Research on user pairing algorithm for LTE femtocell uplink

In this article,a new simulated annealing based bit error rate pairing scheduling(SA-BPS)algorithm for LTE femtocell uplink virtual multiple input multiple output(V-MIMO)systems is proposed,which uses Round Robin(RR)criterion to decide the first user,and simulated annealing(SA)algorithm with objective function of bit error rate(BER)is suggested to decide the pairing users.The SA-BPS is considered not only to be used for inner layer user pairing within femtocell user equipments(HUEs)to increase spectrum efficiency,but also to be used for cross layer user pairing between HUEs and macrocell user equipments(MUEs)to cancel the cross layer interference from MUEs to HUEs.As a growth control coefficient is used in SA-BPS to control the growth of average BER of users in the pairing group,rapid user BER deterioration can be prevented by adopting a proper coefficient.Simulation results show that,the SA-BPS outperforms RPS,DPS,and the conventional SA algorithm in terms of BER performance,whether used for inner layer user pairing or cross layer user pairing.Also,the mode switching signal to interference ratio(SIR)threshold between inner and cross layer user pairing are obtained by simulation in three cross layer interference power distribution scenarios.     

LTE-A系统中基于资源利用率的时延优先调度算法

针对现有LTE系统中调度算法在吞吐量、公平性及丢包率性能指标上难以取得性能平衡的问题,提出一种改进算法,在考虑用户时延的前提下还考虑了用户对资源块(RB)的利用率,从实际获得速率的角度来更精确描述用户对资源的利用能力,更加合理地分配资源.仿真结果表明,该算法的丢包率性能有很大改进,同时在吞吐量、公平性方面也有着较好表现,实现了良好的综合性能,能够更好地满足用户的QoS需求.     

LTE-A飞蜂窝网络自相似业务流的端到端时延边界分析

LTE-A是一种4G移动通信标准,可满足移动数据业务对传输带宽的要求。为解决移动通信网络中室内信号质量较差的问题,LTE-A标准采用飞蜂窝技术作为室内无线接入解决方案。针对LTE-A飞蜂窝网络的时延边界问题,运用随机网络演算方法分析业务流的自相似性质和MIMO信道的时变特性,构建了LTE-A飞蜂窝网络中自相似业务流的随机到达与随机服务模型。围绕所构建的到达与服务模型,运用有效带宽理论和chernoff界方法,给出了自相似业务流的端到端时延边界。NS3仿真验证表明,在信道带宽和业务流优先级等指标不同的情形下,所给出的理论端到端时延边界与仿真时延的偏差在2ms以内,较为准确有效,可为确保LTE-A飞蜂窝网络的服务质量提供依据。     

Clustering-based adaptive low-power subframe configuration with load-aware offsetting in dense heterogeneous networks

Heterogeneous Networks (HetNets) and cell densification represent promising solutions for the surging data traffic demand in wireless networks. In dense HetNets, user traffic is steered toward the Low-Power Node (LPN) when possible to enhance the user throughput and system capacity by increasing the area spectral efficiency. However, because of the transmit power differences in different tiers of HetNets and irregular service demand, a load imbalance typically exists among different serving nodes. To offload more traffic to LPNs and coordinate the Inter-Cell Interference (ICI), Third-Generation Partnership Project (3GPP) has facilitated the development of the Cell Range Expansion (CRE), enhanced Inter-Cell Interference Coordination (eICIC) and Further enhanced ICIC (FeICIC). In this paper, we develop a cell clustering-based load-aware offsetting and an adaptive Low-Power Subframe (LPS) approach. Our solution allows the separation of User Association (UA) functions at the User Equipment (UE) and network server such that users can make a simple cell-selection decision similar to that in the maximum Received Signal Strength (max-RSS) based UA scheme, where the network server computes the load-aware offsetting and required LPS periods based on the load conditions of the system. The proposed solution is evaluated using system-level simulations wherein the results correspond to performance changes in different service regions. Results show that our method effectively solves the offloading and interference coordination problems in dense HetNets.     

