Based on 2012 input-output table of Shandong province and the official statistics, this article uses the input-output analysis method to build the input-output table. On the basis of the development of service industr...Based on 2012 input-output table of Shandong province and the official statistics, this article uses the input-output analysis method to build the input-output table. On the basis of the development of service industry in Shandong province's ability, we make a theoretical analysis framework of a comprehensive in-depth analysis on pull employment, creatively will cost tax rate, fully and completely labor capital and the combination of both the industry development space. So that the industry's ability to pull the employment can be considered, and to realize rapid and sustained development of service industry in Shandong province.展开更多
Under the pressure of sustained growth in energy consumption in China,the implementation of a carbon pricing mechanism is an effective economic policy measure for promoting emission reduction,as well as a hotspot of r...Under the pressure of sustained growth in energy consumption in China,the implementation of a carbon pricing mechanism is an effective economic policy measure for promoting emission reduction,as well as a hotspot of research among scholars and policy makers.In this paper,the effects of carbon prices on Beijing's economy are analyzed using input-output tables.The carbon price costs are levied in accordance with the products'embodied carbon emission.By calculation,given the carbon price rate of 10 RMB/t-CO_2,the total carbon costs of Beijing account for approximately 0.22-0.40%of its gross revenue the same year.Among all industries,construction bears the largest carbon cost Among export sectors,the coal mining and washing industry has much higher export carbon price intensity than other industries.Apart from traditional energy-intensive industries,tertiary industry,which accounts for more than 70%of Beijing's economy,also bears a major carbon cost because of its large economic size.However,from 2007 to 2010,adjustment of the investment structure has reduced the emission intensity in investment sectors,contributing to the reduction of overall emissions and carbon price intensity.展开更多
Massive multiple-input multiple-output(MIMO) system is capable of substantially improving the spectral efficiency as well as the capacity of wireless networks relying on equipping a large number of antenna elements at...Massive multiple-input multiple-output(MIMO) system is capable of substantially improving the spectral efficiency as well as the capacity of wireless networks relying on equipping a large number of antenna elements at the base stations. However, the excessively high computational complexity of the signal detection in massive MIMO systems imposes a significant challenge for practical hardware implementations. In this paper, we propose a novel minimum mean square error(MMSE) signal detection using the accelerated overrelaxation(AOR) iterative method without complicated matrix inversion, which is capable of reducing the overall complexity of the classical MMSE algorithm by an order of magnitude. Simulation results show that the proposed AOR-based method can approach the conventional MMSE signal detection with significant complexity reduction.展开更多
基金supported by the National Social Science Fund of China (Grant No. 15CGL048)
文摘Based on 2012 input-output table of Shandong province and the official statistics, this article uses the input-output analysis method to build the input-output table. On the basis of the development of service industry in Shandong province's ability, we make a theoretical analysis framework of a comprehensive in-depth analysis on pull employment, creatively will cost tax rate, fully and completely labor capital and the combination of both the industry development space. So that the industry's ability to pull the employment can be considered, and to realize rapid and sustained development of service industry in Shandong province.
基金The authors would like to thank Key Projects in the National Science&Technology Pillar Program during the Twelfth Five Year Plan Period[grant number 2012BAC20B03]Beijing Natural Science Foundation[grant number 9112008]for supporting this research
文摘Under the pressure of sustained growth in energy consumption in China,the implementation of a carbon pricing mechanism is an effective economic policy measure for promoting emission reduction,as well as a hotspot of research among scholars and policy makers.In this paper,the effects of carbon prices on Beijing's economy are analyzed using input-output tables.The carbon price costs are levied in accordance with the products'embodied carbon emission.By calculation,given the carbon price rate of 10 RMB/t-CO_2,the total carbon costs of Beijing account for approximately 0.22-0.40%of its gross revenue the same year.Among all industries,construction bears the largest carbon cost Among export sectors,the coal mining and washing industry has much higher export carbon price intensity than other industries.Apart from traditional energy-intensive industries,tertiary industry,which accounts for more than 70%of Beijing's economy,also bears a major carbon cost because of its large economic size.However,from 2007 to 2010,adjustment of the investment structure has reduced the emission intensity in investment sectors,contributing to the reduction of overall emissions and carbon price intensity.
基金supported by the key project of the National Natural Science Foundation of China (No. 61431001)Huawei Innovation Research Program, the 5G research program of China Mobile Research Institute (Grant No. [2015] 0615)+2 种基金the open research fund of National Mobile Communications Research Laboratory Southeast University (No.2017D02)Key Laboratory of Cognitive Radio and Information Processing, Ministry of Education (Guilin University of Electronic Technology)the Foundation of Beijing Engineering and Technology Center for Convergence Networks and Ubiquitous Services, and Keysight
文摘Massive multiple-input multiple-output(MIMO) system is capable of substantially improving the spectral efficiency as well as the capacity of wireless networks relying on equipping a large number of antenna elements at the base stations. However, the excessively high computational complexity of the signal detection in massive MIMO systems imposes a significant challenge for practical hardware implementations. In this paper, we propose a novel minimum mean square error(MMSE) signal detection using the accelerated overrelaxation(AOR) iterative method without complicated matrix inversion, which is capable of reducing the overall complexity of the classical MMSE algorithm by an order of magnitude. Simulation results show that the proposed AOR-based method can approach the conventional MMSE signal detection with significant complexity reduction.
