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Inter-Base Station Cooperative Scheduling Method Among Multiple Service Channels to Maximize Integrated System Throughput

机译:多个服务信道之间的基站间协作调度方法以最大化集成系统吞吐量

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In this paper, we propose an inter-base station (BS) cooperative scheduling method among terminals in multiple service channels that maximizes the system throughput, which is an integrated system metric concatenating the performance levels of all services. The fifth generation (5G) mobile communication system is expected to support various wireless communication services such as massive machine-type communications (mMTC), ultra-reliable low latency communications (URLLC), and enhanced mobile broadband (eMBB). These services will serve different numbers of terminals and have different requirements in terms of spectrum efficiency and fairness among terminals. Therefore, appropriately allocating resources to terminals receiving different services is essential to utilize fully the overall system bandwidth considering the performance levels of all services. The proposed method assumes the centralized radio access network (C-RAN) architecture in heterogeneous networks. The proposed method achieves optimal coordinated time/frequency-domain scheduling with inter-BS cooperation. The optimization criterion is to maximize the integrated system throughput among service channels. Extensive computer simulation results show that the proposed method achieves significant enhancement in the achievable integrated system throughput compared to that for the conventional method, especially when a service prioritizes the fairness among terminals and the number of pico BSs is large.
机译:在本文中,我们提出了一种在多个服务信道中的终端之间的基站间协作调度方法,该方法最大程度地提高了系统吞吐量,这是一种将所有服务的性能水平进行组合的集成系统指标。预计第五代(5G)移动通信系统将支持各种无线通信服务,例如大规模机器类型通信(mMTC),超可靠的低延迟通信(URLLC)和增强型移动宽带(eMBB)。这些服务将服务于不同数量的终端,并且在频谱效率和终端之间的公平性方面有不同的要求。因此,考虑到所有服务的性能水平,适当地向接收不同服务的终端分配资源对于充分利用整个系统带宽是必不可少的。所提出的方法假设异构网络中的集中式无线电接入网络(C-RAN)架构。所提出的方法通过基站之间的协作实现了最优的时/频域协调调度。优化标准是使服务通道之间的集成系统吞吐量最大化。大量的计算机仿真结果表明,与传统方法相比,该方法在可实现的集成系统吞吐量方面取得了显着提高,尤其是当服务优先考虑终端之间的公平性且微微BS的数量较大时。

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