Aloha-NOMA for Ambient Backscatter M2M Communication in IoT Networks with Random Power Levels and Frequency Channel Assignment

Abstract

Internet of Things as known as IoT is a network pointing to a series of interconnected devices that are communicating with each other. M2M communication protocol is integral part of IoT to allowing multiple devices to communicate smoothly. Aloha-NOMA for ambient backscatter M2M communication can provide high throughput matched with low complexity of Aloha-NOMA while leveraging on the low power and cost of ambient backscatter communication links. This paper critically studies the application of Aloha-NOMA for backscatter M2M communication utilizing multichannel and random power levels. In this paper, multichannel Aloha-NOMA throughput analysis had been done in order to observe the impact of adding sub channels. Throughput increased directly proportional as number of sub channels. Then, Aloha-NOMA performances are compared against Ambient Backscatter Aloha-NOMA in which more channels on the line with backscatter channels. Results indicate the combination of random power levels selection with random frequency channel selection yields significant throughput improvement.