This work focuses on the use of reconfigurable intelligent surface (RIS) in dual-function radar-communication (DFRC) systems to improve communication capacity and sensing precision, and enhance coverage for both functions. In contrast to most of the existing RIS aided DFRC works where the RIS is modeled as a diagonal phase shift matrix and can only reflect signals to half space, we propose a novel beyond diagonal RIS (BD-RIS) aided DFRC system. Specifically, the proposed BD-RIS supports the hybrid reflecting and transmitting mode, and is compatible with flexible architectures, enabling the system to realize full-space coverage and to achieve enhanced performance. To achieve the expected benefits, we jointly optimize the transmit waveform, the BD-RIS matrices, and sensing receive filters, by maximizing the minimum signal-to-clutter-plus-noise ratio for fair target detection, subject to the constraints of the communication quality of service, different BD-RIS architectures and power budget. To solve the non-convex and non-smooth max-min problem, a general solution based on the alternating direction method of multipliers is provided. Numerical simulations validate the efficacy of the proposed algorithm and show the superiority of the BD-RIS aided DFRC system in terms of both communication and sensing compared to conventional RIS aided DFRC.

In millimeter-wave (mmWave) dual-function radar-communication (DFRC) systems, hybrid beamforming (HBF) is recognized as a promising technique utilizing a limited number of radio frequency chains. In this work, in the presence of extended target and clutters, a HBF design based on the subarray connection architecture is proposed for a multiple-input multiple-output (MIMO) DFRC system. In this HBF, the double-phase-shifter (DPS) structure is embedded to further increase the design flexibility. We derive the communication spectral efficiency (SE) and radar signal-to-interference-plus-noise-ratio (SINR) with respect to the transmit HBF and radar receiver, and formulate the HBF design problem as the SE maximization subjecting to the radar SINR and power constraints. To solve the formulated nonconvex problem, the joinT Hybrid bEamforming and Radar rEceiver OptimizatioN (THEREON) is proposed, in which the radar receiver is optimized via the generalized eigenvalue decomposition, and the transmit HBF is updated with low complexity in a parallel manner using the consensus alternating direction method of multipliers (consensus-ADMM). Furthermore, we extend the proposed method to the multi-user multiple-input single-output (MU-MISO) scenario. Numerical simulations demonstrate the efficacy of the proposed algorithm and show that the solution provides a good trade-off between number of phase shifters and performance gain of the DPS HBF.

In this letter, we study the Hybrid Beamforming (HBF) design for a Dual-Function Radar-Communication (DFRC) system, which serves Multiple Users (MUs) and detects a target in the presence of signal-dependent clutters, simultaneously. Unlike conventional beamforming strategies, we propose a novel one on the symbol level, which exploits Constructive Interference (CI) to achieve a trade-off between radar and communication using one platform. To implement this novel strategy, we jointly design the DFRC transmit HBF and radar receive beamforming by maximizing the radar Signal to Interference plus Noise Ratio (SINR) while ensuring the Quality of Service (QoS) of downlink communication. To tackle the formulated non-convex problem, we propose an iterative algorithm, which combines the Majorization-Minimization (MM) and Alternating Direction Method of Multipliers (ADMM) judiciously. The numerical experiments indicate that our algorithm yields the CI properly for robust communications and achieves better performance than the conventional HBF benchmarks in both communication bit error rate and radar SINR.

In this letter, we investigate enhancing the physical layer security (PLS) for the dual-function radar-communication (DFRC) system with hybrid beamforming (HBF) architecture, where the base station (BS) achieves downlink communication and radar target detection simultaneously. We consider an eavesdropper intercepting the information transmitted from the BS to the downlink communication users with imperfectly known channel state information. Additionally, the location of the radar target is also imperfectly known by the BS. To enhance PLS in the considered DFRC system, we propose a novel HBF architecture, which introduces a new integrated sensing and security (I2S) symbol. The secure HBF design problem for DFRC is formulated by maximizing the minimum legitimate user communication rate subject to radar signal-to-interference-plus-noise ratio, eavesdropping rate, hardware and power constraints. To solve this non-convex problem, we propose an alternating optimization based method to jointly optimize transmit and receive beamformers. Numerical simulation results validate the effectiveness of the proposed algorithm and show the superiority of the proposed I2S-aided HBF architecture for achieving DFRC and enhancing PLS.

The use of skylights in buildings introduces natural light into the interior space, thereby reducing the reliance on artificial lighting and aligning with the principles of low carbon and environmental sustainability. To ensure optimal indoor lighting quality, it is essential to optimize the arrangement of skylights to strike a balance between high average illumination and uniformity of illumination. Recent initiatives by the Chinese government have emphasized the construction and renovation of numerous gymnasiums. In this research, a novel approach based on optimized algorithms was employed to design skylights and improve the uniformity of indoor illuminance. Simulation results demonstrated that the skylight arrangements derived from the optimization algorithms exhibited significantly higher levels of illumination uniformity, while maintaining comparable average illumination and skylight areas, when compared to conventional designs. Additionally, the study employed genetic algorithms to optimize the skylight arrangement for a specific gymnasium, resulting in a remarkable 32% increase in illumination uniformity. The study also accounted for obstacles and seating in the skylight design, and the genetic algorithm generated desirable skylight arrangements with respective increases of 32% and 21% in illumination uniformity for scenarios involving obstacles and seating. Overall, this study underscores the potential of optimized algorithms in the design of skylights for green buildings, offering valuable insights for future research endeavors in this field.