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In this paper, a transmitting power allocation strategy for users jointed together pre-coding is presented to eliminate interusers interference and improve the energy efficiency of Massive MIMO systems. The power allocation model is formularized as energy efficiency optimization problem of the users ' power and circuit power consumption. We demonstrate that energy efficiency is a convex function of users' power. In order to reduce the complexity of traditional power allocation algorithm, an iterative power allocation algorithm based on convex optimization theory is proposed to figure out the optimal value of each user power. The simulation results show that the iterative algorithm can effectively improve the energy efficiency of Massive MIMO systems. 一 Corresponding author. Yuanyuan,Ren,

The uneven distribution of species diversity on earth, with mountainous regions housing half of the high species diversity areas, makes mountain ecosystems vital to biodiversity conservation. The Panorpidae are ecological indicators, ideal for studying the impact of climate change on potential insect distribution. This study examines the impact of environmental factors on the distribution of the Panorpidae and analyzes how their distribution has changed over three historical periods, the Last Interglacial (LIG), the Last Glacial Maximum (LGM), and Current. The MaxEnt model is used to predict the potential distribution area of Panorpidae based on global distribution data. The results show that precipitation and elevation are the primary factors affecting species richness, and the suitable areas for Panorpidae are distributed in southeastern North America, Europe, and southeastern Asia. Throughout the three historical periods, there was an initial increase followed by a decrease in the area of suitable habitats. During the LGM period, there was a maximum range of suitable habitats for cool-adapted insects, such as scorpionflies. Under the scenarios of global warming, the suitable habitats for Panorpidae would shrink, posing a challenge to the conservation of biodiversity. The study provides insights into the potential geographic range of Panorpidae and helps understand the impact of climate change on their distribution.

In the Multi-user Generalized Spatial Modulation (MU-GSM) System, as channel gain matrix isn't in full rank, conventional linear precoding algorithms can't be directly applied in this system. Given this, a method called Multi-user Generalized Spatial Modulation Partial Linear Precoding (MU-GSM-PLP) is proposed for MU-GSM system. MU-GSM system is established in this method that the antennas at the transmitter are grouped and Generalized Spatial Modulation (GSM) is adopted in each antenna group. Then, dimensional reduction is made on channel gain matrix as well as transmitting signal matrix, and the equivalent channel gain matrix and transmitting signal matrix are obtained. Finally, Partial Linear Precoding (PLP) precoding is carried out by utilizing the equivalent channel gain matrix. The simulation results show that this method have a better error performance and higher system capacity.

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In previous works, they mainly concern on optimizing transmitted antenna to maximize energy efficiency(EE). But the transmitted power optimization is also necessary for the improvement of EE. Because too large or too small transmitted power will lead to the decline of EE. This paper proposes a joint optimal transmitted power and transmitted antenna number iterative algorithm to maximize EE for massive MIMO system. Firstly a good approximation of multiuser interference(MUI) is derived. Then we demonstrate that EE is a concave function of the transmitted power and the transmitted antenna number. So for a given number of transmitted antenna, we can get the optimal transmitted power. An iterative algorithm that can maximize EE is proposed. The monte carlo simulations verify the effectiveness of the proposed algorithm.