针对设备到设备(device to device, D2D)直连技术复用蜂窝网络资源导致用户间干扰的问题,提出了一种基于K-means与Gale-Shapley稳定匹配算法的D2D通信干扰管理资源分配方案。通过分析信号与干扰加噪声比公式,采用K-means聚类算法进行用...针对设备到设备(device to device, D2D)直连技术复用蜂窝网络资源导致用户间干扰的问题,提出了一种基于K-means与Gale-Shapley稳定匹配算法的D2D通信干扰管理资源分配方案。通过分析信号与干扰加噪声比公式,采用K-means聚类算法进行用户分组,降低用户间干扰,实现多对一资源复用;为提高通信系统容量且保证用户的公平性,采用Gale-Shapley稳定匹配算法在用户分组基础上实现信道资源共享。仿真结果表明,与基于贪婪的图着色资源分配算法相比,本文算法在保证系统容量基本稳定的情况下,系统干扰降低了10%~30%。展开更多
Based on the daily sea surface wind field prediction data of Japan Meteorological Agency(JMA) forecast model,National Centers for Environmental Prediction(NCEP GFS) model and U.S.Navy Operational Global Atmospheric Pr...Based on the daily sea surface wind field prediction data of Japan Meteorological Agency(JMA) forecast model,National Centers for Environmental Prediction(NCEP GFS) model and U.S.Navy Operational Global Atmospheric Prediction System(NOGAPS) model at 12:00 UTC from June 28 to August 10 in 2009,the bias-removed ensemble mean(BRE) was used to do the forecast test on the sea surface wind fields,and the root-mean-square error(RMSE) was used to test and evaluate the forecast results.The results showed that the BRE considerably reduced the RMSEs of 24 and 48 h sea surface wind field forecasts,and the forecast skill was superior to that of the single model forecast.The RMSE decreases in the south of central Bohai Sea and the middle of the Yellow Sea were the most obvious.In addition,the BRE forecast improved evidently the forecast skill of the gale process which occurred during July 13-14 and August 7 in 2009.The forecast accuracy of the wind speed and the gale location was also improved.展开更多
文摘针对设备到设备(device to device, D2D)直连技术复用蜂窝网络资源导致用户间干扰的问题,提出了一种基于K-means与Gale-Shapley稳定匹配算法的D2D通信干扰管理资源分配方案。通过分析信号与干扰加噪声比公式,采用K-means聚类算法进行用户分组,降低用户间干扰,实现多对一资源复用;为提高通信系统容量且保证用户的公平性,采用Gale-Shapley稳定匹配算法在用户分组基础上实现信道资源共享。仿真结果表明,与基于贪婪的图着色资源分配算法相比,本文算法在保证系统容量基本稳定的情况下,系统干扰降低了10%~30%。
基金Supported by Chinese Meteorological Administration's Special Funds(Meteorology) for Scientific Research on Public Causes( GYHY200906007)Gale Forecast Item of the Shengli Oil Field Observatory (2008001)~~
文摘Based on the daily sea surface wind field prediction data of Japan Meteorological Agency(JMA) forecast model,National Centers for Environmental Prediction(NCEP GFS) model and U.S.Navy Operational Global Atmospheric Prediction System(NOGAPS) model at 12:00 UTC from June 28 to August 10 in 2009,the bias-removed ensemble mean(BRE) was used to do the forecast test on the sea surface wind fields,and the root-mean-square error(RMSE) was used to test and evaluate the forecast results.The results showed that the BRE considerably reduced the RMSEs of 24 and 48 h sea surface wind field forecasts,and the forecast skill was superior to that of the single model forecast.The RMSE decreases in the south of central Bohai Sea and the middle of the Yellow Sea were the most obvious.In addition,the BRE forecast improved evidently the forecast skill of the gale process which occurred during July 13-14 and August 7 in 2009.The forecast accuracy of the wind speed and the gale location was also improved.
