In this paper,an Interference Alignment and Cancellation(IAC)based transmission and scheduling scheme is proposed for an infrastructured Cognitive Radio(CR)Multiple-Input Multiple-Output(MIMO)system with multiple seco...In this paper,an Interference Alignment and Cancellation(IAC)based transmission and scheduling scheme is proposed for an infrastructured Cognitive Radio(CR)Multiple-Input Multiple-Output(MIMO)system with multiple secondary users.With the cooperation of Primary Base Station(PBS)and Secondary Base Station(SBS),a signal processing procedure is designed to guarantee the priority of the primary transmission.As a reward for offering help to the PBS,the SBS is granted communication opportunity.The transmission difference of various spatial channels is exploited in Secondary User(SU)scheduling.With the proposed scheme,interferencefree concurrent transmission of both PBS and SBS is implemented.Spatial channel resources can be effectively utilised compared with a traditional Interference Alignment(IA)based strategy.Simulation results show that the achievable data for primary transmission is enhanced by cooperative signal processing at the SBS.With respect to the SBS,its data rate grows with an increasing number of SUs by exploiting the multiuser diversity gain.展开更多
For multiuser multiple-input-multiple-output （MIMO） cognitive radio （CR） networks a four-stage transmiision structure is proposed. In learning stage, the learning-based algorithm with low overhead and high flexibi...For multiuser multiple-input-multiple-output （MIMO） cognitive radio （CR） networks a four-stage transmiision structure is proposed. In learning stage, the learning-based algorithm with low overhead and high flexibility is exploited to estimate the channel state information （ CSI ） between primary （PR） terminals and CR terminals. By using channel training in the second stage of CR frame, the channels between CR terminals can be achieved. In the third stage, a multi-criteria user selection scheme is proposed to choose the best user set for service. In data transmission stage, the total capacity maximization problem is solved with the interference constraint of PR terminals. Finally, simulation results show that the multi-criteria user selection scheme, which has the ability of changing the weights of criterions, is more flexible than the other three traditional schemes and achieves a tradeoff between user fairness and system performance.展开更多
基金supported by the National Natural Science Foundation of China under Grants No. 61102057,No. 61231008the National Key Basic Research Program of China (973 Program) under Grant No. 2009CB320404+4 种基金the National Science and Technology Major Project under Grant No. 2012ZX-03003005-005the 111 Project under Grant No.B08038the Program for Changjiang Scholars and Innovative Research Team in University under Grant No. IRT0852the ISN Project under Grant No. ISN1103005the Fundamental Research Funds for the Central Universities under Grant No. K5051301014
文摘In this paper,an Interference Alignment and Cancellation(IAC)based transmission and scheduling scheme is proposed for an infrastructured Cognitive Radio(CR)Multiple-Input Multiple-Output(MIMO)system with multiple secondary users.With the cooperation of Primary Base Station(PBS)and Secondary Base Station(SBS),a signal processing procedure is designed to guarantee the priority of the primary transmission.As a reward for offering help to the PBS,the SBS is granted communication opportunity.The transmission difference of various spatial channels is exploited in Secondary User(SU)scheduling.With the proposed scheme,interferencefree concurrent transmission of both PBS and SBS is implemented.Spatial channel resources can be effectively utilised compared with a traditional Interference Alignment(IA)based strategy.Simulation results show that the achievable data for primary transmission is enhanced by cooperative signal processing at the SBS.With respect to the SBS,its data rate grows with an increasing number of SUs by exploiting the multiuser diversity gain.
基金Supported by National S&T Major Project of China(2013ZX03003002-003)
文摘For multiuser multiple-input-multiple-output （MIMO） cognitive radio （CR） networks a four-stage transmiision structure is proposed. In learning stage, the learning-based algorithm with low overhead and high flexibility is exploited to estimate the channel state information （ CSI ） between primary （PR） terminals and CR terminals. By using channel training in the second stage of CR frame, the channels between CR terminals can be achieved. In the third stage, a multi-criteria user selection scheme is proposed to choose the best user set for service. In data transmission stage, the total capacity maximization problem is solved with the interference constraint of PR terminals. Finally, simulation results show that the multi-criteria user selection scheme, which has the ability of changing the weights of criterions, is more flexible than the other three traditional schemes and achieves a tradeoff between user fairness and system performance.
文摘认知无线电(cognitive radio,CR)和多输入多输出(multiple input multiple output,MIMO)技术能够有效地提高无线频谱资源的利用效率。而线性预编码技术则是实现这一目的的重要手段。但是目前的预编码算法主要针对服从Gauss分布的输入信号,这一前提假设严重地限制了预编码技术在实际情况中的应用。针对这个问题,该文在分析信息论与检测理论基本关系的基础上,结合特征值分解(singular value decomposition,SVD)与水银注水法(mercury water filling,MWF)的优点,提出了一种适用于输入信号服从任意分布的线性预编码算法,有效提高了线性预编码算法的实用价值。仿真表明该算法优于现有算法。
