面向未来移动网络密集连接的关键技术综述

doi:10.11959/j.issn.1000-436x.2021094

Abstract

Abstract:

Based on reviews of the work regarding dense connection, the strategic technologies for dense connection in the upcoming future mobile communication were illuminated.The state of the art of dense connection, including network architecture and related technologies, the transmission technology of dense connection, and the access technology of dense connection were analyzed.A flexible access network structure with verity of connection forms coexisting was proposed.Aiming at the asymmetry of uplink and downlink coverage and considering the QoS requirements of users, a dense terminal access scheme based on the uplink-and-downlink-separated network architecture was proposed.The necessity of the three-dimensional network architecture and the integration of communication and computing to meet the needs of large-scale networking and dense connection were illuminated.Based on technologies such as terahertz and block chain, the future strategic exploratory trends such as the upward extension of frequency bands and the sharing of spectrum resources were discussed and prospected.

Key words: dense connection, mobile network, network architecture, access technology, communication and computation integration

CLC Number:

TN92

Zhihong QIAN, Lin XIAO, Xue WANG. Review on strategic technology of dense connection for the future mobile network[J]. Journal on Communications, 2021, 42(4): 22-43.

Figures/Tables 11

References 149

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指标	数值
峰值速率/(Gbit·s^?1)	100
用户体验速率/(Gbit·s^?1)	1
连接密度/(万·km^-2)	1 000
时延/ms	0.1
能效/(bit·J^-1)	200
频谱效率/(bit·(s·Hz^-1))	200

基站类型	发射功率/dBm	覆盖范围/m	回程
宏基站	46	1 000~25 000	S1接口
小基站	30~37	<300	X2接口
微微基站	23~30	<100	X2接口
家庭基站	<23	<50	IP
中继站	30	<300	无线

分类	含义	方案特性	文献
基于代价函数	将影响用户体验的指标加权在一起，用户通过对比候选网络的代价函数值进行选择	权重的建立往往具有较大的主观性，如果参数两两对比后显示不一致，则需要再次耗时构造判断矩阵检查	文献[12-13]
基于组合优化算法	通常采用模糊逻辑算法和人工神经网络算法等。用户收集网络参数，并上报给切换管理实体，利用人工神经网络进行训练，得到接入决策结果	需要中心控制实体进行辅助	文献[14-15]
基于负载均衡	将终端设备的接入请求分配至负载最低的接入点，当系统的负载达到一定程度时，将执行垂直切换进行重新分布，达到负载均衡	用户有可能连接到质量较差的网络中，无法有效保障用户实时或非实时业务的QoS需求	文献[16]
基于博弈论	在多用户同时接入选网的环境下，有较高的公平性和准确性	所有参与者都计算各自的利益，可能会损害异构网络整体性能；为了不同参与者的纳什均衡收敛，算法复杂度高；一个博弈周期只能得出一个用户选网结果，密集用户选网效率低	文献[17]

类别	技术	方法	文献	优点	缺点
	天线抵消	—	文献[44]	易实施，抵消能力，稳健性好	需手动调谐射频电路，固定天线，发射功率受限
被动自干扰消除	定向天线	—	文献[42]	降低Tx与Rx之间耦合的可能性	天线波束范围限制
	天线隔离	—	文献[50]	由于路径损耗，SI 信号强度衰减；设备间干扰低	设备体积、地理位置、成本受限制；仅限SISO场景
		直接耦合	文献[45, 51,52,53]	对线性和非线性干扰都能有效抑制	灵活性不够
主动自干扰消除	射频域	间接耦合	文献[46, 54]	射频域自干扰消除结构易实现，原理简单	成本较高，器件所占用体积大
主动自干扰消除		基于导频法	文献[47]	调制独立性	抵消能力有限
	数字域	自适应消除	文献[48, 55]	自适应对抗时变环境，实时性好	很难兼顾收敛性和稳态性
		基于预编码	文献[56]	能实现高级优化，容量优化	需信号估计，需进行自干扰信道矩阵的奇异值分解

方向	类别	方法	性能分析	文献
信道估计	线性信道估计	提出了一种基于压缩的线性最小均方误差信道估计算法	与传统的线性相比，降低了计算复杂度，提高了效率	文献[70]
信道估计	非线性信道估计	利用物理环境中有限散射引起的低秩特性，提出了一种基于并行因子的估计方案	较ESPRIT算法，显著提高了估计性能。在天线数目较大的情形下，计算复杂度小	文献[71]
帧结构	基于导频移位结构	确定波束成形向量以减少来自其他小区的干扰；执行接收波束成形；进行信道估计	有效地降低了导频干扰的影响，并提高了频谱效率	文献[72]
帧结构	叠加型结构	提出了基于叠加导频的信道估计非迭代方案，推导了匹配滤波器输出端的上行SINR	叠加型帧结构在提高大规模MIMO系统频谱利用率方面要优于传统帧结构	文献[73]
导频分配	基于信道协方差	将设备分组，用信道协方差矩阵的正交性衡量用户间潜在干扰，为其分配相同导频序列而不影响系统性能	提高了频谱效率；在高信噪比和强相关情况下，均方误差性能增益显著。	文献[74]
导频分配	智能导频分配	测量相同导频用户引起的区间干扰；将最小干扰的导频分配给最差信道质量的用户	优化了系统内用户的最小上行SINR	文献[75]
预编码	线性编码	ZF、匹配滤波、预编码、MMSE预编码	计算复杂度低，实用性强	文献[76]
预编码	非线性编码	THP、脏纸编码	复杂度较高，但性能优于线性编码	文献[77]

Review on strategic technology of dense connection for the future mobile network

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分类	含义	性能对比	文献
SA	将时间分为离散的时隙，用户必须等到下一个时隙才可以发送数据	减少了数据产生冲突的可能性，提高了信道的利用率	文献[116]
DSA	用户将相同的数据包在上行接入周期内不同时隙上重复发送多次	在适中的负载下，较SA相比吞吐量更高、时延更低。但对于密集用户接入网络场景，接入效果还是不理想	文献[117]
CRDSA	在接收端引入了SIC，这使很多原本因碰撞而被丢失的数据包被还原出来，避免了重传	与DSA相比，CRDSA吞吐量和时延等性能都有所提高，且有更高的解决碰撞能力	文献[118]
IRSA	每个用户均具有不同的数据包重发次数，并在接收端利用迭代置信传播对数据包解码	实现比CRDSA更高的吞吐量	文献[119-120]

优势	如何支持高效频谱共享
去中心化	区块链不需要任何信任机构背书，减少了频谱共享网络开销，提高了系统的完整性和隐私性
透明化	频谱用户和服务提供商的交易记录在分布式区块链账本上，基于区块链的频谱共享可更好地了解频谱使用情况
不可篡改	区块链分类账可以很好地抵抗攻击或恶意用户造成的修改，这也确保了频谱服务的可靠性，提高了网络实施的准确性
可用性	区块链向所有实体广播服务信息，网络参与者都可以访问频谱共享数据库
非许可	没有单一可信实体作为控制网络的中央机构，新用户可不需要寻求批准地加入系统中，灵活性高
安全性	区块链具有强大的安全能力抵御拒绝服务风险和内部攻击

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