针对去蜂窝(cell free,CF)大规模多输入多输出(multiple-input multiple-output,MIMO)系统中存在严重的导频污染问题,提出了一种基于位置分配的贪婪导频分配功率控制算法(greedy pilot assignment based on location with pilot power c...针对去蜂窝(cell free,CF)大规模多输入多输出(multiple-input multiple-output,MIMO)系统中存在严重的导频污染问题,提出了一种基于位置分配的贪婪导频分配功率控制算法(greedy pilot assignment based on location with pilot power control,GPABL with PPC).首先,遵循相邻用户不分配相同导频序列的原则进行贪婪导频分配(greedy pilot assignment,GPA);然后,在导频分配的基础上叠加了导频功率控制,选择合理的导频功率控制系数减小信道估计的均方误差.仿真结果表明,将两种方式结合起来进行导频优化,系统的吞吐能力有所提升.展开更多
This paper mainly elaborates the studies of channel estimation and downlink data transmission in Massive MIMO. As there are different types of interference in single-cell and multi-cell systems, this paper establishes...This paper mainly elaborates the studies of channel estimation and downlink data transmission in Massive MIMO. As there are different types of interference in single-cell and multi-cell systems, this paper establishes different models for them separately. In terms of uplink training, for getting channel state information, we introduce LS and MMSE channel estimation algorithms and make a comparison between them. At the same time, the problem of pilot contamination is solved by cell classification and pilot identification. Next, this paper defines mathematical models for downlink data transmission. We use pre-coding methods (including Zero-forcing and Maximal Ratio Combining schemes) and optimize power distribution to improve channel capacity and transmission rate. Furthermore, this paper provides numerical results to show the simulation performance in both single-cell and multi-cell systems and extends to prospects in the future.展开更多
Massive Multiple-Input-Multiple-Output(MIMO)is a promising technology to meet the demand for the connection of massive devices and high data capacity for mobile networks in the next generation communication system.How...Massive Multiple-Input-Multiple-Output(MIMO)is a promising technology to meet the demand for the connection of massive devices and high data capacity for mobile networks in the next generation communication system.However,due to the massive connectivity of mobile devices,the pilot contamination problem will severely degrade the communication quality and spectrum efficiency of the massive MIMO system.We propose a deep Monte Carlo Tree Search(MCTS)-based intelligent Pilot-power Allocation Scheme(iPAS)to address this issue.The core of iPAS is a multi-task deep reinforcement learning algorithm that can automatically learn the radio environment and make decisions on the pilot sequence and power allocation to maximize the spectrum efficiency with self-play training.To accelerate the searching convergence,we introduce a Deep Neural Network(DNN)to predict the pilot sequence and power allocation actions.The DNN is trained in a self-supervised learning manner,where the training data is generated from the searching process of the MCTS algorithm.Numerical results show that our proposed iPAS achieves a better Cumulative Distribution Function(CDF)of the ergodic spectral efficiency compared with the previous suboptimal algorithms.展开更多
In this paper, in order to increase system capacity and reduce the transmitting power of the user's equipment, we propose a efficient power estimation algorithm consisting of a modified open-loop power control (OL...In this paper, in order to increase system capacity and reduce the transmitting power of the user's equipment, we propose a efficient power estimation algorithm consisting of a modified open-loop power control (OLPC) and closed-loop power control (CLPC) for mobile satellite communications systems. The improved CLPC scheme, combining delay compensation algorithms and pilot diversity, is mainly applied to the ancillary ter-restrial component (ATC). ATC link in urban areas, because it is more suitable to the short round-trip delay (RTD). In the case of rural areas, where ATCs are not deployed or where a signal is not received from ATCs, transmit power monitoring equipment and OLPC schemes using efficient pilot diversity are combined and ap-plied to the link between the user's equipment and the satellite. Two modified power control schemes are ap-plied equally to the boundary areas where two kinds of signals are received in order to ensure coverage conti-nuity. Simulation results show that the improved power control scheme has good performance compared to conventional power control schemes in a geostationary earth orbit (GEO) satellite system utilizing ATCs.展开更多
This article proposes a new algorithm to improve the rate control efficiency of enhanced reverse link medium access control （RLMAC） in the code division multiple access （CDMA） 1x EV-DO release A（Rev. A） system. ...This article proposes a new algorithm to improve the rate control efficiency of enhanced reverse link medium access control （RLMAC） in the code division multiple access （CDMA） 1x EV-DO release A（Rev. A） system. The new algorithm brings reverse access terminal （AT） pilot power to the RLMAC rate control procedure and makes it easier for a low pilot power user to increase its data rate when the system is slightly loaded and harder to decrease its date rate when the system is heavily loaded. Numerical results of system level simulations show that the new algorithm can bring higher system throughput, lower AT transmission power, and lower system load.展开更多
文摘针对去蜂窝(cell free,CF)大规模多输入多输出(multiple-input multiple-output,MIMO)系统中存在严重的导频污染问题,提出了一种基于位置分配的贪婪导频分配功率控制算法(greedy pilot assignment based on location with pilot power control,GPABL with PPC).首先,遵循相邻用户不分配相同导频序列的原则进行贪婪导频分配(greedy pilot assignment,GPA);然后,在导频分配的基础上叠加了导频功率控制,选择合理的导频功率控制系数减小信道估计的均方误差.仿真结果表明,将两种方式结合起来进行导频优化,系统的吞吐能力有所提升.
