宏-飞蜂窝双层网络中基于毫微微基站分组的资源分配

发布时间：2018-05-20 20:23

本文选题：毫微微小区 + 资源分配　；参考：《计算机应用》2017年05期

【摘要】：针对宏-飞蜂窝双层网络模型中宏小区(Macrocell)用户层和毫微微小区(Femtocell)用户层之间的跨层干扰和Femtocell之间的同层干扰,提出了一种基于毫微微基站分组的资源分配算法。该算法包括两个部分:一部分是宏基站先利用改进的差额法,设置虚拟的宏用户(MUE),将之变为平衡的指派问题再为宏小区用户分配信道,然后用注水算法分配功率,保证宏小区用户的正常传输。另一部分是在保证宏小区用户的服务质量基础上,采用一种增强型的蚁群优化(EACO)算法,设定信息素浓度范围后对毫微微小区进行分组,避免了原始的蚁群算法有可能陷入局部最优的现象;再利用一种启发式算法和分布式功率分配算法分别对毫微微用户(FUE)进行信道和功率分配,在满足毫微微小区用户的数据速率需求下,最大化频谱效率。仿真结果表明,EACO有效地抑制了跨层干扰和同层干扰,既能保证用户的数据速率需求,又能有效提升网络频谱效率。
[Abstract]:In view of the cross layer interference between the macro cell (Macrocell) user layer and the milli micro cell (Femtocell) user layer in the macro cellular double layer network model, a resource allocation algorithm based on the milli micro base station grouping is proposed. The algorithm consists of two parts: one part is the Acer station using the improved difference first. In the method, a virtual macro user (MUE) is set up to assign a balanced assignment problem to a macro cell user, then the power is allocated to ensure the normal transmission of the macro cell users. The other part is to use an enhanced ant colony optimization (EACO) algorithm to set up the information on the basis of the service quality of the macro cell users. The milli micro cell is grouped after the prime concentration range, avoiding the phenomenon that the original ant colony algorithm is likely to fall into the local optimal. A heuristic algorithm and a distributed power allocation algorithm are used to allocate the channel and power of the milli micro user (FUE), and to meet the data rate requirements of the milli micro cell users. The simulation results show that EACO effectively inhibits the cross layer interference and the same layer interference, which can not only guarantee the user's data rate demand, but also effectively improve the network spectrum efficiency.
【作者单位】：重庆市移动通信重点实验室(重庆邮电大学);
【基金】：国家自然科学基金资助项目(61102062) 重庆市基础与前沿项目(cstc2014jcyj A40052) 重庆市教委科学技术研究项目(KJ1400405)~~
【分类号】：TN929.5

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