This paper presents a novel interference management strategy, to adaptively choose the best fractional frequency reuse （FFR） scheme for macro and femto networks. The strategy aims to maximize the system throughput t...This paper presents a novel interference management strategy, to adaptively choose the best fractional frequency reuse （FFR） scheme for macro and femto networks. The strategy aims to maximize the system throughput taking into account a number of system constraints. Here, the system constrains consist of the outage constraints of two-tier users and macrocell spectral efficiency requirement. The detailed procedures of our proposed strategy are： 1） A reference signal received power （RSRP） based selection algorithm is presented to adaptively select the optional FFR schemes satisfying the outage constraints. 2） Considering the macrocell spectral efficiency, the optimal FFR scheme is selected from the optional FFR schemes at MeNB side, to achieve the maximum system throughput in two-tier femtocell networks. We study the efficacy of the proposed strategy using an long term evolution advanced （LTE-A） system level simulator. Simulation results show that our proposed interference management strategy can select the best FFR scheme to maximize the system throughput, and the FFR schemes derived by using RSRP-based selection algorithm can be the effective solutions to deploy femtocells in macrocells.展开更多
在Femtocell家庭基站(Femtocell Base Station,FBS)组成的异构网络中,为提升网络的频谱效率,FBS与Macrocell宏基站(Macrocell Base Station,MBS)一般要求是同频部署,然而同频部署会产生同信道干扰。为了实现FBS的大规模部署,降低网络同...在Femtocell家庭基站(Femtocell Base Station,FBS)组成的异构网络中,为提升网络的频谱效率,FBS与Macrocell宏基站(Macrocell Base Station,MBS)一般要求是同频部署,然而同频部署会产生同信道干扰。为了实现FBS的大规模部署,降低网络同信道干扰影响变得尤为重要。该文提出一种基于Q-learning的子信道分配方案,既保证大量部署的FBS不会对MBS带来过高的跨层干扰,同时也降低了FBS之间的同层干扰。同时针对FBS稀疏部署和密集部署的场景,分别进行了算法的仿真验证,其仿真结果表明该算法降低了干扰,验证了理论的正确性。展开更多
In this paper, we exploit clustered interference alignment(IA) for efficient subchannel allocation in ultra-dense orthogonal frequency division multiplexing access(OFDMA) based femtocell networks, which notably improv...In this paper, we exploit clustered interference alignment(IA) for efficient subchannel allocation in ultra-dense orthogonal frequency division multiplexing access(OFDMA) based femtocell networks, which notably improves the spectral efficiency as well as addresses the feasibility issue of IA. Our problem is formulated as a combinatorial optimization problem which is NP-hard. To avoid obtaining its optimal solution by exhaustive search, we propose a two-phases efficient solution with low-complexity. The first phase groups all the femtocell user equipments(FUEs) into disjoint clusters, and the second phase allocates subchannels to the formed clusters where IA is performed. By doing this, the intra-cluster and inter-cluster interferences are mitigated by clustered IA and subchannel allocation in ultra-dense femtocell networks, respectively.Also, low-complexity algorithm is proposed to solve the corresponding sub-problem in each phase. Simulation results demonstrate that the proposed scheme not only outperforms other related schemes, but also provides a close performance to the optimal solution.展开更多
在混合接入式femtocell网络中,为了激励家庭小区基站接纳位于死区的宏用户,提出了基于Stackelberg博弈和弹性理论的资源分配方法。首先建立Stackelberg博弈模型,宏基站(macro base station,MBS)作为主导者(leader),家庭小区基站(femto b...在混合接入式femtocell网络中,为了激励家庭小区基站接纳位于死区的宏用户,提出了基于Stackelberg博弈和弹性理论的资源分配方法。首先建立Stackelberg博弈模型,宏基站(macro base station,MBS)作为主导者(leader),家庭小区基站(femto base station,FBS)作为跟随者(follower),MBS支付给FBS效用,而FBS通过获利来补偿因为接纳宏用户(macro user equipment,MUE)而损失的速率;然后引入弹性理论确立MBS和FBS的效用函数,构建凸优化问题,并求解出价格和速率的均衡解,参与人都能实现效用最大化;最后通过数值分析,验证了均衡解的存在,比较分析了在发射功率不同的情况下FBS和MBS的效用。结果表明,迭代20次左右即可找到均衡解,弹性因子参数为0.7时,FBS和MBS的收益最佳。通过理论研究和数值分析验证了策略有效性。展开更多
