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.

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Water is an extremely important resource for the man, thus, to improve the reliability of water supply pipeline is very useful. In this paper, a remote monitoring system for water supply pipeline based on ZigBee and WiFi is designed. The system can effectively resolve the problems of poor real-time performance, high cost, and labor intensiveness of conventional water supply pipeline leakage monitoring systems. The system can be used to detect leaks in the water supply pipe based on the transient change of the negative pressure in the pipe. When the water supply pipeline leaks, the sound signal in the pipeline is collected, and the acoustic signal data are transmitted to the data processing center in real time through the wireless sensor network and the WiFi network. By analyzing and processing these data in the host computer, the leak is located and the goal of monitoring the water supply pipeline in real time is eventually reached.