@article{15207,
  author = {Endre Kure and Paal Engelstad and Sabita Maharjan and Stein Gjessing and Yan Zhang},
  title = {Distributed Uplink Offloading for IoT in 5G Heterogeneous Networks under Private Information Constraints},
  abstract = {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{\textquoteright} battery lifetime is prolonged. In this work 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{\textquoteright}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.},
  year = {2019},
  journal = {IEEE Internet of Things Journal},
  volume = {6},
  pages = {6151-6164},
  month = {12/2018},
  publisher = {IEEE},
  doi = {10.1109/JIOT.2018.2886703},
}