基于异构网络的Massive MIMO RZF预编码

使用异构网络与Massive MIMO系统相结合,在小区分布SCAs来分担基站流量,以不牺牲用户QoS的前提下,提高小区的能源利用率.在现有RZF预编码进行改进使之可以在基于异构网络的Massive MIMO系统下应用,并使系统达到渐近最优性能.     

异构网中的高能效混合协作传输方法

该文提出一种异构网中高能量效率的协作传输方法。协作联合处理(CoMP-JP)和协作波束成型(CoMP- CB)是异构网中两种常用的协作传输方法。通过研究CoMP-JP和CoMP-CB发现：CoMP-JP利用较大的阵列增益能够降低基站的发射功耗,但是需要消耗很高的信号处理功耗、骨干网功耗和电路功耗;CoMP-CB虽然消耗较少的信号处理和骨干网功耗,但是会导致较大的发射功耗。为了充分利用CoMP-JP和CoMP-CB在降低能耗方面的优点,并且有效地降低电路功耗,该文提出一种基于CoMP-JP和CoMP-CB传输的混合协作预编码方法。仿真结果表明,与CoMP-JP和CoMP-CB模式下的迫零预编码相比,所提出的混合协作预编码能够支持更高的系统频谱效率,并且大大提高系统的能量效率。     

FDD Massive MIMO商用挑战

随着5G标准的发展,第一个3GPP 的5G NR标准版本Rel.15计划于2018年6月完成.5G商用场景众多,如增强移动宽带(eMBB)、低时延与高可靠通信(URLLC)、大连接物联网(mMTC)等,其中eMBB业务场景是最传统、运营商最关注、与用户关系最密切的.在众多5G技术中,对eMBB业务性能影响最大的是Massive MIMO.可以预见,未来的5G商用产品中,Massive MIMO是最有可能优先部署的5G标志性技术.     

基于谱聚类的异构蜂窝超密集网络高能效资源分配算法

为了解决5G移动通信超密集场景下功耗较大、频谱紧张、能效不高等问题,针对两层异构蜂窝非正交多址接入网络,提出了一种基于能效最大的资源分配算法.在超密集场景下行通信链路中,通过分步求解频率资源分配和功率分配方案将NP-hard优化问题转化为确定性的约束寻优问题,提出了基于谱聚类用户分组算法和改进的k-means基站聚类分...     

同构与异构网中预测资源分配的性能

预测资源分配能利用蜂窝网络的残余资源大大提升吞吐量。本文面向视频点播等非实时业务,研究在使95%用户播放视频的卡顿时间小于其预期值时预测资源分配能够使网络支持的非实时业务请求到达率提升多少。为了研究预测窗长对预测资源分配性能的影响,考虑一种性能接近最优解的低复杂度双门限策略,分析了预测窗长度、残余带宽、预测方法、用户接入和小区间干扰对其性能的影响。研究结果表明,通过对所需各种信息设计合理的预测方法,预测误差对双门限策略影响很小;预测窗越长,该策略相对于传统非预测方法的吞吐量增益越大、但增速随窗长增加逐渐变缓;网络残余带宽的方差越大,双门限策略相对于非预测方法的吞吐量增益越大;基于残余带宽的接入方法在异构网络中性能远优于基于接收功率最大的用户接入,且网络负载越重、增益越大。      

MIMO天线资源分配方案

建立天线分组前后的注水功率分配模型,阐述了最优天线分组方案。     

Massive MIMO关键技术及应用初探

随着无线通信技术和新型业务的快速发展,人们对数据传输速率提出了更高的需求。为进一步提高数据传输速率,通过增加基站天线数目构建Massive MIMO系统,是一种高效而相对便捷的方式。本文介绍了Massive MIMO研究进展和技术原理,并针对其特有的关键技术信道信息的获取、天线阵列的设计、低复杂度传输技术进行了分析讨论,最后从覆盖、容量、感知和上行干扰四个维度对4G网络上部署的Massive MIMO系统进行了评估分析。     

FDD Massive MIMO 技术演进方向解析

Massive MIMO技术可以直接通过增加天线数增加系统容量,并利用不同用户间信道的近似正交性降低用户间干扰,实现多用户空分复用. Massive MIMO是传统MIMO技术的扩展和延伸,其特征(集中式Massive MIMO)在于以大规模天线阵的方式集中放置数十根甚至数百根以上天线.Massive MIMO技术可以直接通过增加天线数增加系统容量.     

Massive MIMO广播波束场景化研究

Massive MIMO和波束赋形是5G的一项关键技术。5G将LTE时期的MIMO进行了扩展和延伸,即LTE的MIMO最多8天线,到5G扩增为16/32/64/128天线,被称为“大规模”的MIMO。本案通过对不同场景Massive MIMO波束调整方案进行研究,输出场景化的设置方案,以期为后期Massive MIMO优化提供参考。     

基于中断概率的多输入多输出异构网络资源分配

为充分提高通信网络的频谱效率,异构网络采用多个微小基站同时在相同频段上支持用户数据传输的方式;为保障系统通信效能,需要有效控制不同数据接口上信号之间存在的相互干扰。提出了采用资源分配方法利用通信中断概率作为衡量不同微小基站数据分支通信性能的准则,通过将中断概率约束条件有效近似,从而使原复杂矩阵优化问题转换为基于标量的几何规划问题,进而极大地降低计算复杂度。数值仿真结果验证了所提方法的有效性。     

Optimal Resource Allocation in Heterogeneous MIMO Cognitive Radio Networks

The optimal resource allocation in MIMO cognitive radio networks with heterogeneous secondary users, centralized and distributed users, is investigated in this work. The core aim of this work is to study the joint problems of transmission time and power allocation in a MIMO cognitive radio scenario. The optimization objective is to maximize the total capacity of the secondary users (SUs) with the constraint of fairness. At first, the joint problems of transmission time and power allocation for centralized SUs in uplink is optimized. Afterwards, for the heterogeneous case with both the centralized and distributed secondary users, the resource allocation problem is formulated and an iterative power water-filling scheme is proposed to achieve the optimal resource allocation for both kinds of SUs. A dynamic optimal joint transmission time and power allocation scheme for heterogeneous cognitive radio networks is proposed. The simulation results illustrate the performance of the proposed scheme and its superiority over other power control schemes.     

