Nombre: HIGOR ARAUJO FIM CAMPOREZ
Fecha de publicación: 21/03/2025
Junta de examinadores:
Nombre |
Papel |
|---|---|
| ALEXANDRE DE ALMEIDA PRADO POHL | Examinador Externo |
| HEINRICH WÖRTCHE | Coorientador |
| HELDER ROBERTO DE OLIVEIRA ROCHA | Presidente |
| JAIR ADRIANO LIMA SILVA | Coorientador |
| MARIA JOSE PONTES | Examinador Interno |
Páginas
Sumario: The Internet of Things (IoT) growth, particularly applications involving wireless devices, has significantly increased the demand for signal bandwidth. However, Radio Frequency (RF) wireless systems presented a limited spectrum to support massive device connections and susceptibility to electromagnetic interference. These challenges have increased the interest in exploring
alternative solutions to face RF issues while maintaining high data rates, low latency, reliability, and cost efficiency. Advancements in Light Emitting Diode (LED) technology have introduced highly energy-efficient lighting capable of high-speed modulation of light intensity. Thus, these characteristics have driven research into Visible Light Communication (VLC), which can utilize existing lighting infrastructures for data transmission using a broad and unregulated optical spectrum ( 400 THz). Additionally, VLC can also provide physical layer security, low power consumption, high transmission speeds, and immunity to RF electromagnetic interference. Spectral efficiency and high data rates are critical for VLC systems, with Orthogonal Frequency
Division Multiplexing (OFDM) emerging as a robust and spectrally efficient modulation technique for indoor applications. However, nonlinearities introduced by multicarrier signals in LED-based systems can degrade performance. To address these issues, techniques such as Constant-Envelope OFDM (CE-OFDM) have been developed to mitigate Peak-to-Average Power Ratio (PAPR), improving power efficiency and reducing distortions, particularly in highpower transmission scenarios. Additionally, VLC faces several challenges, including signal blockage by opaque objects, confinement of signals, and limited Access Points (AP) coverage. Addressing these limitations often requires deploying ultra-dense networks to ensure reliable connectivity across large areas. However, such dense deployments can lead to frequent handovers, increasing infrastructure costs and complexity. This thesis evaluates the application of larger signal amplitudes despite the LED-nonlinearities to enable data transmission over long distances, evaluating the conventional and constantenvelope OFDM performances. Furthermore, it proposes a Modified Genetic Algorithm (MGA) optimization procedure combined with time series Machine Learning (ML) classifiers to minimize handovers in both a digital twin-based simulation system and experimental VLC setups. The proposed handover scheme considers receiver trajectory information to reduce handover frequency while maintaining system performance within the forward error correction limit. Results demonstrate that a 9.51 Mb/s CE-OFDM system with 16-QAM subcarrier mapping in a 5MHz bandwidth outperformed a conventional OFDM system in terms of efficiency. The application of the CE-OFDM scheme in a 6m VLC link reduced the Error Vector Magnitude (EVM) from 17.5% to 10%, an improvement of approximately 43%. Additionally, the CEOFDM-
based VLC system demonstrated satisfactory performance in an 8 m link when using 4-QAM subcarrier mapping. The proposed handover scheme outperforms a power-based approach, achieving handover reductions of 42.47% in a Multiple Input Single Output (MISO) simulation environment and up to 48.61% in a Multiple Input Multiple Output (MIMO) environment. In experimental scenarios with three and four transmitters, the scheme achieved reductions of 46.43% and 45.45%, respectively. These results confirm that the integration of MGA with ML models effectively minimizes handovers and improves overall VLC system performance.
