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The fifth-generation (5G) and beyond 5G (B5G) wireless networks introduced massive machine-type communications (mMTC) to cope with the growing demand of massive Internet of Things (IoT) applications. However, the heterogeneous characteristics of massive IoT and diverse quality of service (QoS) requirements may lead to severe interference that could degrade the expected QoS of the cellular ecosystem. Therefore, this article studies the impact of interference caused by mMTC connections. We theoretically model the intercell interference (ICI) minimization problem for the existing orthogonal multiple access (OMA) technique and propose its corresponding solution. Furthermore, we jointly solve the ICI and the cochannel interference minimization problem for the IoT users when the nonorthogonal multiple access (NOMA) technique is used. For the proposed OMA and NOMA schemes, we design a cooperative scheduler to reduce the impact of such interference. The results show that our proposed schemes provide up to 58%, 75%, and 100% more improvements in terms of user’s data rates, energy consumption, and connection density, respectively.
Interference , NOMA , Signal to noise ratio , Internet of Things , 5G mobile communication , Quality of service , Performance evaluation, Intercell interference (ICI) , massive machine-type communication (MMTC) , narrow-band IoT (NB-IoT) , nonorthogonal multiple access (NOMA) , orthogonal multiple access (OMA)
Interference , NOMA , Signal to noise ratio , Internet of Things , 5G mobile communication , Quality of service , Performance evaluation, Intercell interference (ICI) , massive machine-type communication (MMTC) , narrow-band IoT (NB-IoT) , nonorthogonal multiple access (NOMA) , orthogonal multiple access (OMA)
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 9 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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