This Letter demonstrates the design of a two-element polarisation diversity antenna, applicable for modern small satellite application systems. The intended antenna mainly consists of two monopole radiators loaded with metasurface reflector as a ground plane. The dimensions of the radiator antenna are 40 × 22 × 1.6 mm³. The antenna measured results offers a wider S ₁₁ bandwidth of (2.23–2.91 GHz) and wider axial ratio bandwidth (ARBW) of (2.16–2.92 GHz) with a common S ₁₁ and ARBW of 26.45% is obtained. A maximum gain of 7.02 dBic and isolation better than 14.5 dB is observed along with the operating frequency range. The antenna provides an ARBW(< 3 dB) and gain (> 2.38 dBic) for theta = ± 45°, for all phi values along with the complete operating frequency range. Also, the antenna port-1 provides left-handed circular polarisation and port-2 provides right-handed circular polarisation radiation with directional radiation characteristics.

This study suggests several analogue bandwidth mismatch compensation techniques for time-interleaved analogue-to-digital converters. All the techniques adjust the equivalent on-resistance of the track and hold (T/H) under calibration. Simulations of a two-channel time interleaved T/H running at GHz shows the effectiveness of the proposed compensations.

The unconditionally stable alternating-direction-implicit finite-difference time-domain (ADI-FDTD) method is extended for modelling anisotropic magnetised graphene sheets. In contrast to the conventional method for isotropic media, two additional sub-stepping calculations are applied to incorporate anisotropic medium properties. The unconditional stability of the proposed extended method is examined numerically. The method is applied to study the transmission properties of graphene sheets. Numerical results show that the proposed method is more accurate than the recently developed locally one-dimensional FDTD method.

To perform the image segmentation task, in this Letter, a kernel fuzzy C-means algorithm is introduced, strengthened by a robust Gaussian radial basis function kernel based on M-estimators. It is well-known that these kernels consider the squared difference as a similarity measure, which is not robust to atypical data. In this regard, the main motivation of this contribution is to improve the atypical information tolerance of these kernels, in order to make a better clustering of pixels. Experimental tests were developed considering colour images. The robustness and effectiveness of this proposal are verified by quantitative and qualitative results.

This Letter discusses the benefits of introducing Machine Learning techniques in multi-view streaming applications. Widespread use of machine learning techniques has contributed to significant gains in numerous scientific and industry fields. Nonetheless, these have not yet been specifically applied to adaptive interactive multimedia streaming systems where, typically, the encoding bit rate is adapted based on resources availability, targeting the efficient use of network resources whilst offering the best possible user quality of experience (QoE). Intrinsic user data could be coupled with such existing quality adaptation mechanisms to derive better results, driven also by the preferences of the user. Head-tracking data, captured from camera feeds available at the user side, is an example of such data to which Recurrent Attention Models could be applied to accurately predict the focus of attention of users within videos frames. Information obtained from such models could be used to assist a preemptive buffering approach of specific viewing angles, contributing to the joint goal of maximising QoE. Based on these assumptions, a research line is presented, focusing on obtaining better QoE in an already existing multi-view streaming system

Mobile edge computing (MEC) has been deemed as one of the key technologies for pushing powerful computing ability to the radio access network. Different scenarios require different services, and tasks usually require computing in a specific runtime environment. However, few studies have taken this into consideration. To this end, the authors propose a novel model of service-dependent task offloading for the multiuser MEC system with resource constraints. Through determining which services should be deployed at the network edge and how many tasks should be offloaded, a revenue maximisation problem is constructed. Accordingly, they propose an iterative optimisation algorithm with high performance for the service deploying and task offloading problem. Finally, numerical simulations reveal that their proposed algorithm outperforms other schemes.

