Ruixin Yang

Integrated sensing and communication (ISAC) enables simultaneous sensing and data transmission with the assistance of unmanned aerial vehicles (UAVs) in emergency disaster relief and inspects scenarios. However, the impact of sensing uncertainty on communication performance has not been systematically investigated. In this paper, we propose a novel UAV-aided ISAC framework that explicitly accounts for the uncertainty location sensing error (LSE). To characterize LSE more realistically, we derive the Cramér-Rao bound (CRB) and use it as the variance parameter for the considered uncertainty LSE models, instead of adopting the conventional unit-variance assumption. Then, we analytically reveal the inherent coupling relationship between LSE and achievable communication rate. Considering three practical LSE distributions, namely, ellipsoidal, Gaussian, and arbitrary distributions, we formulate three robust communication and sensing power allocation problems and develop tractable solutions using the ${\cal {S}}$-Procedure with alternating optimization (${\cal {S}}$-AO) method, Bernstein-type inequality with successive convex approximation (BI-SCA) method, and conditional value-at-risk (CVaR) with AO (CVaR-AO) method. Simulation results validate the theoretical coupling, demonstrate the robustness of the proposed schemes, and reveal sensing-communication trade-offs, providing valuable insights for robust UAV-aided ISAC system design.

Emerging Integrated Sensing and Communication (ISAC) systems integrate wireless communication with highprecision sensing, but the enhanced sensing capabilities also raise serious location privacy concerns. In this paper, we propose ChannelGuard, a novel DISCO intelligent reflective surface (DIRS)-based location privacy protection (LPP) mechanism. ChannelGuard introduces DIRS-based interference and thereby degrades the location estimation accuracy of the untrustworthy ISAC base station (BS). On this basis, we analyze the statistical characteristics of DIRS-based interference noise, revealing an intrinsic link between its noise properties and differential privacy (DP). We then formally prove that ChannelGuard satisfies (ε, δ)- DP and evaluate location privacy by deriving the position error bound (PEB). Numerical results demonstrate that ChannelGuard effectively protects location privacy while inducing a slight tradeoff in communication performance

Unmanned aerial vehicle (UAV) holds immense potential in integrated sensing and communication (ISAC) systems for the Internet of Things (IoT). In this paper, we propose a UAV-aided ISAC framework and investigate three robust power allocation schemes. First, we derive an explicit expression of the Cramér-Rao bound (CRB) based on time-of-arrival (ToA) estimation, which serves as the performance metric for location sensing. Then, we analyze the impact of the location sensing error (LSE) on communications, revealing the inherent coupling relationship between communication and sensing. Moreover, we formulate three robust communication and sensing power allocation problems by respectively characterizing the LSE as an ellipsoidal distributed model, a Gaussian distributed model, and an arbitrary distributed model. Notably, the optimization problems seek to minimize the CRB, subject to data rate and total power constraints. However, these problems are non-convex and intractable. To address the challenges related to the three aforementioned LSE models, we respectively propose to use the ${\cal{S}}$-Procedure and alternating optimization (${\cal{S}}$-AO) method, Bernstein-type inequality and successive convex approximation (BI-SCA) method, and conditional value-at-risk (CVaR) and AO (CVaR-AO) method to solve these problems. Finally, simulation results demonstrate the robustness of our proposed UAV-aided ISAC system against the LSE by comparing with the non-robust design, and evaluate the trade-off between communication and sensing in the ISAC system.

Integrated visible light positioning and communication (VLPC), capable of combining advantages of visible light communications (VLC) and visible light positioning (VLP), is a promising key technology for the future Internet of Things. In VLPC networks, positioning and communications are inherently coupled, which has not been sufficiently explored in the literature. We propose a robust power allocation scheme for integrated VLPC Networks by exploiting the intrinsic relationship between positioning and communications. Specifically, we derive explicit relationships between random positioning errors, following both a Gaussian distribution and an arbitrary distribution, and channel state information errors. Then, we minimize the Cramer-Rao lower bound (CRLB) of positioning errors, subject to the rate outage constraint and the power constraints, which is a chance-constrained optimization problem and generally computationally intractable. To circumvent the nonconvex challenge, we conservatively transform the chance constraints to deterministic forms by using the Bernstein-type inequality and the conditional value-at-risk for the Gaussian and arbitrary distributed positioning errors, respectively, and then approximate them as convex semidefinite programs. Finally, simulation results verify the robustness and effectiveness of our proposed integrated VLPC design schemes.

