# Software-Defined Visible Light Communication for Internet of Things: A Low-Complexity Approach
## 1 Introduction  
As the demand for wireless data continues to grow, existing spectrum resources are under immense pressure. The urgent need for new spectral resources has become evident to keep up with this trend. In this context, visible light communication (VLC) technology has emerged as a promising solution to address the spectrum shortage [1, 2, 3, 4, 5, 6]. VLC uses light-emitting diode (LED) lights for data transmission, making it particularly suitable for the upcoming ubiquitous computing and Internet of Things (IoT) ecosystems [7, 8, 9]. Although the visible light spectrum provides a wide bandwidth ranging from 400 to 800 THz, the inherent physical limitations of LED modulation bandwidth significantly constrain the potential for improving data transmission rates. As a result, despite its theoretical bandwidth advantage, the practical performance of VLC remains limited by hardware constraints. The primary objective of indoor VLC is to meet lighting requirements. Consequently, LEDs used in VLC systems typically have a much wider half-power angle compared to conventional optical wireless communication systems [10, 11]. This wider half-power angle significantly increases the energy received by the receiver through the diffuse channel. Additionally, reflections from walls further enhance this effect. However, this also considerably increases inter-channel interference, which negatively impacts system performance. In the era of ubiquitous connectivity, traditional VLC systems, which rely on fixed hardware architectures, lack flexibility and cannot accommodate the diverse application scenarios of the IoT. The integration of VLC and IoT offers a promising solution for high-speed, energy-efficient, and interference-free wireless communication. Software-defined VLC (SD-VLC) introduces a highly programmable communication platform that enablesdynamic, software-based adjustments of modulation schemes, bandwidth allocation, and equalization algorithms without the need to modify the underlying hardware. This flexibility is particularly crucial for heterogeneous IoT environments, where devices exhibit significant variations in data rates, latency, and power consumption requirements. Furthermore, SD-VLC significantly reduces the deployment and maintenance costs of IoT networks by allowing communication protocols to be optimized through software updates, eliminating the need for costly hardware upgrades. By offering a flexible, adaptive, and cost-effective VLC-based communication solution, SD-VLC lays a solid foundation for the development of scalable, intelligent, and energy-efficient wireless ecosystems. To fully leverage the advantages of SD-VLC, it is essential to adopt modulation and equalization techniques that align with the software-defined paradigm. Traditional analog-based approaches often rely on fixed circuit implementations, limiting their adaptability to dynamic channel conditions and diverse application scenarios. In contrast, digital modulation schemes provide greater flexibility, enabling software-based implementation and real-time reconfiguration. These digital methods reduce hardware complexity while maintaining high spectral efficiency, making them particularly suitable for software-defined optical communication systems. Similarly, adaptive equalization plays a crucial role in mitigating channel impairments in VLC, particularly in multipath fading environments. Digital equalization techniques, implemented within an SD-VLC framework, offer computationally efficient solutions for dynamically compensating signal distortions. By continuously adjusting equalization parameters through software-defined updates, the receiver can enhance its resilience against varying channel conditions. The combination of digital modulation and software-defined equalization enables a fully reconfigurable VLC system, improving adaptability, robustness, and overall system performance, while also facilitating seamless integration into IoT and next-generation wireless networks.