Achieving Covert Wireless Communications Using a Full-Duplex Receiver

Shahzad, Khurram; Zhou, Xiangyun; Yan, Shihao; Hu, Jinsong; Shu, Feng; Li, Jun

doi:10.1109/twc.2018.2878014

Cited by 205 publications

(105 citation statements)

References 36 publications

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“…where W t ∈ ℝ N×N and s t ≜ [s 1,t , s 2,t , … , s N,t ] T are the optimization variables for the time t ∈ {1, 2, … , T}. Due to the nonconvex problems in the main function (12) and constraint function (22), the problem P 1 cannot have the convex function of the global optimal state. Subsequently, relaxation methods are used to create an equivalent optimization problem in the following sections.…”

Section: Sensor Collaboration and Energy Storage Management For Detecmentioning

confidence: 99%

“…Shahzad et al studied the full‐duplex receiver for covert wireless communications for detecting a target. However, in their method, the sensors have always fixed position in transmitting data or energy and have not considered the ability to modify the sensor from the state of transmitter to the state of collecting energy and data according to the position and the channel access quality for the relay sensors.…”

Section: Introductionmentioning

confidence: 99%

“…Based on Lemma 1, the main detection function (12) and the transmission cost (22) are converted into the expression that involves quadratic vector function with respect to w. Using definition t ≜ g ′ t W t = G t w t , ie, G t is derived from the g ′ t in the same way that B is derived from b in Lemma 1, namely, the main detection function simplifies to…”

mentioning

confidence: 99%

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Optimization of distributed detection in energy harvesting wireless sensor networks with multiple antenna fusion center

Choubin

Taherpour

2020

Trans Emerging Tel Tech

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This paper addresses the detection improvement using multiple antenna fusion center (FC) and optimal collaboration among sensors with energy harvesting (EH) capability in WSNs. Using multiple antennas at FC, we benefit from the available fundamental spatial diversity in distributed WSN. We formulate to maximize the probability of collaborative detection based on parameters of collaboration among sensors and the energy of each sensor for the different scenarios as the optimization problem. In particular, we consider several practical constraints for EH and battery energy storage to maintain network connectivity. The objective function is the nonconvex function so the optimization problem is obtained as the nonconvex problem. To resolve this issue, the objective function is converted to a convex function using a relaxation method, and an optimum solution is obtained for this problem using local optimum values. The numerical results show the impact of the different parameters on the performance of the collaborative decision. These results also demonstrate that using distributed spatial diversity at FC by multiple antennas leads to a better decision in terms of error probability, and distributed wireless sensor‐enabled with EH capability results to more robust network connectivity in practice.

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Section: Sensor Collaboration and Energy Storage Management For Detecmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimization of distributed detection in energy harvesting wireless sensor networks with multiple antenna fusion center

Choubin

Taherpour

2020

Trans Emerging Tel Tech

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“…To create uncertainty at Willie's decoder, the jammer must vary his total power P j , independently in each n channel uses [7], [8], [22]. That is, the value of P j must be unknown to Willie in a way which he cannot estimate it efficiently.…”

Section: System Modelmentioning

confidence: 99%

“…That is, the value of P j must be unknown to Willie in a way which he cannot estimate it efficiently. Therefore, following similar assumptions as in [8], [22], we assume that P j is a uniform r.v. on [0, P max ] with the probability density function (pdf) given by,…”

Section: System Modelmentioning

confidence: 99%

Multi-Antenna Jamming in Covert Communication

Shmuel

Cohen

Gurewitz

et al. 2019

2019 IEEE International Symposium on Information Theory (ISIT)

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Covert communication conceals transmission of messages from Alice to Bob out of a watchful adversary, Willie, which tries to determine if a transmission took place or not. While covert communication in a basic, vanilla settings where all variables are known to Willie results in the well known squareroot law, when a jammer is present and assists Alice by creating uncertainty in Willie's decoder, this transmission may have a positive rate.In this work, we analyze the case where the jammer is equipped with multiple antennas and obtain the optimal transmission strategy of the jammer in order to maximize his assistance to Alice, in terms of maximizing a ratio between Willie's and Bob's noise variance. We show that the optimal strategy of the jammer is to perform beamforming towards a single direction with all his available power. This direction though, is not trivial, since it reflects an optimal tradeoff point between minimizing the interference at Bob and maximizing the interference at Willie.

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