the secrecy sum rate and the harvested power in the large-system regime where K, N → ∞ with a fixed ratio β = K/N. Based on the large-system results, we jointly optimize the regularization parameter of the RCI and the PS ratio or the TS ratio such that the secrecy sum rate is maximized subject to an energy-harvesting constraint. We then present the tradeoff between the secrecy sum rate and the harvested power achieved by each scheme, and find that neither scheme always outperforms the other one. Motivated by this fact, we design an RCI-hybrid scheme based on the RCI and a newly proposed hybrid receiver architecture. The hybrid receiver architecture takes advantages of both the PS and TS receiver architectures. We show that the RCI-hybrid scheme outperforms both the RCI-PS and RCI-TS schemes.ARC Discovery Projects Grant DP15010390

Covert communication with finite blocklength in AWGN channels

Covert communication is to achieve a reliable transmission from a transmitter to a receiver while guaranteeing an arbitrarily small probability of this transmission being detected by a warden. In this work, we study the covert communication in AWGN channels with finite blocklength, in which the number of channel uses is finite. Specifically, we analytically prove that the entire block (all available channel uses) should be utilized to maximize the effective throughput of the transmission subject to a predetermined covert requirement. This is a nontrivial result because more channel uses results in more observations at the warden for detecting the transmission. We also determine the maximum allowable transmit power per channel use, which is shown to decrease as the blocklength increases. Despite the decrease in the maximum allowable transmit power per channel use, the maximum allowable total power over the entire block is proved to increase with the blocklength, which leads to the fact that the effective throughput increases with the blocklength.ARC Discovery Projects Grant DP15010390

Efficient Multi-objective Evolutionary 3D Neural Architecture Search for COVID-19 Detection with Chest CT Scans

COVID-19 pandemic has spread globally for months. Due to its long incubation period and high testing cost, there is no clue showing its spread speed is slowing down, and hence a faster testing method is in dire need. This paper proposes an efficient Evolutionary Multi-objective neural ARchitecture Search (EMARS) framework, which can automatically search for 3D neural architectures based on a well-designed search space for COVID-19 chest CT scan classification. Within the framework, we use weight sharing strategy to significantly improve the search efficiency and finish the search process in 8 hours. We also propose a new objective, namely potential, which is of benefit to improve the search process's robustness. With the objectives of accuracy, potential, and model size, we find a lightweight model (3.39 MB), which outperforms three baseline human-designed models, i.e., ResNet3D101 (325.21 MB), DenseNet3D121 (43.06 MB), and MC3\_18 (43.84 MB). Besides, our well-designed search space enables the class activation mapping algorithm to be easily embedded into all searched models, which can provide the interpretability for medical diagnosis by visualizing the judgment based on the models to locate the lesion areas.Comment: Neural Architecture Search, Evolutionary Algorithm, COVID-19, C

On Covert Communication With Noise Uncertainty

Prior studies on covert communication with noise uncertainty adopted a worst-case approach from the warden’s perspective. That is, the worst-case detection performance of the warden is used to assess covertness, which is overly optimistic. Instead of simply considering the worst limit, in this work, we take the distribution of noise uncertainty into account to evaluate the overall covertness in a statistical sense. Specifically, we define new metrics for measuring the covertness, which are then adopted to analyze the maximum achievable rate for a given covertness requirement under both bounded and unbounded noise uncertainty models.ARC Discovery Projects Grant DP15010390

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

Delay-Intolerant Covert Communications with Either Fixed or Random Transmit Power

In this paper, we study delay-intolerant covert communications in additive white Gaussian noise (AWGN) channels with a finite block length, i.e., a finite number of channel uses. Considering the maximum allowable number of channel uses to be N, it is not immediately clear whether the actual number of channel uses, denoted by n, should be as large as N or smaller for covert communications. This is because a smaller n reduces a warden’s chance to detect the communications due to fewer observations, but also reduces the chance to transmit information. We show that n=N is indeed optimal to maximize the amount of information bits that can be transmitted, subject to any covert communication constraint in terms of the warden’s detection error probability. To better make use of the warden’s uncertainty due to the finite block length, we also propose to use uniformly distributed random transmit power to enhance covert communications. Our examination shows that the amount of information that can be covertly transmitted logarithmically increases with the number of random power levels, which indicates that most of the benefit of using random transmit power is achieved with just a few different power levels.This work was supported by the Australian Research Council’s Discovery Projects under Grant DP180104062