Fairness-Aware Beamforming for Polarimetric ISAC Systems with Polarization-Reconfigurable Antennas

Polarization diversity offers significant flexibility for enhancing integrated sensing and communications (ISAC). However, conventional dual-polarized arrays typically require dedicated radio-frequency (RF) chains for each polarization branch, leading to prohibitive hardware costs. To address this, polarization-reconfigurable (PR) antennas have emerged as a cost-effective alternative, enabling polarization flexibility with reduced hardware complexity by driving two polarization branches with a single RF chain. In this paper, we investigate fairness-aware beamforming for ISAC systems equipped with PR antennas. Specifically, we jointly optimize the transmit beamforming and PR control coefficients to maximize the minimum signal-to-interference-plus-noise ratio (SINR) for communication users and the minimum signal-to-clutter-plus-noise ratio (SCNR) for sensing targets. The resulting problem is highly nonconvex and nonsmooth due to the strong coupling among optimization variables in the max-min objective, as well as the nonconvex spherical constraints imposed by the PR antennas. To tackle this, we derive an equivalent smooth reformulation by introducing auxiliary variables and transforming the minimum operators into inequality constraints. Subsequently, we develop an exact-penalty product Riemannian manifold gradient descent (EP-PRMGD) algorithm, which integrates an exact penalty method with Riemannian optimization to guarantee convergence to a Karush-Kuhn-Tucker (KKT) point. Numerical results demonstrate that the proposed PR-enabled ISAC scheme achieves performance comparable to dual-polarized architectures while utilizing only half the RF chains, thereby validating its effectiveness in balancing fairness and hardware efficiency.

💡 Research Summary

This paper addresses the challenge of achieving fairness in integrated sensing and communications (ISAC) systems while reducing hardware complexity through the use of polarization‑reconfigurable (PR) antennas. Conventional dual‑polarized arrays require a dedicated RF chain for each polarization branch, which doubles the number of RF chains and analog‑to‑digital converters (ADCs) and leads to prohibitive cost and power consumption, especially for massive MIMO deployments envisioned for 6G. PR antennas, by contrast, drive both horizontal (H) and vertical (V) polarization elements with a single RF chain, using analog combiners (e.g., variable attenuators or varactor‑based networks) to adjust the relative amplitudes and phases of the two branches. This architecture retains the full polarization degree of freedom while halving the RF‑chain count.

The authors consider a monostatic ISAC scenario where a base station (BS) equipped with (M_{\text{tx}}) transmit and (M_{\text{rx}}) receive PR antennas serves (K) single‑antenna communication users and simultaneously detects (T) point‑like targets in the presence of (C) clutter sources. Two independent data streams are generated: a communication stream (\mathbf{s}_c\in\mathbb{C}^{K}) and a radar stream (\mathbf{s}r\in\mathbb{C}^{L_r}). Digital beamforming matrices (\mathbf{W}c) and (\mathbf{W}r) shape these streams, producing the baseband vector (\hat{\mathbf{x}}=\mathbf{W}c\mathbf{s}c+\mathbf{W}r\mathbf{s}r). The PR transmit combining matrix (\mathbf{P}{\text{tx}}=\operatorname{blkdiag}(\mathbf{p}{\text{tx},1},\dots,\mathbf{p}{\text{tx},M{\text{tx}}})\in\mathbb{R}^{2M{\text{tx}}\times M{\text{tx}}}) maps the single‑RF‑chain output to the dual‑polarized antenna ports. Each (\mathbf{p}{\text{tx},m}=