Capacity and Energy Efficiency Trade-off in Multi-Packet Reception Wireless Systems

Abstract

The radio access in Internet-of-Things (IoT) networks requires minimizing the energy consumption while achieving the capacity requirements especially for high density deployment. The Multi-Packet Reception (MPR) systems can potentially increase the capacity of devices due to the capability of decoding multiple transmitted packets at the receiver. However, the aggregate interference in such scenarios can lead to unfair distribution of the resources and eventually waste of energy. Therefore, this work provides an analytical characterization of the trade-off between capacity and energy consumption while regulating the channel access of multiple transmitters to a single-MPR receiver. The theoretical modeling considers different densities of spatially distributed nodes and their channel propagation conditions, in addition to different capture sensitivity thresholds at the receiver. The model is validated through simulation and it is shown to be an effective tool to identify the optimal channel access probability that maximizes the capacity per energy consumption.

Analysis on the Current Consumption of Applying the Huffman Codification for Data Transmission using the ESP-NOW Protocol

“…Usually, IoT devices employ the 900 MHz or 2.4 GHz frequency to transmit data, the frequency selection depends on the distance and throughput required for each application. Some authors suggest methods to save energy while transmitting data [10], others methods suggest using the radio only when the transmission link is available for transmission [11]. In this scenario data compression algorithms are a good choice to reduce the amount of data to be transmitted [12].…”