Max-min fairness based radio resource management in fourth generation heterogeneous networks

Max-min fairness based radio resource management in fourth generation heterogeneous networks
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DOI:
10.1109/iscit.2009.5341258
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发表时间:
2009-09
期刊:
2009 9th International Symposium on Communications and Information Technology
影响因子:
--
通讯作者:
Peng Xue;Peng Gong;Jae Hyun Park;Daeyoung Park;D. Kim
Peng Xue;Peng Gong;Jae Hyun Park;Daeyoung Park;D. Kim
中科院分区:
其他
文献类型:
--
作者:
Peng Xue;Peng Gong;Jae Hyun Park;Daeyoung Park;D. Kim

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在异构网络中,无线资源管理(RRM)在利用潜在的网络多样性方面发挥着重要作用。在本文中,我们研究了涉及正交频分多址(OFDMA)网络的异构网络中的RRM策略,其目的是最大化最小用户吞吐量。为了解决RRM问题,提出了反映异构网络特征的分析模型。假设系统能够支持多归属接入,并且子载波能够被OFDMA网络中的多个用户共享,则问题可以通过凸优化问题来表述并得到最优解。我们还针对实际应用提出了一种次优的 RRM 算法,包括网络选择和每个网络中的资源分配。所提出的 RRM 算法的性能在异构长期演进 (LTE) 无线局域网 (WLAN) 网络中进行了评估。我们的模拟结果显示,与仅 LTE 和 WLAN 优先策略相比,性能有了相当大的提升。此外,随着用户数量的增加,最优解和次优算法之间的性能差距变得越来越小。
In the heterogeneous networks, radio resource management (RRM) plays an important role to utilize the potential network diversity. In this paper, we study the RRM strategy in the heterogeneous networks involved with an orthogonal frequency division multiple access (OFDMA) network, with the aim of maximizing the minimum user throughput. An analytical model which reflects the feature of heterogeneous networks is presented in order to formulate the RRM problem. Assuming that the system can support multi-homing access and the subcarrier can be shared by multiple users in the OFDMA network, the problem can be formulated by a convex optimization problem and the optimal solution is obtained. We also propose a suboptimal RRM algorithm for practical applications, including network selection and resource allocation in each network. The performance of the proposed RRM algorithms is evaluated in the heterogeneous long term evolution (LTE)-wireless local area network (WLAN) networks. Our simulation results show considerable gains in comparison to the performance of LTE-Only and WLAN-First strategies. In addition, the performance gap between the optimal solution and suboptimal algorithm becomes minor as the number of users increases.