摘要
为了有效地分配车间通信的功率和资源块(Resource Block,RB),提出基于高斯过程回归的功率分配(Gaussian Process Regression-based Power Allocation,GPR-PA)算法.GPR-PA算法采用年龄信息感知的传输功率和RB分配技术,允许网络动态的学习网络信息,并在最小车辆的信息年龄(Age of Information,AoI)超过预定阈值的概率与最大化网络动态的信息间达到平衡.结合GPR,GPR-PA算法采用分布式策略主动学习网络动态信息,估计车辆下一时隙的AoI和主动分配资源.仿真结果表明,相比于同类算法,提出的GPR-PA算法有效地降低了AoI超标概率.
To effectively al1ocate power and Resource Block,Gaussian Process Regression-based Power Allocation(GPR-PA)algorithm is proposed in this paper.An age of information(AoI)-aware transmission power and resource block(RB)allocation technique for vehicular communication networks is proposed.GPR-PA algorithm allows the network to actively learn its dynamics by balancing a tradeoff between minimizing the probability that the vehicles'AoI exceeds a predefined threshold and maximizing the knowledge about the network dynamics.In this regard,using a Gaussian process regression(GPR)approach,an online decentralized strategy is proposed to actively learn the network dynamics,estimate the vehicles'future AoI,and proactively allocate resources.Simulation results show a signi?cant improvement in terms of AoI violation probability,compared to several baselines,with a reduction of at least 50%.
作者
王维
WANG Wei(Network Information Center,Sichuan Normal University,Chengdu 610066,China)
出处
《小型微型计算机系统》
CSCD
北大核心
2021年第11期2428-2432,共5页
Journal of Chinese Computer Systems
基金
四川师范大学实验建设项目(SYJS201416)资助.
关键词
车间通信
信息年龄
功率分配
高斯过程回归
超标概率
vehicle-to vehicle
age of information
power allocate
gaussian process regression
violation probability
作者简介
王维,男,1982年生,硕士,高级工程师,CCF会员,研究方向为网络工程、信息系统安全、计算机应用.E-mail:wang_weiwei82@aliyun.com。
