In this paper, we investigate a resource allocation issue in OFDMA-based decode-and-forward cooperative multiuser networks and propose joint subcarrier and power allocation schemes. The optimal solution of this combin...In this paper, we investigate a resource allocation issue in OFDMA-based decode-and-forward cooperative multiuser networks and propose joint subcarrier and power allocation schemes. The optimal solution of this combinable allocation shows high computational complexity, so we allocate subcarriers and power separately. At firstly, we distribute subcarriers to relays and users under the assumption of equal power distribution. Here, we propose an equal capacity increment （ECI） allocation strategy to achieve tradeoff between total throughput and fairness. To further improve the system performance, we introduce threshold into ECI strategy, named ECI strategy with threshold （ECI-T）, where subcarriers with bad performance are prevented from transmitting. Subsequently, a water-filling method is adopted to distribute the power to cooperative links in order to fully utilize the limited power. Simulation results show that system performance of the proposed schemes is significantly enhanced compared with an existing resource allocation scheme. Besides, the resource allocation schemes with the water- filling method notably outperform schemes with equal power allocation.展开更多
加公司以人工智能指导油田"低盐度注水"加拿大卡尔加里(Calgary)计算机建模集团公司于2020年初推出利用人工智能进行油气田"低盐度注水"(LSWI,Low-Salinity Water Injection)优化,并在巴西Namorado油田进行了实际应...加公司以人工智能指导油田"低盐度注水"加拿大卡尔加里(Calgary)计算机建模集团公司于2020年初推出利用人工智能进行油气田"低盐度注水"(LSWI,Low-Salinity Water Injection)优化,并在巴西Namorado油田进行了实际应用,效果显著.加拿大公司"低盐度注水"(LSWI)方法,是结合"组合模拟"和一种数学优化工具,首先利用人工智能进行注水油气田未来产值的净现值(NPV)评价;其次,技术人员利用多元地质统计方法,根据油田历史上开采模型进行拟合运算,并且考虑地下油藏中相关不确定性,经过调整得出最佳油气田注水方案.展开更多
基金Supported by the National High Technology Research and Development Programme of China （No. 2009AA01Z247, No. 2007AA01Z265）, and the National Natural Science Foundation of China （No. 60972076）
文摘In this paper, we investigate a resource allocation issue in OFDMA-based decode-and-forward cooperative multiuser networks and propose joint subcarrier and power allocation schemes. The optimal solution of this combinable allocation shows high computational complexity, so we allocate subcarriers and power separately. At firstly, we distribute subcarriers to relays and users under the assumption of equal power distribution. Here, we propose an equal capacity increment （ECI） allocation strategy to achieve tradeoff between total throughput and fairness. To further improve the system performance, we introduce threshold into ECI strategy, named ECI strategy with threshold （ECI-T）, where subcarriers with bad performance are prevented from transmitting. Subsequently, a water-filling method is adopted to distribute the power to cooperative links in order to fully utilize the limited power. Simulation results show that system performance of the proposed schemes is significantly enhanced compared with an existing resource allocation scheme. Besides, the resource allocation schemes with the water- filling method notably outperform schemes with equal power allocation.
文摘加公司以人工智能指导油田"低盐度注水"加拿大卡尔加里(Calgary)计算机建模集团公司于2020年初推出利用人工智能进行油气田"低盐度注水"(LSWI,Low-Salinity Water Injection)优化,并在巴西Namorado油田进行了实际应用,效果显著.加拿大公司"低盐度注水"(LSWI)方法,是结合"组合模拟"和一种数学优化工具,首先利用人工智能进行注水油气田未来产值的净现值(NPV)评价;其次,技术人员利用多元地质统计方法,根据油田历史上开采模型进行拟合运算,并且考虑地下油藏中相关不确定性,经过调整得出最佳油气田注水方案.
