Signal Processing and Machine Learning (SPML) Laboratory at Istinye University offers expertise on:
Beyond-5G and 6G Physical Layer Design
Advanced waveform, modulation, and signal processing techniques for future smart networks, emphasizing scalability, robustness, and hardware-aware designs.
AI-Assisted and AI-Native 6G Systems
Machine learning–enabled physical-layer and cross-layer solutions for 6G, including AI-driven channel estimation, beamforming, beam management, and adaptive transceiver design. Focus on model-based, data-driven, and hybrid learning approaches ensuring interpretability, generalization, and low complexity.
Advanced Multi-Antenna Systems (Massive MIMO & XL-MIMO)
Hybrid architectures, near-field channel modeling, and signal processing for extremely large antenna arrays across sub-6 GHz, mmWave, and THz frequencies.
Millimeter-Wave and Terahertz Communications
Channel estimation, mobility-aware beam tracking, and low-complexity transceiver algorithms addressing propagation and hardware challenges at high frequencies.
Integrated Sensing and Communications (ISAC)
Joint waveform, beamforming, and resource optimization enabling unified sensing and communication for vehicular, industrial, and smart environment applications.
Intelligent Reflecting Surfaces (RIS) and Programmable Radio Environments
RIS-assisted channel modeling, passive and hybrid beamforming, and AI-aided optimization for energy-efficient and reconfigurable networks.
Index Modulation Techniques
Spatial and media-based index modulation schemes improving spectral and energy efficiency in MIMO and RIS-assisted systems.
Simultaneous Wireless Information and Power Transfer (SWIPT)
Joint information-energy transmission and learning-based optimization for sustainable and low-power 6G devices.
Energy-Efficient and Sustainable Network Design
Low-complexity, AI-enabled physical-layer solutions supporting green, intelligent, and scalable 6G networks.