Key research themes
1. How do advanced modulation and coding techniques improve digital communication reliability and efficiency in challenging channels?
This research theme explores the development and evaluation of novel modulation and coding strategies, such as GFDM combined with CPM and channel coding schemes (BCH, Reed-Solomon, convolutional codes), to enhance bit error rates, spectral efficiency, and robustness over hostile communication channels including wireless multipath fading and underwater acoustic environments. The focus is on designing flexible, low-interference waveforms and integrating error correction to reliably transmit data under channel impairments, with implications for 5G, IoT, and underwater applications.
2. How is digital communication evolving beyond traditional identifiers such as phone numbers in the context of emerging technologies and privacy concerns?
This theme encapsulates research investigating the obsolescence of traditional communication identifiers like phone numbers in favor of digital identities facilitated by app-based platforms, biometrics, and decentralized technologies such as blockchain. The work emphasizes privacy, security, and user experience improvements with these new paradigms. It also addresses technological, regulatory, and societal challenges in transitioning to a new communication identification framework anticipated by 2030.
3. What roles do digital communication tools and social media play in shaping societal behavior, language, and reputation in contemporary settings?
This theme covers investigations into the sociolinguistic and organizational impacts of digital communication mediums, including emoji use among university students, crisis management via social media, and new professional identities like social media influencers. Research explores how digital tools influence language evolution, emotional expression, corporate reputation, and political activism, highlighting the transformative effects of digital communication on interpersonal relations, organizational behavior, and public discourse.
4. How can artificial intelligence and cognitive radio techniques optimize spectrum utilization and management in digital communication networks?
This theme examines the integration of AI methodologies within cognitive radio systems aimed at dynamic spectrum sensing, intelligent spectrum access, interference management, and energy-efficient operation. It emphasizes machine learning and reinforcement learning algorithms that enable real-time adaptation to changing radio environments, enhancing spectrum sharing, regulatory compliance, and reducing conflicts among unlicensed users in increasingly crowded networks.