In this Letter, a novel self-packaged grounded suspended coplanar waveguide (GSCPW) structure is proposed by using the common multi-layer PCB techniques, which eliminates the drawbacks of bulky circuit size, heavy weight and difficult to be integrated as that of the traditional suspended circuits with mechanical mounting. Both self-packaging and end connection are used to reduce the wave leakage, and the multiple via holes are saved, which greatly reduce the simulation time and the fabrication complexity. The proposed GSCPW structure has been fabricated, and has been demonstrated by experimental results with a measured insertion loss of no more than 0.45 dB, and a measured return loss of better than 20 dB from dc to 4 GHz.

This Letter proposes a novel balanced triple-mode substrate integrated waveguide (SIW) bandpass filter for the first time. The new triple-mode resonator is realised by a square-shaped SIW cavity with a capacitive loading patch. The resonance of higher-order mode TE₃₀₁ can be controlled and shifted to that of modes TE₁₀₂ and TE₂₀₁. High-performance common mode suppression, controllable bandwidth, compact size and quasi-elliptic differential mode response can be achieved. For demonstration, a balanced triple-mode SIW filter is designed, fabricated and measured.

Theoretical calculations and simulations are introduced to explain the passive intermodulation power level rise (PLR) in coaxial connectors with broadband signal excitation for the third-order intermodulation products. An equivalent model is developed to describe the characteristics of the broadband signals. The non-linearity of connectors is defined by a polynomial behaviour model. A mathematical model of the PLR is developed. A series of experiments are conducted to verify the proposed models. The experimental results agree well with the analytic results, having a mean difference of 0.6 dB.

A terahertz (THz) imaging enhancement approach is presented by using multi-features of images. First, a set of THz images are reconstructed from a single data collection using THz time-domain spectroscopy system by selecting different features. Second, the THz beam model is considered to improve image resolution, which is realised via a Wiener de-convolution operation. Third, an approach to suppress the noise and enhance image feature is adopted to achieve a better image quality. Finally, three high-quality images are selected from the new image set as red, green, and blue channels, respectively, to form a pseudo-colour image. The experimental results suggest that the pseudo-colour images show multiple features of the sample and achieve a better image quality.

The thermal response of packaged biconic taper filter with a free spectral range of 1.7 nm is investigated over a temperature range of 0–70°C. The filter length dependence with temperature is estimated from the spectral offset. This device presented thermal stability of 3 × 10⁻³ nm/°C, measured at λ ₀ = 1550 nm.

The authors present an adaptive algorithm based on a non-linear regression model for mitigating time-varying etalon drifts in line-scanned optical absorption spectrometers. By dynamically varying the etalon spectral background using physically realistic degrees of freedom, the authors’ dynamic etalon fitting-routine (DEF-R) significantly increases the spectral baseline recalibration interval as compared to conventional fringe subtraction models. They provide an empirical demonstration of the efficacy of DEF-R using an on-chip 10 cm silicon waveguide for near-infrared methane absorption spectroscopy at 6057 cm⁻¹, which suffers significant etalon spectral noise due to reflections and multi-path interference from stochastic line-edge roughness imperfections. They demonstrate the corresponding improvement in both spectral clean-up and long-term stability via Allan-variance analysis. For the sensor presented here, application of DEF-R enables Gaussian-noise limited performance for more than 10² s and provides almost an order-of-magnitude improvement in stability time with respect to conventional baseline subtraction. Although DEF-R is applied here to an on-chip sensor embodiment, they envision their technique to be applicable to any absorption sensor limited by time-varying etalon drifts.

In this Letter, a multistage energy management system is developed and analysed incorporating the coordination between the tertiary stage and the primary stage. In the tertiary level, a day-ahead peak shaving strategy is developed using the autoregressive moving average and artificial neural network technique. These two techniques are used to predict customer's power demand and photovoltaic power generation, which are fed to a tertiary controller for the day-ahead power demand management. As the peak-power-demand management system is highly dependent on the demand-generation values, any fluctuations and errors in predicted values impact the performance of the peak shaving. The reference power generated from the energy management layer at the tertiary stage is communicated to the local inverter controller at the primary stage. The inverter implements a dq-current controller to track the reference power efficiently.

