Towards Realistic Waveform-Level IoT Network Simulation via IQ Mixing

TL;DR

IQSim introduces a waveform-level IoT network simulation approach using IQ stream mixing, capturing physical effects missed by traditional packet-level simulators, enabling more realistic and detailed experiments.

Contribution

The paper presents IQSim, a novel simulation paradigm that models physical-layer effects at the waveform level using IQ stream mixing, improving realism over existing packet-level methods.

Findings

Preliminary results support real-time execution feasibility.

IQSim captures physical-layer effects like interference and leakage.

The approach enables detailed waveform-level IoT network simulation.

Abstract

Most Internet of Things (IoT) network simulators are packet-level discrete-event systems in which physical-layer (PHY) behavior is approximated through analytical interference rules and precomputed error models. While this enables scalable experiments, it can miss key waveform-level effects such as adjacent-channel leakage, cross-modulation interference between coexisting signals, and receiver imperfections, which are critical in heterogeneous sub-GHz ISM-band coexistence scenarios. This paper discusses these limitations and introduces IQSim, a simulation paradigm based on in-phase/quadrature (IQ) stream mixing. Instead of predicting packet outcomes from abstract collision models, IQSim maintains a shared complex baseband IQStream into which simulated transmissions are inserted as IQ waveforms after propagation processing, and then demodulated by software-based receivers or hardware gateways. We outline the end-to-end workflow, including online or offline waveform generation, IQ-domain propagation, waveform superposition, and delivery to gateways. We also report preliminary prototype results supporting the feasibility of real-time execution.