Cooperative communication has used to be a hot topic and it has been studied extensively in the past 10 years, but in recent years, it becomes less likely to find substantial innovation in this field as before. In this paper, we propose a new hybrid decode-forward and amplify-forward with non-orthogonal multiple access (NOMA) (HDAF-NOMA) transmission scheme for a cellular system with multiple relays. To the best of our knowledge, this is the first work that attempts to integrate decode-forward (DF), amplifyforward, and NOMA into one strategy design to improve system performance. To verify the performance advantages, the proposed HDAF-NOMA scheme is compared with the other four traditional schemes in terms of channel capacity and average system throughput, and the optimal number of selected DF relays is also determined for the HDAF-NOMA scheme. Simulation results show that compared with the traditional schemes, the proposed HDAF-NOMA scheme can achieve larger sum channel capacity for the transmission of x 1 and x 2 , and it can also achieve larger average system throughput at high SNR region. INDEX TERMSNOMA, non-orthogonal multiple access, DF, decode-forward, AF, amplify-forward, relay. YANG LIU received the B.Eng. degree in automation from Tsinghua University, Beijing, China, in 1997, the M.Eng. degree in electrical engineering and electronics from Nanyang Technological University, Singapore, in 2002, and the Ph.D. degree in information and communication system from the Beijing University of Posts and Telecommunications (BUPT), China, in 2011. He is currently an Assistant Professor with the School of Electronic Engineering, BUPT. His research interests include 5G Communication technologies such as NOMA, MIMO, broadcast/multicast, cooperative communications, and interference management. GAOFENG PAN received the B.Sc. degree in communication engineering from Zhengzhou University, Zhengzhou, China, in 2005, and the Ph.D. degree in communication and informa-

Zero-shot learning (ZSL) has been widely researched and get successful in machine learning. Most existing ZSL methods aim to accurately recognize objects of unseen classes by learning a shared mapping from the feature space to a semantic space. However, such methods did not investigate in-depth whether the mapping can precisely reconstruct the original visual feature. Motivated by the fact that the data have low intrinsic dimensionality e.g. low-dimensional subspace. In this paper, we formulate a novel framework named Lowrank Embedded Semantic AutoEncoder (LESAE) to jointly seek a low-rank mapping to link visual features with their semantic representations. Taking the encoder-decoder paradigm, the encoder part aims to learn a low-rank mapping from the visual feature to the semantic space, while decoder part manages to reconstruct the original data with the learned mapping. In addition, a non-greedy iterative algorithm is adopted to solve our model. Extensive experiments on six benchmark datasets demonstrate its superiority over several state-ofthe-art algorithms.

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Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) utilizes large antenna arrays and is considered a promising technology for fifth-generation (5G) and beyond wireless communication systems. However, the high-power consumption of the radio-frequency (RF) chains makes it infeasible. To solve this problem, hybrid precoding is proposed, which is a combination of analog and digital precoding. The fully connected architecture hybrid precoding still requires a large number of phase shifters (PSs). The sub-connected architecture can greatly reduce the required power consumption, and however, it cannot obtain a satisfactory achievable rate. To avoid the high energy consumption and obtain a high resolution, we propose a novel partly connected architecture in this paper. In addition, we propose an energy-efficient successive interference cancelation (SIC) hybrid precoding based on the partly connected architecture, which transforms the problem of maximizing the total achievable rate with non-convex constraints into a series of sub-rate optimization problems. Furthermore, a low-complexity energy-efficient SIC hybrid precoding based on the partly connected architecture is developed, which uses the partial singular value decomposition (SVD) to realize the sub-rate optimization and significantly reduce the complexity. Theoretical analysis demonstrates the superiority of the proposed hybrid precoding in terms of complexity. The simulation results indicate that the proposed hybrid precoding algorithms enjoy better energy efficiency and achievable rate performance than some recently proposed hybrid precoding algorithms.INDEX TERMS Millimeter wave communication, MIMO, energy efficiency, complexity theory, hybrid precoding.

Both SVC (Static Var Compensator) and STATCOM (Static Synchronous Compensator) are important equipment of reactive compensation, which are compared in voltage supporting, improving the transient stability and transmission limit, and damping low frequency oscillation. Simulation results are presented as high capacity static var system for SVC or STATCOM is placed on transmission path of power system. Firstly, single SVC and STATCOM are limited in voltage supporting after fault occurrence, but STATCOM is little better than SVC. Secondly, STATCOM is much better than SVC in improving the transient stability and transmission limit. Thirdly, on the damping low frequency oscillation, STATCOM is much better than SVC as SVC and STATCOM have the same capacity, and performs similarly with SVC as the two have the same controllable capacity. Lastly, the results also indicate that dynamical response speed effects the control result little though STATCOM responses much faster than SVC.