Co-frequency and co-time full duplex(CCFD) is an attractive technology for the future wireless communication because of its high spectral efficiency.However,applications of CCFD to mobile network can suffer from stron...Co-frequency and co-time full duplex(CCFD) is an attractive technology for the future wireless communication because of its high spectral efficiency.However,applications of CCFD to mobile network can suffer from strong base station to base station(B2B)interference.In this paper,the authors proposed a design that uses centralized base station(BS)transmit antenna and distributed BS receive antennas,each of which consists of an antennary to perform beamforming that can nullify the B2 B interference.In addition,we proposed a combination algorithm that uses the zero forcing method to cascade the recursive least square(RLS) method for reducing the necessary number of the bits taken to the digital processor.This enables the faster convergence and,thus,allows the transmission of more information bits,compared to the conventional method,for mobile communication.The simulation results confirm this approach for practical application.展开更多
By employing a radio frequency(RF) feedback chain, the self-interference can be canceled efficiently in co-time co-frequency full duplex(CCFD). However, the evitable signal crosstalk which is caused by the imperfect R...By employing a radio frequency(RF) feedback chain, the self-interference can be canceled efficiently in co-time co-frequency full duplex(CCFD). However, the evitable signal crosstalk which is caused by the imperfect RF feedback chain isolation usually damages the self-interference cancelation(SIC) performance. To deal with this problem, firstly, we analyze the impact of RF feedback chain isolation on SIC performance. Then a digital preprocessing scheme with RF feedback chain is proposed in the multiple-antenna CCFD architecture. Using both analytical and experimental methods, we find that the proposed scheme achieves a better performance on SIC.展开更多
软测量技术为工业过程中重要变量及难测变量的预测提供了一个有效的解决办法。然而,由于工业过程的复杂化和高昂的数据获取成本,使得标记数据与未标记数据分布不平衡。此时,构建高性能的软测量模型成为一个挑战。针对这一问题,提出了一...软测量技术为工业过程中重要变量及难测变量的预测提供了一个有效的解决办法。然而,由于工业过程的复杂化和高昂的数据获取成本,使得标记数据与未标记数据分布不平衡。此时,构建高性能的软测量模型成为一个挑战。针对这一问题,提出了一种基于时差的多输出tri-training异构软测量方法。通过构建一种新的tri-training框架,采用多输出的高斯过程回归(multi-output Gaussian process regression,MGPR)、相关向量机(multi-output relevance vector machine,MRVM)、最小二乘支持向量机(multi-output least squares support vector machine,MLSSVM)三种模型作为基线监督回归器,使用标记数据进行训练和迭代;同时,引入时间差分(time difference,TD)改进模型的动态特性,并通过卡尔曼滤波(Kalman filtering,KF)优化模型的参数,提高其预测性能;最后通过模拟污水处理平台(benchmark simulation model 1,BSM1)和实际污水处理厂对该模型进行了验证。结果表明,与传统的软测量建模方法相比,该模型能显著提高数据分布不平衡下软测量模型的自适应性和预测性能。展开更多
基金supported by the National High Technology Research and Development Program of China(Grant No.2014AA01A704)National Natural Science Foundation of China(Grant No.61271203)
文摘Co-frequency and co-time full duplex(CCFD) is an attractive technology for the future wireless communication because of its high spectral efficiency.However,applications of CCFD to mobile network can suffer from strong base station to base station(B2B)interference.In this paper,the authors proposed a design that uses centralized base station(BS)transmit antenna and distributed BS receive antennas,each of which consists of an antennary to perform beamforming that can nullify the B2 B interference.In addition,we proposed a combination algorithm that uses the zero forcing method to cascade the recursive least square(RLS) method for reducing the necessary number of the bits taken to the digital processor.This enables the faster convergence and,thus,allows the transmission of more information bits,compared to the conventional method,for mobile communication.The simulation results confirm this approach for practical application.
基金supported by the National Natural Science Foundation of China under Grants No.61601064,No.61471108,No.61601065,and No.41404102supported by the Sichuan Youth Science and Technology Foundation under Grant No.2016JQ0012
文摘By employing a radio frequency(RF) feedback chain, the self-interference can be canceled efficiently in co-time co-frequency full duplex(CCFD). However, the evitable signal crosstalk which is caused by the imperfect RF feedback chain isolation usually damages the self-interference cancelation(SIC) performance. To deal with this problem, firstly, we analyze the impact of RF feedback chain isolation on SIC performance. Then a digital preprocessing scheme with RF feedback chain is proposed in the multiple-antenna CCFD architecture. Using both analytical and experimental methods, we find that the proposed scheme achieves a better performance on SIC.
文摘软测量技术为工业过程中重要变量及难测变量的预测提供了一个有效的解决办法。然而,由于工业过程的复杂化和高昂的数据获取成本,使得标记数据与未标记数据分布不平衡。此时,构建高性能的软测量模型成为一个挑战。针对这一问题,提出了一种基于时差的多输出tri-training异构软测量方法。通过构建一种新的tri-training框架,采用多输出的高斯过程回归(multi-output Gaussian process regression,MGPR)、相关向量机(multi-output relevance vector machine,MRVM)、最小二乘支持向量机(multi-output least squares support vector machine,MLSSVM)三种模型作为基线监督回归器,使用标记数据进行训练和迭代;同时,引入时间差分(time difference,TD)改进模型的动态特性,并通过卡尔曼滤波(Kalman filtering,KF)优化模型的参数,提高其预测性能;最后通过模拟污水处理平台(benchmark simulation model 1,BSM1)和实际污水处理厂对该模型进行了验证。结果表明,与传统的软测量建模方法相比,该模型能显著提高数据分布不平衡下软测量模型的自适应性和预测性能。
