基于设备能耗分簇的M2M通信随机接入方法  

Random Access Method for M2M Communications Based on Device Energy Consumption Clustering

在线阅读下载全文

作  者:阚求实 何继爱[1] 李志鑫 张琴 KAN Qiushi;HE Jiai;LI Zhixin;ZHANG Qin(School of Computer and Communication,Lanzhou University of Technology,Lanzhou 730050,China)

机构地区:[1]兰州理工大学计算机与通信学院,甘肃兰州730050

出  处:《测控技术》2023年第11期40-46,共7页Measurement & Control Technology

基  金:国家自然科学基金(61561031)。

摘  要:针对机器对机器(Machine to Machine, M2M)通信设备数量的持续增大导致M2M通信在当前蜂窝网络架构下会产生网络拥塞和接入成功率下降的问题,提出了一种基于设备能耗率分簇的M2M通信随机接入方法。该方法中M2M通信设备根据自身能量消耗率划分优等簇,即能耗率越大其优等级越高,优等级高的簇内设备享有随机接入资源的优先分配权,其随机接入资源由每簇的簇头代表簇接收,并在簇内设备之间通过随机接入竞争过程实现分配。仿真结果表明,相对于接入级限制(Access Class Barring, ACB)方法,该方法在接入成功率方面提升约5%,在延迟方面降低约10 s,能够有效降低设备能耗,提高设备接入的成功率。In response to the continuous increase in the number of machine to machine(M2M)communication devices,which leads to network congestion and a decrease in access success rate in M2M communication un-der the current cellular network architecture,a random access method for M2M communications based on de-vice energy consumption rate clustering is proposed.In this method,M2M communication devices are divided into priority clusters based on their energy consumption rate,that is,the higher the energy consumption rate,the higher the priority level,and the devices in the cluster with the higher priority level have priority in the alloca-tion of random access resources,which are received by a representative group of cluster heads in each cluster and distributed among the devices in the cluster through a random access competition process.The simulation results show that,compared with the access class barring(ACB)method,this method improves the access suc-cess rate by about 5%and reduces the latency by about 10 s,which can effectively reduce the energy con-sumption of devices and improve the success rate of device access.

关 键 词:机器对机器通信 随机接入 分簇 能量消耗率 

分 类 号:TN911.75[电子电信—通信与信息系统]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象