摘要
为了解决毫米波信道条件下有限区域内多用户调度问题,提出了一种基于毫米波多用户多输入单输出(MUMISO)下行链路信道的自适应多用户调度方案.首先,根据各个用户反馈的区域位置信息,基站对用户进行分组,并根据区域的用户密度为每个区域分配适当的射频链资源;然后,基于获取到的各个区域角度范围信息和各区域所分配的射频链数,为每个区域设计通信波束;最后,在综合考虑组内和组间波束干扰的情况下,在用户端为每个满足匹配约束条件的用户确定最佳通信波束,并将该波束的信噪比值和信道质量信息反馈给基站,在基站端,根据用户反馈的信息,为每个区域的通信波束依次选择最佳用户.仿真结果表明,该方案能获得较好的和速率性能,尽管与SUS-ZFBF算法相比有一定的差距,但降低了反馈信息量,而且射频资源的分配方式在一定程度上更能保证用户通信的公平性.
A new adaptive user scheduling was proposed to solve the multi-user scheduling problem of millimeter wave multi-user multiple-input single-output( MU-MISO) downlink system,in which users are located in the finite areas. Firstly,the area's user will be grouped based on the access information of user,and then the radio frequency chain will be properly allocated for each area based on the user density.Secondly,based on the RF's number and the range of angle of departure of each area,the communication beams will be designed. Finally,the best matched user will be selected to each pre-designed random beam for minimum inter-interference of beams in the base station,based on the channel quality indicator and the channel state information( CSI) feedback only from the matched users. It is shown that,the proposed scheme can achieve good rate performance. Although there is a certain gap compared with the semi-orthogonal user selection with zero-forcing beamforming that requires full CSI feedback from all us-ers,it reduces feedback overhead to some degree. Moreover,the allocation of RF resources guarantees the fairness of user communication to a certain extent.
作者
邹卫霞
王海勇
刘学锋
ZOU Wei-xia;WANG Hai-yong;LIU Xue-feng(Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China;State Key Laboratory of Millimeter Waves, Southeast University, Nanjing 210096, China)
出处
《北京邮电大学学报》
EI
CAS
CSCD
北大核心
2018年第2期32-37,共6页
Journal of Beijing University of Posts and Telecommunications
基金
国家自然科学基金项目(61571055)
毫米波国家重点实验室开放课题经费项目(K201815)
国家科技重大专项项目(2017ZX03001028)
关键词
毫米波
用户调度算法
破零预编码
millimeter wave
user scheduling algorithm
zero-forcing precoding