# Neighbor-Aware Non-Orthogonal Multiple Access Scheme for Energy Harvesting Internet of Things
## 1 Introduction  
Internet of Things (IoT) devices have a limited battery capacity [1], which is one of the characteristic drawbacks of IoT systems. To overcome this drawback, many researchers have focused on the use of energy harvesting [2, 3, 4]. With energy harvesting, IoT devices can charge their battery by themselves, and therefore the operators of IoT systems do not need to replace and charge the IoT devices' batteries, which provides low operating expenditure. Meanwhile, many researchers have given much attention to non-orthogonal multiple access (NOMA) because it can significantly improve the spectral efficiency [5, 6, 7]. Additionally, the 5G standard defined by the third generation partnership project (3 GPP) supports two types of NOMA: (1) power-domain-based NOMA and (2) code-domain-based NOMA. In the first type (i.e., power-domain-based NOMA), different powers are assigned to different IoT devices by considering their channel conditions for simultaneous transmissions to the base station (BS). On the other hand, BS can retrieve the desired signals using the received power difference and some signal processing techniques (e.g., successive interference cancellation). In the code-domain-based NOMA, different IoT devices use distinct codes, and therefore they are multiplexed over the same frequency. In general, the domain-based NOMA can be simply implemented without any significant changes of existing networks compared with the code-domain-based NOMA [7]. Specifically, for the power-domain-based NOMA, at the receiver side (i.e., BS), the only simple multiuser detection algorithm such as successive interference cancellation is needed. On the other hand, the transmitter (i.e., IoT devices) does not need any modification. Therefore, we consider the power-domain-based NOMA in this paper. In the power-domain-based NOMA, each IoT device can increase its data rate by increasing its transmission power. However, excessively high transmission power can cause an energy outage of an IoT device and have a detrimental effect on the signal-to-interference-plus-noise ratio (SINR) of neighbor IoT devices, which indicates that each IoT device should choose the appropriate transmission power to maximize the aggregated data rate of IoT devices while preventing its energy outage. Even though a centralized approach can help decide transmission powers of IoT devices, a huge signaling overhead can occur and a centralized entity can be overloaded. In this paper, we propose a neighbor-aware NOMA scheme (NA-NOMA) where each IoT device determines whether to transmit data to BS and the transmission power at each time epoch in a distributed manner by considering its energy level and other devices' (i.e., neighbors') transmission powers. To maximize the aggregated data rate of IoT devices while keeping an acceptable average energy outage probability, a constrained stochastic game model is formulated, and the solution of the model is obtained by means of a best response dynamics-based algorithm. Evaluation results show that NA-NOMA can increase the average data rate up to 22% compared to a probability-based scheme while providing a sufficiently low energy outage probability (e.g., 0.05). In addition, it is found that IoT devices using NA-NOMA adaptively change the operations (e.g., transmission powers) according to their environments (e.g., harvesting probability). The contributions of this paper are as follows: (1) we optimize the policy on the transmission of IoT devices to maximize the aggregated data rate of IoT devices while keeping an acceptable average energy outage probability under the energy harvesting NOMA environment; (2) the optimal transmission policy can be achieved with small overhead (i.e., few iterations), and therefore the proposed scheme can easily achieve the optimal performance in practical systems; (3) we evaluate the proposed scheme under diverse environments, which can give useful guidelines to design energy harvesting and NOMA-based IoT systems.