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Machine-to-machine (M2M) constitutes the communication paradigm at the basis of Internet of Things (IoT) vision. M2M solutions allow billions of multi-role devices to communicate with each other or with the underlying data transport infrastructure without, or with minimal, human intervention. Current solutions for wireless transmissions originally designed for human-based applications thus require a substantial shift to cope with the capacity issues in managing a huge amount of M2M devices. In this paper, we consider the multiple access techniques as promising solutions to support a large number of devices in cellular systems with limited radio resources. We focus on non-orthogonal multiple access (NOMA) where, with the aim to increase the channel efficiency, the devices share the same radio resources for their data transmission. This has been shown to provide optimal throughput from an information theoretic point of view. We consider a realistic system model and characterize the system performance in terms of throughput and energy efficiency in a NOMA scenario with a random packet arrival model, where we also derive the stability condition for the system to guarantee the performance. Index TermsInternet of Things, Machine-to-machine, Machine-type communication, non-orthogonal multiple access, NOMA. M. Shirvanimoghaddam is with the School

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Abstract-The 5G mobile network is expected to meet the diverse demands from multiple types of business services. At the same time, some of the 5G use cases come with hard, and often expensive to meet, requirements in terms of latency and bandwidth. It is a common understanding that one system can not fit all and there is a need for customizing network according to the requirements of specific business use cases. Network slicing is introduced to partition the physical network to different slices to be configured for providing different quality of service as requested by the slice' operator and required by the slice' users. Since these slices will be used by the businesses, e.g. verticals, allocating physical resources to the network slices, is not anymore only a matter of performance but also a matter of revenue and business model. In this paper, we address a joint resource and revenue optimization a novel auction based model. Through extensive simulation study, we demonstrate our proposed auction model can allocate network resources to network slices for providing (i) higher satisfaction of requirements per network slice, and (ii) increased network revenue.

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