5G超密集组网的多点协作传输和功率分配策略
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摘要
5G超密集组网(UDN)允许在异构网络中部署大量高密度的低功率传输节点(TP),在提高系统性能的同时也引入了小小区间的同频干扰(ICI)问题。为了解决这一问题,多点协作传输(CoMP)在UDN中得到了广泛的使用。但它也带来了新的挑战,如何有效地进行网络资源的分配就是其中之一。为了提高小小区边缘用户的速率和系统总和率,提出了一种基于小区负载感知的CoMP(CLA-CoMP)方案。针对UDN中的功率分配问题,采用了基于用户关联的后验概率功率分配(P2UPA)策略,它旨在为高关联概率的用户分配更高的功率。仿真结果表明,同使用平均功率分配的UDN系统相比,采用CLA-CoMP和P2UPA的系统性能增益有了明显的提高。
5G Ultra-Dense Network(UDN) allows a large number of high-density low-power transmission points(TPs) to be deployed in heterogeneous networks( HetNets). It greatly improves the system performance whereas introduces inter-cell interference( ICI). To elim-inate ICI, CoMP concept has been widely used in UDN. But it also brings new challenges, how to effectively allocate network re-sources is one of them. This paper proposes a CLA-CoMP algorithm to improve both the rate of the small cell edge users and the system sum rate. In order to deal with the power allocation problem in UDN, this paper adopts P2UPA strategy, which aims to al-locate higher power to users with the high probability of association. Simulation results reveal that jointly use CLA-CoMP and P2UPA can significantly improve the system performance, compared with the case of average power allocation.
5G Ultra-Dense Network(UDN) allows a large number of high-density low-power transmission points(TPs) to be deployed in heterogeneous networks( HetNets). It greatly improves the system performance whereas introduces inter-cell interference( ICI). To elim-inate ICI, CoMP concept has been widely used in UDN. But it also brings new challenges, how to effectively allocate network re-sources is one of them. This paper proposes a CLA-CoMP algorithm to improve both the rate of the small cell edge users and the system sum rate. In order to deal with the power allocation problem in UDN, this paper adopts P2UPA strategy, which aims to al-locate higher power to users with the high probability of association. Simulation results reveal that jointly use CLA-CoMP and P2UPA can significantly improve the system performance, compared with the case of average power allocation.
引文
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[5]BAI L,LIU T T,CHEN Z L,et al.A graph-based interference topology control for ultra-dense networks[C].201412th International Conference on Signal Processing(ICSP),2014:1676-1681.
[6]GAO Y,CHENG L,ZHANG X,et al.Enhanced power allocation scheme in ultra-dense small cell network[J].中国通信(英文版),2016,13(2):21-29.
[7]XU X,ZHAO Z F,LI R P,et al.A resource scheduling scheme based on utility function in CoMP environment[C].2017 9th International Conference on WCSP,2017.
[8]YANG Z,ZHANG H,HAO P,et al.Backhaul-aware adaptive TP selection for virtual cell in ultra-dense networks[C].International Symposium on Personal,Indoor,and Mobile Radio Communications.IEEE,2016:1-6.
[9]ZHANG T,ZHAO J,AN L,et al.Energy efficiency of base station deployment in ultra dense HetNets:a stochastic geometry analysis[J].IEEE Wireless Communications Letters,2016,5(2):184-187.
[10]HAMIDOUCHE K,SAAD W,DEBBAH M,et al.MeanField games for distributed caching in ultra-dense small cell networks[C].American Control Conference.IEEE,2016:4699-4704.