# Sub-channel Assignment, Power Allocation and User Scheduling for Non-Orthogonal Multiple Access Networks

arXiv: https://arxiv.org/abs/1608.08313 · HTML: https://mlsanity.com/paper/1608.08313/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Aug 2016.

## Built on by (most cited first, 3 of 3)

- [Joint Resource Management for MC-NOMA: A Deep Reinforcement Learning Approach](https://mlsanity.com/paper/2103.15371/) (2021)
- [Deep Unsupervised Learning for Generalized Assignment Problems: A Case-Study of User-Association in Wireless Networks](https://mlsanity.com/paper/2103.14548/) (2021)
- [Should I Use This Synthetic Dataset for Training? How to Test with Minimal Real Data](https://mlsanity.com/paper/2608.27996/) (2026)

## Abstract (arXiv)

In this paper, we study the resource allocation and user scheduling problem for a downlink nonorthogonal multiple access network where the base station allocates spectrum and power resources to a set of users. We aim to jointly optimize the sub-channel assignment and power allocation to maximize the weighted total sum-rate while taking into account user fairness. We formulate the sub-channel allocation problem as equivalent to a many-to-many two-sided user-subchannel matching game in which the set of users and sub-channels are considered as two sets of players pursuing their own interests. We then propose a matching algorithm which converges to a two-side exchange stable matching after a limited number of iterations. A joint solution is thus provided to solve the sub-channel assignment and power allocation problems iteratively. Simulation results show that the proposed algorithm greatly outperforms the orthogonal multiple access scheme and a previous non-orthogonal multiple access scheme.