Resource Allocation and User Grouping for Sum Rate and Fairness Optimization in NOMA and IoT

In this paper, we present the joint optimization of sum rate and fairness for contention based uplink multiple access with non-orthogonal multiple access (NOMA) communication system by resource allocation and user grouping. In particular, we study the cases of many users sharing the same resources that address application of the the internet of things (IoT). The key feature of contention based multiple access is to serve multiple users at the same time and frequency. With different power levels and user grouping, it can achieve better spectral efficiency over conventional orthogonal multiple access (OMA). However, unlike the OMA system, NOMA results in additional inter-user interference (IUI). It has also been shown that, without proper resource allocation for users in the uplink NOMA, the weak users can always be in outage. In this work, we have developed algorithms on subbands assignment, user grouping, and power allocation for joint optimization of sum rate and fairness. The algorithm allocates resources iteratively to handle the IUI in each iteration. Given a number of N
_s
subbands allocation to each user, we could prevent starvation of poor users, e.g. cell edge users. We have also compare and analyze the sum rate and fairness performance with different combination of L and N
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. We also find that, by properly limiting the maximum number of subbands each user can use, the system could better exploit multi-user diversity to improve the sum rate and hence the energy efficiency. The numerical simulations are also conducted to verify the results.