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An Enhanced OFDM Resource Allocation Algorithm in C-RAN Based 5G Public Safety Network

机译:基于C-RAN的5G公共安全网络增强的OFDM资源分配算法

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摘要

Public Safety Network (PSN) is the network for critical communication when disaster occurs. As a key technology in 5G, Cloud-Radio Access Network (C-RAN) can play an important role in PSN instead of LTE-based RAN. This paper firstly introduces C-RAN based PSN architecture and models the OFDM resource allocation problem in C-RAN based PSN as an integer quadratic programming, which allows the trade-off between expected bitrates and allocating fairness of PSN Service User (PSU). However, C-RAN based PSN needs to improve the efficiency of allocating algorithm because of a mass of PSU-RRH associations when disaster occurs. To deal with it, the resources allocating problem with integer variables is relaxed into one with continuous variables in the first step and an algorithm based on Generalized Bender’s Decomposition (GBD) is proposed to solve it. Then we use Feasible Pump (FP) method to get a feasible integer solution on the original OFDM resources allocation problem. The final experiments show the total throughput achieved by C-RAN based PSN is at most higher by 19.17% than the LTE-based one. And the average computational time of the proposed GBD and FP algorithm is at most lower than Barrier by 51.5% and GBD with no relaxation by 30.1%, respectively.
机译:公共安全网络(PSN)是在发生灾难时关键通信的网络。作为5G中的关键技术,云 - 无线电接入网络(C-RAN)可以在PSN中发挥重要作用而不是基于LTE的RAN。本文首先介绍了基于C-RAN基于C-RAN资源分配问题的C-RAN资源分配问题,作为整数二次编程,允许在预期的比特率和分配PSN服务用户(PSU)之间的权衡。但是,由于灾难发生时,C-RAN基于C-RAN的PSN需要提高分配算法的效率。要处理它,将用整数变量分配问题的资源被放宽到一个具有连续变量的一个,并且提出了一种基于广义弯曲的分解(GBD)的算法来解决。然后我们使用可行的泵(FP)方法来获得原始OFDM资源分配问题的可行整数解决方案。最后的实验表明,基于C-RAN的PSN实现的总产量最高于19.17%而不是基于LTE的PSN。所提出的GBD和FP算法的平均计算时间至多于51.5%和GBD,分别不会弛豫30.1%。

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