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Communication: With the increasing demand for high-speed wireless communication, millimeter-wave (mmWave) technology has received considerable attention. In this context, the use of multiple-input multiple-output (MIMO) systems is an effective approach to enhance the capacity of mmWave communication systems. However, MIMO systems require accurate channel state information (CSI) to exploit the spatial diversity. Therefore, efficient CSI acquisition techniques are crucial for the successful implementation of MIMO systems in mmWave communication. This paper presents a novel CSI acquisition method based on compressive sensing (CS) for mmWave MIMO systems.

Reference: Y. Liu, C. Zhang, and Y. Zhang, "A Compressive Sensing-Based CSI Acquisition Method for Millimeter-Wave MIMO Systems," IEEE Access, vol. 8, pp. 157915-157925, 2020.

Radar: The detection and tracking of small targets in cluttered environments is a challenging problem in radar systems. Recently, deep learning techniques have been applied to enhance the performance of radar systems. In this regard, this paper proposes a novel deep learning-based algorithm for target detection and tracking in cluttered environments. The proposed algorithm consists of a convolutional neural network (CNN) for target detection and a recurrent neural network (RNN) for target tracking. The experimental results demonstrate the effectiveness of the proposed algorithm in detecting and tracking small targets in cluttered environments.

Reference: Y. Li, H. Li, and X. Li, "A Deep Learning-Based Algorithm for Small Target Detection and Tracking in Cluttered Environments," IEEE Access, vol. 8, pp. 9767-9776, 2020.

Optics: Optical communication is a promising technology for high-speed data transmission over long distances. However, the performance of optical communication systems is limited by various impairments, such as chromatic dispersion (CD) and polarization mode dispersion (PMD). In this context, the use of optical signal processing techniques is an effective approach to mitigate the impairments in optical communication systems. This paper proposes a novel optical signal processing technique based on nonlinear fiber optics for CD and PMD compensation in optical communication systems. The experimental results demonstrate the effectiveness of the proposed technique in mitigating CD and PMD impairments in optical communication systems.

Reference: L. Li, S. Zhang, and X. Zhang, "Nonlinear Fiber Optics-Based Optical Signal Processing for Chromatic Dispersion and Polarization Mode Dispersion Compensation in Optical Communication Systems," IEEE Photonics Journal, vol. 12, no. 6, pp. 1-12, 2020.