arXiv subjects

Ataher Sams

Publications and source records attributed to Ataher Sams.

3 recordsLinked to original sources

arXiv2026

On the Reliability of Estimation Bounds in Low-SNR Bistatic ISAC

This paper explores a bistatic Integrated Sensing and Communication (ISAC) framework, where a base station transmits communication signal that serve both direct communication with a user and multi-target parameter estimation through reflections captured by a separate sensing receiver. We assume that the instantaneous knowledge of the transmit signal at the sensing receiver is not available, and the sensing receiver only has knowledge of the statistical properties of the received signal. Unlike prior research that focuses on power allocation or optimal beamforming design for ISAC, we emphasize the inadequacy of the Cram\'er-Rao Bound (and its variant) in low Signal-to-Noise Ratio (SNR) regimes, particularly in passive sensing scenarios. Due to severe path loss and other impairments, the received sensing SNR is often significantly lower than that of direct Line-of-Sight communication, making CRB-based performance evaluation unreliable. To address this, we adopt the Ziv-Zakai Bound (ZZB) for Angle of Arrival estimation, which provides a more meaningful lower bound on estimation error. We derive analytical expressions for the ZZB and the achievable ergodic communication rate as functions of SNR. Through numerical simulations, we analyze the pareto-front between communication and sensing performance, demonstrating why ZZB serves as a better metric in low sensing SNR ISAC where traditional CRB-based approaches fail.

cs.IT↗

arXiv2025

Optimizing ISAC MIMO Systems with Reconfigurable Pixel Antennas

The integration of sensing and communication demands architectures that can flexibly exploit spatial and electromagnetic (EM) degrees of freedom (DoF). This paper proposes an Integrated Sensing and Communication (ISAC) MIMO framework that uses Reconfigurable Pixel Antenna (RPixA), which introduces additional EM-domain DoF that are electronically controlled through binary antenna coder switch networks. We introduce a beamforming architecture combining this EM and digital precoding to jointly optimize Sensing and Communication. Based on full-wave simulation of pixel antenna, we formulate a non-convex joint optimization problem to maximize sensing rate under user-specific constraints on communication rate. We utilize an Alternating Optimization framework incorporating genetic algorithm for port states of Pixel antennas, and semi-definite relaxation (SDR) for digital beamforming. Numerical results demonstrate that the proposed EM-aware design achieves considerably higher sensing rate compared to conventional arrays and enables considerable antenna reduction for equivalent ISAC performance. These findings highlight the potential of reconfigurable pixel antennas to realize efficient and scalable EM-aware ISAC systems for future 6G networks.

eess.SP↗

arXiv2025

On Estimation of Angles of Arrival in Monostatic ISAC Without Instantaneous Transmit CSI

This paper explores the fundamental limits of Integrated Sensing and Communication (ISAC) in a more realistic setting compared to previous literature when the Base Staion (BS) has only statistical CSI of the communication user rather than full CSI. We analyze a monostatic setting where the BS performs multi-target Angle of Arrival (AoA) estimation while simultaneously communicating with one of the targets. We assume that the BS has statistical CSI about all AoAs, with less uncertainty in the AoA of the communication receiver. The communication receiver is assumed to have perfect CSI. Utilizing a Bayesian Cram\'er-Rao Bound (BCRB) framework to characterize the fundamental limits of sensing under minimum mean square error (MMSE) criteria, we derive achievable BCRB-rate trade-off regions. Our approach introduces a number of transmission strategies that share power across sensing and communication beams over a coherence time. Our analysis reveals that beam allocation strategies leveraging the principal eigenvectors of the target-specific sensing matrices minimize individual AoA estimation errors, while strategies balancing sensing and communication directions optimize joint estimation performance at the cost of individual accuracy. We demonstrate that leveraging updated BCRB-based sensing information for the communication receiver, due to its lower channel uncertainty, enables significantly improved communication rates.

cs.IT↗