Characteristic modes can be used to solve many radiation and scattering problems involving fully conducting structures. The basic concept is to use eigenvalues and eigenvectors of the characteristic mode equations of a certain topology, and to use these eigenmode currents to control the radiating structure’s behavior. This is accomplished by understanding the overall reflection and radiation characteristics across the operating frequency band. More specifically, characteristic modes are effective for example in determining the best location for the excitation of a radiating structure. In this paper, a comprehensive overview is provided to the different studies and their results obtained for different antennas that are based on the characteristic mode analysis method. A future perspective is given regarding the potential of this method in antenna analysis and design.

In this paper, the design of a multiband multiple-input multiple-output (MIMO) antenna with frequency and radiation pattern reconfiguration capability in the 5G sub-6 GHz band is presented. Frequency and radiation pattern reconfiguration are enabled on the antenna consisting of two planar inverted-F antenna (PIFA) elements using PIN diodes and DC biasing circuits. At the reflection coefficients of less than −6 dB, both PIFA element 1 and PIFA element 2 achieves triband with bandwidth from 220 MHz to 2330 MHz, ranging from 0.8 GHz to 6 GHz, covering cellular bands for GSM, UMTS, LTE and 5G-NR bands. Moreover, high isolation of at least −10 dB and envelope correlation coefficient with less than 0.3 between ports ensures satisfactory MIMO diversity performance. PIFA elements 1 and 2 have achieved main lobe gain ranging from 1.06 dB to 2.97 dB at their respective resonant frequencies with total efficiencies ranging from 46.2% to 74.5% achieved within the operating bandwidth. This enables a calculated channel capacity of 9.45 to 10.5 bit/s/Hz for PIFA element 1 and 9.56 to 10.23 bit/s/Hz for PIFA element 2, respectively. The percentage of channel capacity achieved over IID capacity for both PIFA elements ranges from 73.71% to 92.8%. Simulated antenna performance parameters agreed well with measurements, and potentially enables reliable and consistent data throughput for 5G mobile terminals.

This work presents, for the first time, an in-situ self-aligned fluidic-integrated microwave sensor for characterizing NaCl contents in NaCl-aqueous solution based on a 16-GHz bandpass combline cavity resonator. The discrimination of the NaCl concentration is achievable by determining amplitude differences and resonant frequency translations between the incident and reflected microwave signals at the input terminal of the cavity resonator based on the capacitive loading effects of the comb structure inside the cavity introduced by the NaCl solution under test. Twelve NaCl-aqueous liquid mixture samples with different NaCl concentrations ranging from 0% to 20% (0 - 200 mg/mL), which are generally exploited in most industrial and biomedical applications, were prepared and encapsulated inside a Teflon tube performing as a fluidic channel. The Teflon tube is subsequently inserted into the cavity resonator through two small holes, fabricated through the sidewalls of the cavity, which can be used to automatically align the fluidic subsystem inside the combline resonator considerably easing the sensor setup. Based on at least five repeated measurements, the NaCl sensor can discriminate the NaCl content of as low as 1% with the measurement accuracy of higher than 96% and the maximum standard deviation of only 0.0578. There are several significant advantages achieved by the novel NaCl sensors, e.g. high accuracy, traceability and repeatability; ease of sensor setup and integration to actual industrial and biomedical systems enabling in-situ and real-time measurements; noninvasive and noncontaminative liquid solution characterization as well as superior sensor reusability due to a complete physical separation between the fluidic and microwave subsystems.

In this paper, the design and measurement of a three-dimensional-printed low-loss asymptotically single-mode hollow-core terahertz Bragg fiber are reported, operating across the frequency range from 0.246 to 0.276 THz. The HE11 mode is employed as it is the lowest loss propagating mode, with the electromagnetic field concentrated within the air core as a result of the photonic crystal bandgap behavior. The HE11 mode also has large loss discrimination compared to its main competing HE12 mode. This results in asymptotically single-mode operation of the Bragg fiber, which is verified by extensive simulations based on the actual fabricated Bragg fiber dimensions and measured material parameters. The measured average propagation loss of the Bragg fiber is lower than 5 dB/m over the frequency range from 0.246 to 0.276 THz, which is, to the best of our knowledge, the lowest loss asymptotically single-mode all-dielectric microstructured fiber yet reported in this frequency range, with a minimum loss of 3 dB/m at 0.265 THz.

Advances in reconfigurable liquid-based reconfigurable antennas are enabling new possibilities to fulfil the requirements of more advanced wireless communication systems. In this review, a comparative analysis of various state-of-the-art concepts and techniques for designing reconfigurable antennas using liquid is presented. First, the electrical properties of different liquids at room temperature commonly used in reconfigurable antennas are identified. This is followed by a discussion of various liquid actuation techniques in enabling high frequency reconfigurability. Next, the liquid-based reconfigurable antennas in literature used to achieve the different types of reconfiguration will be critically reviewed. These include frequency-, polarization-, radiation pattern-, and compound reconfigurability. The current concepts of liquid-based reconfigurable antennas can be classified broadly into three basic approaches: altering the physical (and electrical) dimensions of antennas using liquid; applying liquid-based sections as reactive loads; implementation of liquids as dielectric resonators. Each concept and their design approaches will be examined, outlining their benefits, limitations, and possible future improvements.

Ganoderma boninense (G. boninense) infection reduces the productivity of oil palms and causes a serious threat to the palm oil industry. This catastrophic disease ultimately destroys the basal tissues of oil palm, causing the eventual death of the palm. Early detection of G. boninense is vital since there is no effective treatment to stop the continuing spread of the disease. This review describes past and future prospects of integrated research of near-infrared spectroscopy (NIRS), machine learning classification for predictive analytics and signal processing towards an early G. boninense detection system. This effort could reduce the cost of plantation management and avoid production losses. Remarkably, (i) spectroscopy techniques are more reliable than other detection techniques such as serological, molecular, biomarker-based sensor and imaging techniques in reactions with organic tissues, (ii) the NIR spectrum is more precise and sensitive to particular diseases, including G. boninense, compared to visible light and (iii) hand-held NIRS for in situ measurement is used to explore the efficacy of an early detection system in real time using ML classifier algorithms and a predictive analytics model. The non-destructive, environmentally friendly (no chemicals involved), mobile and sensitive leads the NIRS with ML and predictive analytics as a significant platform towards early detection of G. boninense in the future.