异构Femtocell网络中基于用户公平性的干扰协调

为使含有家庭基站和宏基站的异构网络(HetNet)中各用户的服务质量需求都能满足并达到用户间的公平性,在功率限制条件下对宏用户中最小的用户数据速率最大化,将此最小用户速率提供给家庭基站用户,获得各家庭基站用户的目标信干噪比(SINR),再利用对分法调整家庭基站的发射功率.仿真结果表明,该方法能够保证最小的宏用户数据速率且提高异构网络用户间的公平性.     

Cooperative Q‐learning techniques for distributed online power allocation in femtocell networks

In this paper, we address the problem of distributed interference management of femtocells that share the same frequency band with macrocells using distributed multi‐agent Q‐learning. We formulate and solve two problems representing two different Q‐learning algorithms, namely, femto‐based distributed and sub‐carrier‐based distributed power controls using Q‐learning (FBDPC‐Q and SBDPC‐Q). FBDPC‐Q is a multi‐agent algorithm that works on a global basis, for example, deals with the aggregate macrocell and femtocell capacities. Its complexity increases exponentially with the number of sub‐carriers in the system. Also, it does not take into consideration the sub‐carrier macrocell capacity as a constraint. To overcome these problems, SBDPC‐Q is proposed, which is a multi‐agent algorithm that works on a sub‐carrier basis, for example, sub‐carrier macrocell and femtocell capacities. Each of FBDPC‐Q and SBDPC‐Q works in three different learning paradigms: independent (IL), cooperative (CL), and weighted cooperative (WCL). IL is considered the simplest form for applying Q‐learning in multi‐agent scenarios, where all the femtocells learn independently. CL and WCL are the proposed schemes in which femtocells share partial information during the learning process in order to strike a balance between practical relevance and performance. We prove the convergence of the CL paradigm when used in the FBDPC‐Q algorithm. We show via simulations that the CL paradigm outperforms the IL paradigm in terms of the aggregate femtocell capacity, especially in networks with large number of femtocells and large number of power levels. In addition, we propose WCL to address the CL limitations. Finally, we evaluate the robustness and scalability of both FBDPC‐Q and SBDPC‐Q, against several typical dynamics of plausible wireless scenarios (fading, path loss, random activity of femtocells, etc.). We show that the CL paradigm is the most scalable to large number of femtocells and robust to the network dynamics compared with the IL and WCL paradigms. Copyright © 2014 John Wiley & Sons, Ltd.     

一种基于CoMP的随机接入方案

提出了一种新的基于协作多点传输和接收（CoMP）技术的多发随机接入流程,并根据 随机接入的目的和业务类型设计了接入优先级,在此基础上设计了一种新的随机接入方案, 对 不同类型的随机接入请求提供不同的接入机制,以保证边缘用户的接入性能和满足不同业务 的QoS需求。仿真结果表明,与LTE标准随机接入方案相比,该方案对系统整体接入性能略有 提高,且大大提高了边缘高优先级用户的接入性能。     

LTE-A系统一种降低复杂度的软球形检测算法

软球形译码算法虽然能接近ML(最大似然)算法的误码性能,但其计算复杂度很高。文章提出了一种降低计算复杂度的SSD(软球形译码)算法,该算法在QR(正交三角)分解算法的反向迭代上三角矩阵R中引入减弱噪声部分以缩小初始搜索半径,然后利用最小距离准则对搜索树进行有效地删减,缩小树搜索空间。MATLAB仿真结果表明,该算法在获得接近传统SSD性能的条件下,能够很大程度地降低系统的计算复杂度。     

WiMAX Femtocell网络架构及技术挑战

由于可以提高室内用户的使用感知并降低网络建设的费用,利用室内有线网络作为回传的Femtocell系统吸引了产业界的极大关注。作为WiMAX技术标准组织的WiMAX Forum已经开始了WiMAX Femtocell的标准化进程。本文详细论述了WiMAX Femtocell的网络架构情况和面临的技术挑战及应对,最后对WiMAX Femtocell的标准化进程进行了描述。     

LTE-A系统下行链路信道估计的性能评估

使用3GPP10版本即LTE-A(Long Term Evolution Advanced)中新的参考信号,通过不同的信道估计算法来进行信道估计,然后对其性能进行了评估。信道状态信息参考信号被用来进行反馈估计,采用终端专用参考信号来进行解调。此外还对比了LTE中参考信号与LTE-A的参考信号的优缺点。最后给出了评估信道估计性能的仿真结果。