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Information Theory (cs.IT)

Tue, 29 Aug 2023

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1.Robust Transceiver Design for Covert Integrated Sensing and Communications With Imperfect CSI

Authors:Yuchen Zhang, Wanli Ni, Jianquan Wang, Wanbin Tang, Min Jia, Yonina C. Eldar, Dusit Niyato

Abstract: We propose a robust transceiver design for a covert integrated sensing and communications (ISAC) system with imperfect channel state information (CSI). Considering both bounded and probabilistic CSI error models, we formulate worst-case and outage-constrained robust optimization problems of joint trasceiver beamforming and radar waveform design to balance the radar performance of multiple targets while ensuring communications performance and covertness of the system. The optimization problems are challenging due to the non-convexity arising from the semi-infinite constraints (SICs) and the coupled transceiver variables. In an effort to tackle the former difficulty, S-procedure and Bernstein-type inequality are introduced for converting the SICs into finite convex linear matrix inequalities (LMIs) and second-order cone constraints. A robust alternating optimization framework referred to alternating double-checking is developed for decoupling the transceiver design problem into feasibility-checking transmitter- and receiver-side subproblems, transforming the rank-one constraints into a set of LMIs, and verifying the feasibility of beamforming by invoking the matrix-lifting scheme. Numerical results are provided to demonstrate the effectiveness and robustness of the proposed algorithm in improving the performance of covert ISAC systems.

2.An Advanced Tree Algorithm with Interference Cancellation in Uplink and Downlink

Authors:Quirin Vogel, Yash Deshpande, Čedomir Stefanović, Wolfgang Kellerer

Abstract: In this paper, we propose Advanced Tree-algorithm with Interference Cancellation (ATIC), a variant of binary tree-algorithm with successive interference cancellation (SICTA) introduced by Yu and Giannakis. ATIC assumes that Interference Cancellation (IC) can be performed both by the access point (AP), as in SICTA, but also by the users. Specifically, after every collision slot, the AP broadcasts the observed collision as feedback. Users who participated in the collision then attempt to perform IC by subtracting their transmissions from the collision signal. This way, the users can resolve collisions of degree 2 and, using a simple distributed arbitration algorithm based on user IDs, ensure that the next slot will contain just a single transmission. We show that ATIC reaches the asymptotic throughput of 0.924 as the number of initially collided users tends to infinity and reduces the number of collisions and packet delay. We also compare ATIC with other tree algorithms and indicate the extra feedback resources it requires.

3.A Novel Dual Predictors Framework of PEE

Authors:Fangjian Shen, Yicheng Zheng, Songyou Li

Abstract: In this paper, we propose a improved 2D-PEH based on double prediction-error. First,different from previous 2D-PEH, the proposed 2D-DPEH is established by selecting two distinct predictors with low correlation to calculate double prediction errors for each pixel. In addition, we adopt DP to optimize the selection of expansion bins, speeding up the running time and improving the quality of the embedded image. Finally,we combined the proposed method with C-PEE and original MHM, then designed comparative experiments with state of-the-art Pee-based methods in recent years to verify the superiority of the proposed algorithm and extend PEE into a more general case.

4.Sampling for Remote Estimation of an Ornstein-Uhlenbeck Process through Channel with Unknown Delay Statistics

Authors:Yuchao Chen, Haoyue Tang, Jintao Wang, Pengkun Yang, Leandros Tassiulas

Abstract: In this paper, we consider sampling an Ornstein-Uhlenbeck (OU) process through a channel for remote estimation. The goal is to minimize the mean square error (MSE) at the estimator under a sampling frequency constraint when the channel delay statistics is unknown. Sampling for MSE minimization is reformulated into an optimal stopping problem. By revisiting the threshold structure of the optimal stopping policy when the delay statistics is known, we propose an online sampling algorithm to learn the optimum threshold using stochastic approximation algorithm and the virtual queue method. We prove that with probability 1, the MSE of the proposed online algorithm converges to the minimum MSE that is achieved when the channel delay statistics is known. The cumulative MSE gap of our proposed algorithm compared with the minimum MSE up to the $(k+1)$-th sample grows with rate at most $\mathcal{O}(\ln k)$. Our proposed online algorithm can satisfy the sampling frequency constraint theoretically. Finally, simulation results are provided to demonstrate the performance of the proposed algorithm.

5.Timely Multi-Goal Transmissions With an Intermittently Failing Sensor

Authors:Ismail Cosandal, Sennur Ulukus

Abstract: A sensor observes a random phenomenon and transmits updates about the observed phenomenon to a remote monitor. The sensor may experience intermittent failures in which case the monitor will not receive any updates until the sensor has recovered. The monitor wants to keep a timely view of the observed process, as well as to detect any sensor failures, using the timings of the updates. We analyze this system model from a goal-oriented and semantic communication point of view, where the communication has multiple goals and multiple meanings/semantics. For the first goal, the performance is quantified by the age of information of the observed process at the monitor. For the second goal, the performance is quantified by the probability of error of the monitor's estimation of the sensor's failure status. Each arriving update packet brings both an information update and an indication about the sensor's status. The monitor estimates the failure status of the sensor by using the timings of the received updates. This estimation is subject to error, since a long period without any update receptions may be due to a low update rate or a failure of the sensor. We examine the trade-off between these two goals. We show that the probability of error of estimating a sensor failure decreases with increased update rate, however, the age of information is minimized with an intermediate update rate (not too low or high).