文摘This paper mainly elaborates the studies of channel estimation and downlink data transmission in Massive MIMO. As there are different types of interference in single-cell and multi-cell systems, this paper establishes different models for them separately. In terms of uplink training, for getting channel state information, we introduce LS and MMSE channel estimation algorithms and make a comparison between them. At the same time, the problem of pilot contamination is solved by cell classification and pilot identification. Next, this paper defines mathematical models for downlink data transmission. We use pre-coding methods (including Zero-forcing and Maximal Ratio Combining schemes) and optimize power distribution to improve channel capacity and transmission rate. Furthermore, this paper provides numerical results to show the simulation performance in both single-cell and multi-cell systems and extends to prospects in the future.
文摘Massive Multiple-Input-Multiple-Output(MIMO)is a promising technology to meet the demand for the connection of massive devices and high data capacity for mobile networks in the next generation communication system.However,due to the massive connectivity of mobile devices,the pilot contamination problem will severely degrade the communication quality and spectrum efficiency of the massive MIMO system.We propose a deep Monte Carlo Tree Search(MCTS)-based intelligent Pilot-power Allocation Scheme(iPAS)to address this issue.The core of iPAS is a multi-task deep reinforcement learning algorithm that can automatically learn the radio environment and make decisions on the pilot sequence and power allocation to maximize the spectrum efficiency with self-play training.To accelerate the searching convergence,we introduce a Deep Neural Network(DNN)to predict the pilot sequence and power allocation actions.The DNN is trained in a self-supervised learning manner,where the training data is generated from the searching process of the MCTS algorithm.Numerical results show that our proposed iPAS achieves a better Cumulative Distribution Function(CDF)of the ergodic spectral efficiency compared with the previous suboptimal algorithms.
文摘In this paper, in order to increase system capacity and reduce the transmitting power of the user's equipment, we propose a efficient power estimation algorithm consisting of a modified open-loop power control (OLPC) and closed-loop power control (CLPC) for mobile satellite communications systems. The improved CLPC scheme, combining delay compensation algorithms and pilot diversity, is mainly applied to the ancillary ter-restrial component (ATC). ATC link in urban areas, because it is more suitable to the short round-trip delay (RTD). In the case of rural areas, where ATCs are not deployed or where a signal is not received from ATCs, transmit power monitoring equipment and OLPC schemes using efficient pilot diversity are combined and ap-plied to the link between the user's equipment and the satellite. Two modified power control schemes are ap-plied equally to the boundary areas where two kinds of signals are received in order to ensure coverage conti-nuity. Simulation results show that the improved power control scheme has good performance compared to conventional power control schemes in a geostationary earth orbit (GEO) satellite system utilizing ATCs.
文摘This article proposes a new algorithm to improve the rate control efficiency of enhanced reverse link medium access control （RLMAC） in the code division multiple access （CDMA） 1x EV-DO release A（Rev. A） system. The new algorithm brings reverse access terminal （AT） pilot power to the RLMAC rate control procedure and makes it easier for a low pilot power user to increase its data rate when the system is slightly loaded and harder to decrease its date rate when the system is heavily loaded. Numerical results of system level simulations show that the new algorithm can bring higher system throughput, lower AT transmission power, and lower system load.
