In this communication, a metasurface-based decoupling method (MDM) is proposed to reduce the mutual couplings at two independent bands of two coupled MIMO antennas. The metasurface superstrate is composed of pairs of non-uniform cut wires with two different lengths. It is compact in size and effective in decoupling two nearby dual-band patch antennas that are strongly coupled in H-plane with the edge-to-edge spacing of only 0.008 wavelengths at low frequency band (LB). The antenna is fabricated and measured and the results show that the isolation between two dual-band antennas can be improved to more than 25 dB at both 2.5-2.7 GHz and 3.4-3.6 GHz bands while their reflection coefficients remain to be below -10 dB after the metasurface superstrate is introduced. Moreover, the total efficiency is improved by about 15% in the low band and the envelope correlation coefficient (ECC) between the two antennas is reduced from 0.46 to 0.08 at 2.6 GHz and 0.08 to 0.01 at 3.5 GHz. The proposed method can find plenty of applications in dual-band MIMO and 5G communication systems.

This paper proposes a dual-band eight-antenna array for multiple input and multiple output (MIMO) applications in 5G mobile terminals. The designed MIMO antenna array comprises eight L-shaped slot antennas based on stepped impedance resonators (SIRs). The required dual-resonance can be obtained by adjusting the impedance ratio of the SIR, and good impedance matching can be ensured for each antenna element by tuning the position of the microstrip feed line. The experimental results show that a measured return loss of higher than 10 dB and a measured inter-element isolation of greater than 11.2 dB have been obtained for each antenna element with a simulated total efficiency of larger than 51% across the long term evolution (LTE) band 42 (3400–3600 MHz) and LTE band 46 (5150–5925 MHz). In addition, the measured envelope correlation coefficient (ECC) is lower than 0.1 between arbitrary two antenna elements and the proposed MIMO antenna array realizes a simulated channel capacity of higher than 36.9 bps/Hz within both operation bands. Furthermore, the MIMO antenna array can maintain acceptable radiation and MIMO performance in the presence of specific anthropomorphic mannequin (SAM) head and human hands.

A ceramic superstrate-based decoupling method (CSDM) is proposed to reduce the mutual coupling between two closely packed dipole antennas while maintaining cross-polarization suppression. Compared with other superstrate-based methods, this proposed method can effectively reduce the mutual coupling between the antennas without using any periodic structures on the superstrate. The ceramic superstrate is a 2 mm thin slab with a relative dielectric constant of 20.5 and is suspended over the antennas coupled in H-plane with the spacing of only 0.28 wavelength at 3.5 GHz. It is demonstrated by both simulation and measurement that the isolation between two dipole antennas can be improved from 10 dB to more than 25 dB within the operation band while their reflection coefficients remain to be below -10 dB after the ceramic superstrate is introduced. The radiation patterns of the antenna maintain stable at different operation frequencies within the band of interest and the peak gain has increased by around 1.5 dB. Meanwhile, the total efficiency is enhanced by about 15% and the envelope correlation coefficient (ECC) between the two antennas is reduced from 0.7 to 0.4.

Correntropy is a local similarity measure defined in kernel space, and the maximum correntropy criterion (mcc) has been successfully applied in many areas of signal processing and machine learning in recent years. The kernel function in correntropy is usually restricted to the Gaussian function with the center located at zero. However, the zero-mean Gaussian function may not be a good choice for many practical applications. In this letter, we propose an extended version of correntropy, whose center can be located at any position. Accordingly, we propose a new optimization criterion called maximum correntropy criterion with variable center (MCC-VC). We also propose an efficient approach to optimize the kernel width and center location in the MCC-VC. Simulation results of regression with linear-in-parameter (LIP) models confirm the desirable performance of the new method.

In this paper, an antenna interference cancellation chip (AICC) with a high-pass response is proposed to mitigate the mutual coupling of two antennas resonating in contiguous frequency bands. Using the most up-to-date low temperature co-fired ceramic (LTCC) technology, the chip only occupies a compact volume of 1.6 × 0.8 × 0.6 mm ³ . Two external tuning capacitors and two shunt inductors together with the LTCC AICC device which are in shunt with two coupled antennas, are able to improve the antenna isolation near band-edge by more than 15 dB without sacrificing antenna performance in its useful resonating bands. The high-pass property of the AICC device prevents the decoupling design near 2.4GHz affecting the successful operation of GPS at 1.575 GHz. The superiority of the proposed method is verified with active measurement of a Mi-Fi (mobile Wi-Fi) device in Wi-Fi hotspot mode using the AICC device. The proposed AICC device and corresponding decoupling method with the device can find plenty of applications in long-term-evolution and future 5G wireless platforms.

A blocked proportionate normalized maximum correntropy criterion (MCC) (PNMCC) is presented to improve the estimation behavior of the traditional MCC algorithm for identifying the blocked sparse systems. The proposed blocked MCC is implemented by constructing a new cost function based on a hybrid-norm constraint of the filter coefficient vector to adaptively utilize the cluster-sparse characteristic of unknown systems, denoting as hybrid-norm constrained PNMCC (HNC-PNMCC). The proposed HNC-PNMCC algorithm is achieved by using the basis pursuit (BP). Various simulations are brought out to confirm the validity of the HNC-PNMCC. Simulation results indicate that the HNC-PNMCC is better than the PNMCC, MCC and sparse MCC with respect to the estimation performance for the cluster-sparse system identification under the impulsive noises.