In this paper, we investigate an integrated visible light positioning and communication (VLPC) system with a single LED-lamp. First, by leveraging the fact that the VLC channel model is a function of the receiver’s location, we propose a system model that estimates the channel state information (CSI) based on the positioning information without transmitting pilot sequences. Second, we derive the Cramer-Rao lower bound (CRLB) on the positioning error variance and a lower bound on the achievable rate with on-off keying modulation. Third, based on the derived performance metrics, we optimize the power allocation to minimize the CRLB, while satisfying the rate outage probability constraint. To tackle this non-convex optimization problem, we apply the worst-case distribution of the Conditional Value-at-Risk (CVaR) and the block coordinate descent (BCD) methods to obtain the feasible solutions. Finally, the effects of critical system parameters, such as outage probability, rate threshold, total power threshold, are revealed by numerical results.

In this paper, we propose new inner and outer bounds of the capacity region for multiple access channels in visible light communication (VLC) networks under both peak and average optical power constraints. Specifically, the proposed inner bounds are established by employing the single-user capacity achieving input distribution for each user. The proposed outer bounds are derived by determining single-user capacities for each user and calculating a sum capacity upper bound by relaxing the input constraints. Numerical results show that the proposed new bounds are extremely tight and outperform existing bounds over wide ranges of SNRs.

We propose covert beamforming design frameworks for integrated radar sensing and communication (IRSC) systems, where the radar can covertly communicate with legitimate users under the cover of the probing waveforms without being detected by the eavesdropper. Specifically, by jointly designing the target detection beamformer and communication beamformer, we aim to maximize the radar detection mutual information (MI) (or the communication rate) subject to the covert constraint, the communication rate constraint (or the radar detection MI constraint), and the total power constraint. For the perfect eavesdropper’s channel state information (CSI) scenario, we transform the covert beamforming design problems into a series of convex subproblems, by exploiting semidefinite relaxation, which can be solved via the bisection search method. Considering the high complexity of iterative optimization, we further propose a single-iterative covert beamformer design scheme based on the zero-forcing criterion. For the imperfect eavesdropper’s CSI scenario, we develop a relaxation and restriction method to tackle the robust covert beamforming design problems. Simulation results demonstrate the effectiveness of the proposed covert beamforming schemes for perfect and imperfect CSI scenarios.

In this letter, we investigate a robust beamforming problem for localization-aided millimeter wave (mmWave) communication systems. To handle this problem, we propose a novel restriction and relaxation (R&R) method. The proposed R&R method aims at minimizing the total transmit power while the positioning error follows a Gaussian distribution. Specifically, in the restriction phase of R&R, the probabilistic constraint is transformed into the deterministic form by using the Bernstein-type inequality. In the relaxation phase of R&R, the non-convex optimization problem is reformulated into a convex semidefinite program (SDP) by using semidefinite relaxation (SDR) and first-order Taylor expansion methods. To the best of our knowledge, we first consider the impact of the distribution of the positioning error on the channel state information (CSI), which further influences the data rate. Numerical results present the trade-off of the beamforming between the communication and positioning.

The bound of the information transmission rate of direct current biased optical orthogonal frequency division multiplexing (DCO-OFDM) for visible light communication (VLC) with finite-alphabet inputs is yet unknown, where the corresponding spectral efficiency (SE) and energy efficiency (EE) stems out as the open research problems. In this paper, we derive the exact achievable rate of the DCO-OFDM system with finite-alphabet inputs for the first time. Furthermore, we investigate SE maximization problems of the DCO-OFDM system subject to both electrical and optical power constraints. By exploiting the relationship between the mutual information and the minimum mean-squared error, we propose a multi-level mercury-water-filling power allocation scheme to achieve the maximum SE. Moreover, the EE maximization problems of the DCO-OFDM system are studied, and the Dinkelbach-type power allocation scheme is developed for the maximum EE. Numerical results verify the effectiveness of the proposed theories and power allocation schemes.