Optimization of the Energy-Efficient Relay-Based Massive IoT Network

被引:45
作者
Lv, Tiejun [1 ]
Lin, Zhipeng [1 ]
Huang, Pingmu [1 ]
Zeng, Jie [1 ]
机构
[1] Beijing Univ Posts & Telecommun, Sch Informat & Commun Engn, Beijing 100876, Peoples R China
基金
中国国家自然科学基金;
关键词
Decode-and-forward (DF) relay; energy efficiency (EE); green massive Internet of Things (mIoT); massive multiple-input multiple-output (MIMO); resource allocation; CELLULAR NETWORKS; MIMO; COMMUNICATION; ALLOCATION; INTERNET; MACHINE; DESIGN;
D O I
10.1109/JIOT.2018.2829827
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
To meet the requirements of high energy efficiency (EE) and large system capacity for the fifth-generation Internet of Things (IoT), the use of massive multiple-input multiple-output technology has been launched in the massive IoT (mIoT) network, where a large number of devices are connected and scheduled simultaneously. This paper considers the energy-efficient design of a multipair decode-and-forward relay-based IoT network, in which multiple sources simultaneously transmit their information to the corresponding destinations via a relay equipped with a large array. In order to obtain an accurate yet tractable expression of the EE, first, a closed-form expression of the EE is derived under an idealized simplifying assumption, in which the location of each device is known by the network. Then, an exact integral-based expression of the EE is derived under the assumption that the devices are randomly scattered following a uniform distribution and transmit power of the relay is equally shared among the destination devices. Furthermore, a simple yet efficient lower bound of the EE is obtained. Based on this, finally, a low-complexity energy-efficient resource allocation strategy of the mIoT network is proposed under the specific quality-of-service constraint. The proposed strategy determines the near-optimal number of relay antennas, the near-optimal transmit power at the relay, and near-optimal density of active mIoT device pairs in a given coverage area. Numerical results demonstrate the accuracy of the performance analysis and the efficiency of the proposed algorithms.
引用
收藏
页码:3043 / 3058
页数:16
相关论文
共 46 条
[31]   An Overview of Massive MIMO: Benefits and Challenges [J].
Lu, Lu ;
Li, Geoffrey Ye ;
Swindlehurst, A. Lee ;
Ashikhmin, Alexei ;
Zhang, Rui .
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 2014, 8 (05) :742-758
[32]   Energy Efficiency Tradeoff Mechanism Towards Wireless Green Communication: A Survey [J].
Mahapatra, Rajarshi ;
Nijsure, Yogesh ;
Kaddoum, Georges ;
Ul Hassan, Naveed ;
Yuen, Chau .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2016, 18 (01) :686-705
[33]  
Pielli C., 2016, P IEEE GLOB WORKSH G, P1
[34]  
Sarwesh P, 2015, 2015 INTERNATIONAL CONFERENCE ON GREEN COMPUTING AND INTERNET OF THINGS (ICGCIOT), P784, DOI 10.1109/ICGCIoT.2015.7380569
[35]   Research Directions for the Internet of Things [J].
Stankovic, John A. .
IEEE INTERNET OF THINGS JOURNAL, 2014, 1 (01) :3-9
[36]  
Suraweera H. A., 2013, P IEEE INT C COMM IC, p[1, 1]
[37]   Linear Precoding for Multi-Pair Two-Way MIMO Relay Systems With Max-Min Fairness [J].
Tao, Meixia ;
Wang, Rui .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2012, 60 (10) :5361-5370
[38]   Stress Detection and Management [J].
Thapliyal, Himanshu ;
Khalus, Vladislav ;
Labrado, Carson .
IEEE CONSUMER ELECTRONICS MAGAZINE, 2017, 6 (04) :64-69
[39]   Overlapping User Grouping in loT Oriented Massive MIMO Systems [J].
Tian, Run ;
Liang, Yuan ;
Tan, Xuezhi ;
Li, Tongtong .
IEEE ACCESS, 2017, 5 :14177-14186
[40]   Resource Allocation Optimization in Multi-User Multi-Cell Massive MIMO Networks Considering Pilot Contamination [J].
Tri Minh Nguyen ;
Vu Nguyen Ha ;
Long Bao Le .
IEEE ACCESS, 2015, 3 :1272-1287