This paper studies an integrated sensing and communication (ISAC) system, where a multi-antenna base station transmits beamformed signals for joint downlink multi-user communication and radar sensing of an extended target (ET). By considering echo signals as reflections from valid elements on the ET contour, a set of novel Cramér-Rao bounds (CRBs) is derived for parameter estimation of the ET, including central range, direction, and orientation. The ISAC transmit beamforming design is then formulated as an optimization problem, aiming to minimize the CRB associated with radar sensing, while satisfying a minimum signal-to-interference-pulse-noise ratio requirement for each communication user, along with a 3-dB beam coverage constraint tailored for the ET. To solve this non-convex problem, we utilize semidefinite relaxation (SDR) and propose a rank-one solution extraction scheme for non-tight relaxation circumstances. To reduce the computation complexity, we further employ an efficient zero-forcing (ZF) based beamforming design, where the sensing task is performed in the null space of communication channels. Numerical results validate the effectiveness of the obtained CRB, revealing the diverse features of CRB for differently shaped ETs. The proposed SDR beamforming design outperforms benchmark designs with lower estimation error and CRB, while the ZF beamforming design greatly improves computation efficiency with minor sensing performance loss.
In this paper, we investigate the network utility maximization problem in a dual-functional radar-communication multi-unmanned aerial vehicle (multi-UAV) network where multiple UAVs serve a group of communication users and cooperatively sense the target simultaneously. To balance the communication and sensing performance, we formulate a joint UAV location, user association, and UAV transmission power control problem to maximize the total network utility under the constraint of localization accuracy. We then propose a computationally practical method to solve this NP-hard problem by decomposing it into three sub-problems, i.e., UAV location optimization, user association and transmission power control. Three mechanisms are then introduced to solve the three sub-problems based on spectral clustering, coalition game, and successive convex approximation, respectively. The spectral clustering result provides an initial solution for user association. Based on the three mechanisms, an overall algorithm is proposed to iteratively solve the whole problem. We demonstrate that the proposed algorithm improves the minimum user data rate significantly, as well as the fairness of the network. Moreover, the proposed algorithm increases the network utility with a lower power consumption and similar localization accuracy, compared to conventional techniques.
Flexible strain sensors have attracted much attention due to their good flexibility, high sensitivity, superior repeatability, and great potentials for application in physiological signal detection. Carbon materials, including carbon nanotubes, graphene, carbon black, graphite, and natural-bioderived carbon materials are often used as active materials for the fabrication of flexible strain sensors because of their superior electrical conductivity and flexibility. Among them, carbon nanotubes and graphene can be prepared into flexible sensors in various forms, such as fibers, films, or textiles. Therefore, carbon material flexible sensors used for physiological signal detection have been sufficiently studied. Herein, the sensing mechanism of flexible strain sensors and the recent advances are reviewed. Sensor characteristics and functions of fibers/films with carbon nanotubes, graphene, and other carbon materials are described in terms of materials, preparation, and properties. From the aspect of sensor application, the sensors with different materials in large- and small-amplitude physiological signals are introduced in detail. Eventually, the superiorities and disadvantages of various carbon-based flexible strain sensors are summarized, and the challenges and opportunities of them in the future are also presented.
The adoption of self-sterilizing materials to reduce infection transmission in hospitals and related healthcare facilities has been hampered by the availability of scalable, cost-effective, and potent antimicrobial textiles. Here, we investigated whether photodynamic materials comprising photosensitizer-embedded wool/acrylic blends were able to mediate the photodynamic inactivation of Gram-positive and Gram-negative bacteria. A small library of wool/acrylic (W/A) blended fabrics was constructed wherein the wool fibers were embedded with rose Bengal (RB) as a photosensitizer and the acrylic fibers were dyed with a traditional cationic yellow X-8GL dye, thereby enabling a broader color palette than was achievable with a single photosensitizer. The resultant photodynamic materials were characterized by physical (SEM, DSC, TGA, tensile strength), spectroscopic (fluorescence), colorimetric (K/S and CIELab values), and color fastness (against rubbing, washing) studies, and their photooxidation of the model substrate potassium iodide demonstrated the ability of these materials to generate microbicidal reactive oxygen species (i.e., singlet oxygen) upon illumination. Our best results yielded the photodynamic inactivation of Gram-positive S. aureus (99.98%) and B. subtilis (99.993%) by ∼4 log units upon illumination with visible light (60 min; 65 ± 5 mW/cm 2 ; λ ≥ 420 nm), although more modest activity was observed against Gram-negative P. aeruginosa and E. coli (1−2 log units pathogen reduction). While there were no statistically significant differences for dual-dyed materials that were produced through either sequential or simultaneous dyeing steps, it was noted that high loadings of the cationic yellow X-8GL dye did inhibit the antimicrobial activity of the RB photosensitizer, with the dualdyed materials able to mediate a 2.9 log unit reduction against S. aureus at a 1% o.w.f X-8GL loading. These findings indicate that the antimicrobial photodynamic inactivation of dual-dyed materials is independent of the dyeing process itself, yet exhibits limitations on the loading of the traditional dye with regards to the activity of the photosensitizer. Taken together, the results suggest the feasibility of photosensitizer-embedded blended fabrics produced through a one-step dyeing process as a low-cost and scalable method for creating effective self-disinfecting textiles for infection prevention, and whose inclusion of a second traditional dye for color variation will further benefit their adoption from a commercial standpoint.
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