Power Control for Cognitive M2M Communications Underlaying Cellular with Fairness Concerns

Bo Gu, Cheng Zhang, Huanyu Wang, Yang Yao, Xiaojun Tan*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


The explosion in the number of machine-to-machine (M2M) devices, as envisioned in the Internet of Things (IoT), will create a significant challenge in terms of spectrum scarcity. One promising approach for addressing this problem is to accommodate the fast-growing M2M traffic with temporally unused or under-used licensed bands. In this paper, a cognitive M2M communications underlaying cellular network is studied where M2M devices reuse licensed spectrum of cellular users in an opportunistic and fair manner. In particular, we consider two fairness metrics: 1) proportional fairness; and 2) max-min fairness, and design two transmit power assignment strategies for M2M devices that achieve the global fairness objectives, while satisfying an interference temperature constraint at the base station (BS) side. Furthermore, we provide a heuristical floating-ceiling water-filling (FCWF) algorithm with little computational overhead to obtain the optimal solutions. The numerical results show that the proportional fair power assignment could maximize the joint system utility and improve average SINR, while denying data transmission to some M2M devices with high interfering channel gain to the BS; On the other hand, the max-min fair power assignment protects those with high interfering channel gain to the BS by offering them the largest possible power allocation, which is more applicable to scenarios where at least a minimum level of QoS should be guaranteed.

Original languageEnglish
Article number8703378
Pages (from-to)80789-80799
Number of pages11
JournalIEEE Access
Publication statusPublished - 2019 Jan 1


  • cognitive radio
  • convex optimization
  • fairness
  • HetNets
  • M2M
  • power control
  • spectrum scarcity
  • utility
  • white space

ASJC Scopus subject areas

  • General Computer Science
  • General Materials Science
  • General Engineering


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