A novel non-isolated resonant quasi-impedance (quasi-Z)-source network DC–DC converter is proposed. The resonant impedance source network is derived from the quasi-Z-source network by including the autotransformer-based resonant cell instead of the second inductor of the quasi-Z-network. The leakage inductance of the autotransformer and two resonant capacitors connected in series with the autotransformer windings constitute a high-frequency resonant tank. At the same time, the resonant capacitors block the DC-bias current of the autotransformer. The resonant operation with a sinusoidal current of the main switch and diodes enables electromagnetic interference mitigation and improves the efficiency of the converter. Experimental results of a 100 W, 30 V/200 V prototype are presented to verify the analysis results of the proposed converter.

The detection performance of high-frequency surface wave radar (HFSWR) is significantly impacted by ionospheric clutter and sea clutter. In order to suppress the ionospheric clutter, a new method based on the largest Lyapunov exponent prediction algorithm is proposed in this Letter. Firstly, it is demonstrated, for the first time, that the ionospheric clutter from HFSWR is a chaotic dynamical process, and then the largest Lyapunov exponent is estimated using the Wolf algorithm. After verifying the actual data, this suppression algorithm can decrease the amplitude of the ionospheric clutter by at least 30 dB.

In supervised infinite impulse response adaptive filtering, approximate gradient-based approaches are the usual option among optimisation methods. When based on the mean squared error (MSE) criterion, however, these approaches may present biased solutions in noisy scenarios. In that sense, instead of the MSE, the authors propose the use of Shannon's error entropy, an information theoretic learning criterion, which is able to extract higher order statistics from the underlying signals. In particular, a multivariate entropy definition is considered, which is applied to derive a Recursive Prediction Error-based algorithm. The performance analyses are carried out in the context of the supervised channel equalisation problem, with results very favourable to the proposal, in high and low noise level environments.

A discriminative feature extraction method for playback speech detection is proposed, it relies on the finding that frame-wise magnitude-spectrum weight (FWMW) can enlarge the difference between genuine speech and playback speech. The proposed FWMW is obtained by supplying the sum of every frame magnitude spectrum frequency bin as the weight on the frame magnitude spectrum. Then, a new feature based on FWMW is proposed, namely constant-Q weight segmentation coefficients (CQWSCs). The experimental result on ASVspoof 2017 version 2.0 evaluation set using CQWSC indicates that: (i) FWMW can make the proposed feature has more discriminative ability and the equal error rate can decline 15.53 and 19.18% under Gaussian mixture model and deep neural network, respectively, and (ii) CQWSC performs better than some commonly used features.

Total variability model-based i-vector and deep neural network-based embedding x-vector are both widely used for text-independent speaker verification. In this Letter, a novel model is proposed, which can contain information of both i-vector and x-vector by using parallel factor analysis. The authors aim to obtain a linear transformation expression for x-vectors based on background i-vectors and x-vectors, and consider the linearly transformed x-vector as the novel model, thus they name it as -vector. The novel -vector can maximise intra and minimise inner speaker variability, in addition, it can improve the system performance without latency. Experiments were conducted on NIST 2010 dataset, and in terms of equal error rate, they observe up to 37.27 and 53.38% relative improvement of the authors proposed -vector model compared to the i-vector and x-vector models, respectively.

In this Letter, the authors analyse the secrecy outage probability (SOP) over fluctuating two-ray fading channels but with a different definition from the one adopted in Zeng et al. Following the new defined SOP, they derive an analytical closed-form expression for their proposed SOP, as well as an asymptotic formula valid in the high signal-to-noise ratio region of the source to destination link. In the numerical results section, they perform some Monte-Carlo simulations to validate the accuracy of their derived expressions, and also present the probability gap between their proposed SOP and the SOP in Zeng et al. .