Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userSecrecy Limits of Energy Harvesting IoT Networks under Channel Imperfections
76
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
Simultaneous wireless information and power transfer (SWIPT) has recently gathered much research interest from both academia and industry as a key enabler of energy harvesting Internet-of-things (IoT) networks. Due to a number of growing use cases of such networks, it is important to study their performance limits from the perspective of physical layer security (PLS). With this intent, this work aims to provide a novel analysis of the ergodic secrecy capacity of a SWIPT system is provided for Rician and Nakagami-m faded communication links. For a realistic evaluation of the system, the imperfections of channel estimations for different receiver designs of the SWIPT-based IoT systems have been taken into account. Subsequently, the closedform expressions of the ergodic secrecy capacities for the considered scenario are provided and, then, validated through extensive simulations. The results indicate that an error ceiling appears due to imperfect channel estimation at high values of signal-to-noise ratio (SNR). More importantly, the secrecy capacity under different channel conditions stops increasing beyond a certain limit, despite an increase of the main link SNR. The in-depth analysis of secrecy-energy trade-off has also been performed and a comparison has been provided for imperfect and perfect channel estimation cases. As part of the continuous evolution of IoT networks, the results provided in this work can help in identifying the secrecy limits of IoT networks in the presence of multiple eavesdroppers.
rate research
Read More
Surveillance performance is studied for a wireless eavesdropping system, where a full-duplex legitimate monitor eavesdrops a suspicious link efficiently with the artificial noise (AN) assistance. Different from the existing work in the literature, the suspicious receiver in this paper is assumed to be capable of detecting the presence of AN. Once such receiver detects the AN, the suspicious user will stop transmission, which is harmful for the surveillance performance. Hence, to improve the surveillance performance, AN should be transmitted covertly with a low detection probability by the suspicious receiver. Under these assumptions, an optimization problem is formulated to maximize the eavesdropping non-outage probability under a covert constraint. Based on the detection ability at the suspicious receiver, a novel scheme is proposed to solve the optimization problem by iterative search. Moreover, we investigate the impact of both the suspicious link uncertainty and the jamming link uncertainty on the covert surveillance performance. Simulations are performed to verify the analyses. We show that the suspicious link uncertainty benefits the surveillance performance, while the jamming link uncertainty can degrade the surveillance performance.
Analog-to-digital converters (ADCs) allow physical signals to be processed using digital hardware. The power consumed in conversion grows with the sampling rate and quantization resolution, imposing a major challenge in power-limited systems. A common ADC architecture is based on sample-and-hold (S/H) circuits, where the analog signal is being tracked only for a fraction of the sampling period. In this paper, we propose the concept of eSampling ADCs, which harvest energy from the analog signal during the time periods where the signal is not being tracked. This harvested energy can be used to supplement the ADC itself, paving the way to the possibility of zero-power consumption and power-saving ADCs. We analyze the tradeoff between the ability to recover the sampled signal and the energy harvested, and provide guidelines for setting the sampling rate in the light of accuracy and energy constraints. Our analysis indicates that eSampling ADCs operating with up to 12 bits per sample can acquire bandlimited analog signals such that they can be perfectly recovered without requiring power from the external source. Furthermore, our theoretical results reveal that eSampling ADCs can in fact save power by harvesting more energy than they consume. To verify the feasibility of eSampling ADCs, we present a circuit-level design using standard complementary metal oxide semiconductor (CMOS) 65 nm technology. An eSampling 8-bit ADC which samples at 40 MHZ is designed on a Cadence Virtuoso platform. Our experimental study involving Nyquist rate sampling of bandlimited signals demonstrates that such ADCs are indeed capable of harvesting more energy than that spent during analog-to-digital conversion, without affecting the accuracy.
Synchronization and ranging in internet of things (IoT) networks are challenging due to the narrowband nature of signals used for communication between IoT nodes. Recently, several estimators for range estimation using phase difference of arrival (PDoA) measurements of narrowband signals have been proposed. However, these estimators are based on data models which do not consider the impact of clock-skew on the range estimation. In this paper, clock-skew and range estimation are studied under a unified framework. We derive a novel and precise data model for PDoA measurements which incorporates the unknown clock-skew effects. We then formulate joint estimation of the clock-skew and range as a two-dimensional (2-D) frequency estimation problem of a single complex sinusoid. Furthermore, we propose: (i) a two-way communication protocol for collecting PDoA measurements and (ii) a weighted least squares (WLS) algorithm for joint estimation of clock-skew and range leveraging the shift invariance property of the measurement data. Finally, through numerical experiments, the performance of the proposed protocol and estimator is compared against the Cramer Rao lower bound demonstrating that the proposed estimator is asymptotically efficient.
In this paper, we investigate the downlink transmission of a multiuser multiple-input single-output (MISO) channel under a symbol-level precoding (SLP) scheme, having imperfect channel knowledge at the transmitter. In defining the SLP problem, a general category of constructive interference regions (CIR) called distance preserving CIR (DPCIR) is adopted. In particular, we are interested in the robust SLP design minimizing the total transmit power while satisfying the users quality-of-service (QoS) requirements. We consider two common models for the channel uncertainty region, namely, norm-bounded spherical and stochastic. For the spherical uncertainty model, a worst-case robust precoder is proposed, while for the stochastic uncertainties, we define a convex optimization problem with probabilistic constraints. We simulate the performance of the proposed robust approaches, and compare them with the existing methods. Through the simulation results, we also show that there is an essential trade-off between the two robust approaches.
Recently, multi-user multiple input multiple output (MU-MIMO) systems with low-resolution digital-to-analog converters (DACs) has received considerable attention, owing to the capability of dramatically reducing the hardware cost. Besides, it has been shown that the use of low-resolution DACs enable great reduction in power consumption while maintain the performance loss within acceptable margin, under the assumption of perfect knowledge of channel state information (CSI). In this paper, we investigate the precoding problem for the coarsely quantized MU-MIMO system without such an assumption. The channel uncertainties are modeled to be a random matrix with finite second-order statistics. By leveraging a favorable relation between the multi-bit DACs outputs and the single-bit ones, we first reformulate the original complex precoding problem into a nonconvex binary optimization problem. Then, using the S-procedure lemma, the nonconvex problem is recast into a tractable formulation with convex constraints and finally solved by the semidefinite relaxation (SDR) method. Compared with existing representative methods, the proposed precoder is robust to various channel uncertainties and is able to support a MUMIMO system with higher-order modulations, e.g., 16QAM.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
