Distributed Uplink Offloading for IoT in 5G Heterogeneous Networks Under Private Information Constraints

被引:8
|
作者
Kure, Endre Hegland Hjort [1 ,2 ]
Engelstad, Paal [3 ]
Maharjan, Sabita [1 ,4 ]
Gjessing, Stein [1 ]
Zhang, Yan [1 ]
机构
[1] Univ Oslo, Dept Informat, N-0316 Oslo, Norway
[2] Simula Res Lab, Ctr Resilient Networks & Applicat, N-1364 Fornebu, Norway
[3] Univ Oslo, Dept Technol Syst, N-0316 Oslo, Norway
[4] Simula Metropolitan Ctr Digital Engn, Ctr Resilient Networks & Applicat, N-1325 Lysaker, Norway
来源
IEEE INTERNET OF THINGS JOURNAL | 2019年 / 6卷 / 04期
关键词
5G mobile communication; channel capacity; closed-form solutions; energy efficiency (EE); Internet of Things (IoT); optimization; probability; DATA AGGREGATION; LTE;
D O I
10.1109/JIOT.2018.2886703
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The expected influx of Internet of Things (IoT) in 5G will provide new opportunities for uplink traffic offloading. In general, base stations with proximity require lower transmission power of the IoT device (IoTD), thus saving energy consumption as spectral efficiency (SE) of the transmissions increase. By letting IoTDs send to base stations with better link conditions the IoTDs' battery lifetime is prolonged. In this paper, we present a many-to-many offloading scheme for uplink traffic. The scheme works when link conditions are private information and gives incentives to all involved players to participate. We believe this approach is better suited for the expected complex ecosystem of 5G base station cells. The sensitivity analyses show that there is a limited gain by requiring that the link conditions are public knowledge. Further, the suggested market optimizes the SE for all involved players. Numerical results show that the IoTDs can on average increase their SE with 25% and their spectral energy efficiency with 40%. The networks which are offloaded to and from can both expect an increase in the SE of 1%-6%. Sensitivity analyses show that the market equilibrium's benefits are robust as they stay positive for a range of different network configurations. Also, the work proves that market equilibrium is stable and unique. To derive the equilibrium, two approaches are presented, a closed form solution and a distributed algorithm, that both are solvable in polynomial time.
引用
收藏
页码:6151 / 6164
页数:14
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