基金supported by the National Natural Science Foundation of China(61121001)Program for New Century Excellent Talents in University(NCET-10-0242)
文摘This paper presents a novel interference management strategy, to adaptively choose the best fractional frequency reuse （FFR） scheme for macro and femto networks. The strategy aims to maximize the system throughput taking into account a number of system constraints. Here, the system constrains consist of the outage constraints of two-tier users and macrocell spectral efficiency requirement. The detailed procedures of our proposed strategy are： 1） A reference signal received power （RSRP） based selection algorithm is presented to adaptively select the optional FFR schemes satisfying the outage constraints. 2） Considering the macrocell spectral efficiency, the optimal FFR scheme is selected from the optional FFR schemes at MeNB side, to achieve the maximum system throughput in two-tier femtocell networks. We study the efficacy of the proposed strategy using an long term evolution advanced （LTE-A） system level simulator. Simulation results show that our proposed interference management strategy can select the best FFR scheme to maximize the system throughput, and the FFR schemes derived by using RSRP-based selection algorithm can be the effective solutions to deploy femtocells in macrocells.
文摘在Femtocell家庭基站(Femtocell Base Station,FBS)组成的异构网络中,为提升网络的频谱效率,FBS与Macrocell宏基站(Macrocell Base Station,MBS)一般要求是同频部署,然而同频部署会产生同信道干扰。为了实现FBS的大规模部署,降低网络同信道干扰影响变得尤为重要。该文提出一种基于Q-learning的子信道分配方案,既保证大量部署的FBS不会对MBS带来过高的跨层干扰,同时也降低了FBS之间的同层干扰。同时针对FBS稀疏部署和密集部署的场景,分别进行了算法的仿真验证,其仿真结果表明该算法降低了干扰,验证了理论的正确性。
基金supported by China Scholarship Council (201406960042)the National Science Foundation (91338115,61231008)+2 种基金National S&T Major Project (2015ZX03002006)Program for Changjiang Scholars and Innovative Research Team in University (IRT0852)the 111 Project (B08038)
文摘In this paper, we exploit clustered interference alignment(IA) for efficient subchannel allocation in ultra-dense orthogonal frequency division multiplexing access(OFDMA) based femtocell networks, which notably improves the spectral efficiency as well as addresses the feasibility issue of IA. Our problem is formulated as a combinatorial optimization problem which is NP-hard. To avoid obtaining its optimal solution by exhaustive search, we propose a two-phases efficient solution with low-complexity. The first phase groups all the femtocell user equipments(FUEs) into disjoint clusters, and the second phase allocates subchannels to the formed clusters where IA is performed. By doing this, the intra-cluster and inter-cluster interferences are mitigated by clustered IA and subchannel allocation in ultra-dense femtocell networks, respectively.Also, low-complexity algorithm is proposed to solve the corresponding sub-problem in each phase. Simulation results demonstrate that the proposed scheme not only outperforms other related schemes, but also provides a close performance to the optimal solution.
文摘在混合接入式femtocell网络中,为了激励家庭小区基站接纳位于死区的宏用户,提出了基于Stackelberg博弈和弹性理论的资源分配方法。首先建立Stackelberg博弈模型,宏基站(macro base station,MBS)作为主导者(leader),家庭小区基站(femto base station,FBS)作为跟随者(follower),MBS支付给FBS效用,而FBS通过获利来补偿因为接纳宏用户(macro user equipment,MUE)而损失的速率;然后引入弹性理论确立MBS和FBS的效用函数,构建凸优化问题,并求解出价格和速率的均衡解,参与人都能实现效用最大化;最后通过数值分析,验证了均衡解的存在,比较分析了在发射功率不同的情况下FBS和MBS的效用。结果表明,迭代20次左右即可找到均衡解,弹性因子参数为0.7时,FBS和MBS的收益最佳。通过理论研究和数值分析验证了策略有效性。