多用户大规模MIMO系统能效资源分配算法

该文针对多用户大规模多输入多输出(MIMO)移动通信上行系统,提出一种基于能效优化的资源分配算法。所提方法在采用最大比合并(MRC)接收情况下,满足用户数据速率和可容忍的干扰水平约束条件下,以最大化系统能效下界为准则建立优化模型。根据分数规划的性质,把原始的分数最优化问题转换成减式的形式,进而采用凸优化的方法,通过联合调整基站端的发射天线数和用户的发射功率来优化能效函数。仿真结果表明,所提算法与穷举算法在能效上的差距不足9%,并且有较好的系统频谱效率性能,同时算法复杂度得到了显著降低。     

Efficient Network Slicing with Dynamic Resource Allocation

With the rapid development of wireless network technologies and the growing de?mand for a high quality of service(QoS),the effective management of network resources has attracted a lot of attention.For example,in a practical scenario,when a network shock oc?curs,a batch of affected flows needs to be rerouted to respond to the network shock to bring the entire network deployment back to the optimal state,and in the process of rerouting a batch of flows,the entire response time needs to be as short as possible.Specifically,we re?duce the time consumed for routing by slicing,but the routing success rate after slicing is re?duced compared with the unsliced case.In this context,we propose a two-stage dynamic net?work resource allocation framework that first makes decisions on the slices to which flows are assigned,and coordinates resources among slices to ensure a comparable routing suc?cess rate as in the unsliced case,while taking advantage of the time efficiency gains from slicing.     

异构蜂窝网络中基于能效的非正交多址接入下行功率分配算法

该文针对应用非正交多址接入(NOMA)技术的异构蜂窝网络,在考虑层间层内干扰的情况下,提出一种能效最大化的功率分配算法。该算法主要包括两部分,一部分为子信道内用户功率分配因子的求解,主要利用差分优化的方法,迭代求解。另一部分为子信道间的功率分配,主要利用凹凸程序法将原有的非凸问题简化为可解的凸问题,最后利用拉格朗日求解法得出功率最优解。仿真结果表明该算法有良好的迭代性,且新算法表明利用NOMA技术得到的系统能效较利用正交技术得到的系统能效提高了至少44%以上。     

LTE-A异构网络下的高效资源分配算法

分析了OFDMA上行系统中,由宏基站(macrocell)和家庭式基站(femtocell)组成的双层网络,并提出了高效的资源分配算法。为避免严重的跨层干扰导致双层网络中的资源分配不协调,提出了一个跨层干扰控制算法。在基于干扰控制算法的结果上,提出包括功率分配和频谱分配的资源分配算法,以满足UE的目标速率,并获得较好的吞吐量性能。通过仿真,结果显示所提的资源分配算法相比较传统的算法,尤其在UE QoS保证和吞吐量性能的体现上,能获得明显的性能增益。     

Full-duplex Distributed Massive MIMO System with Optimal Beamforming and Resource Allocation for WPCN

This paper proposes a joint beamforming and resource allocation scheme to maximize the minimum capacity for wireless powered communication network (WPCN) designed for multi-user distributed massive multi-input multi-output (DM-MIMO) system with full-duplex radio remote heads (RRHs), which enable simultaneous uplink (UL) and downlink (DL) communications. The minimum capacity is maximized by a proposed algorithm based on the non-negative matrix theory. The simulation results have demonstrated that the achievable max-min capacity of the DM-MIMO is considerably higher compared to that of the CMMIMO system. It has also showed that the convergence speed of the proposed algorithm is so fast.     

Efficient Resource Allocation with Improved Interference Mitigation in FFR-Aided OFDMA Heterogeneous Networks

Fractional frequency reuse (FFR) has recently emerged as an efficient inter-cell interference coordination technique for orthogonal frequency division multiple access (OFDMA) based multi-tier cellular networks due to its low complexity, minimal signaling over-head, and coverage improvement. In this work, an intermediary region (IR) at the border of the center region (CR) and edge region (ER) is defined, which prevents severe cross-tier interference and is usually ignored by other schemes. Furthermore, a strategic resource allocation scheme is proposed, which allows macro users in this new region to be served more resources due to their good channel conditions close to the serving base station (BS), while femto users are assigned resource blocks from sub-bands that receive the least net interference from a set of usable sub-bands in any region. We find by analysis and simulation the optimal threshold for IR, which minimizes the cross-tier interference, and show that the femto throughput is also maximized for this threshold. Numerical results show the proposed scheme outperforms other notable schemes in terms of throughput and outage performances.     

全双工大规模MIMO异构网络频谱效率分析及优化

本文研究全双工大规模多输入多输出（multiple-input-multiple-output, MIMO）异构网络。推导了采用迫零（zero-forcing, ZF）预编码/检测方案的上下行渐近信干噪比（signal-to-interference-plus-noise ratio, SINR）的闭合表达式。根据理论分析,提出了基于几何规划（geometric programming, GP）的功率控制方案和基于部分用户选择（partial users selection, PUS）的跨层干扰消除方案,改善系统频谱效率。仿真结果表明,与传统方案相比本文提出的功率控制方案和跨层干扰消除方案能够显著提升异构网络的频谱效率。