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北京交通大学电子信息工程学院,北京 100044
[ "王一兵(1995- ),女,黑龙江大庆人,北京交通大学博士生,主要研究方向为毫米波通信和媒体访问控制。" ]
[ "牛勇(1988- ),男,山西太原人,博士,北京交通大学教授,主要研究方向为毫米波通信无线网络资源分配与性能优化无线网络MAC层协议设计、高速铁路移动通信和车联网通信。" ]
[ "丁玮光(1994- ),女,河北秦皇岛人,北京交通大学硕士生,主要研究方向为毫米波通信和媒体访问控制。" ]
[ "吴昊(1973- ),女,北京人,博士,北京交通大学教授,主要研究方向为网络安全、宽带移动通信系统和专用移动通信。" ]
网络出版日期:2019-01,
纸质出版日期:2019-01-25
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王一兵, 牛勇, 丁玮光, 等. 基于冲突图的毫米波无线个域网并行调度方案[J]. 通信学报, 2019,40(1):34-42.
Yibing WANG, Yong NIU, Weiguang DING, et al. Contention graph based concurrent scheduling algorithm in millimeter wave WPAN[J]. Journal on communications, 2019, 40(1): 34-42.
王一兵, 牛勇, 丁玮光, 等. 基于冲突图的毫米波无线个域网并行调度方案[J]. 通信学报, 2019,40(1):34-42. DOI: 10.11959/j.issn.1000-436x.2019010.
Yibing WANG, Yong NIU, Weiguang DING, et al. Contention graph based concurrent scheduling algorithm in millimeter wave WPAN[J]. Journal on communications, 2019, 40(1): 34-42. DOI: 10.11959/j.issn.1000-436x.2019010.
毫米波的定向天线和波束赋形技术使得多条数据流之间的并行传输成为可能,但并行传输也可能造成更高的多用户干扰。因此在时隙资源有限且请求传输的数据流数较多时,如何对数据流进行有效的并行调度以提高网络性能,仍然是一项重要挑战。针对这些问题,提出了一种基于网络全局冲突图的并行调度算法(CB-STDMA)。为保证用户的服务质量(QoS)需求,该算法以最大化网络中满足QoS需求的流数为目标,考虑了流之间的冲突干扰,并且优先对所用时隙数较少的流进行调度来节省资源。通过仿真验证了该算法性能的优势。
The directional antennas and beamforming techniques in millimeter wave (mmWave) bands are used to make concurrent transmission between multiple flows become possible.However
higher mutual interference may be caused by concurrent transmission.Therefore
when the time slots were limited and the number of data flows was large
how to schedule the concurrent flows efficiently was solved by proposed algorithm.The contention graph based spatial-time division multiple access (CB-STDMA) concurrent scheduling algorithm guaranteed the quality of service (QoS) of users
and aimed at maximizing the number of flows with their QoS requirements satisfied.It considered the interference between different flows
and a higher priority was given to the flow with fewer time slots requirement.Extensive simulations demonstrated that the proposed CB-STDMA algorithm increased the number of flows with their QoS requirements satisfied and the network throughput by 50% and 20% respectively compared with the existing algorithms.
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