Neural Networks Go On Air: MIET Students Build Smarter, More Reliable Communications

Why LDPC and Neural Networks Matter for the Future of Connectivity

Low-Density Parity-Check (LDPC) codes form the backbone of modern data transmission standards, including 5G and the forthcoming 6G networks.

They protect information from noise and signal interference but traditionally demand extensive computational power. The MIET team’s hybrid approach fuses the classical structure of LDPC coding with adaptive machine learning. The neural network dynamically tunes the decoder’s parameters to channel conditions, enhancing accuracy without increasing processor load.

This balance between precision and efficiency opens the door to smarter, faster, and more sustainable communications—both in base stations and in consumer devices. The project received up to 400,000 rubles in funding under Russia’s Young Researcher competition.

From Concept to Lab Bench: Building an Innovation Ecosystem

The LDPC decoder project reflects MIET’s broader telecom innovation ecosystem. In 2023, the university’s Department of Telecommunication Systems launched the Mobile Communications Laboratory, a hub equipped with modern test benches and connected to industry partners. Programs like Priority 2030 and Young Researcher provide sustainable funding and cross-disciplinary collaboration, allowing ideas to move quickly from theory to working prototypes.

“Our goal is to design an LDPC decoding algorithm that combines two crucial strengths—near-optimal decoding accuracy with the computational simplicity of low-complexity methods. By merging neural network techniques with a modified Min-Sum approach, our hybrid solution already shows reduced bit error rates compared to traditional algorithms at comparable computational cost. This makes it highly promising for real-world applications in next-generation communication systems, where bandwidth and reliability are equally critical. In the future, this solution could be integrated into 5G NR standards and adapted for diverse scenarios—from low-power IoT devices to high-load base stations.”

Mikhail Zvyagin

a second-year master’s student at the Department of Telecommunication Systems and a 2025 Young Researcher competition winner

Over the next 6 to 18 months, the MIET team plans to evaluate performance metrics—bit error rate (BER), latency, and power consumption—before presenting results to leading telecom conferences. If validated, the algorithm could advance to FPGA or ASIC implementation, integrating into receiver front-ends.

This is not merely an academic exercise but a potential step toward deployable communications hardware. Notably, MIET previously built Russia’s first 5G prototype base station, accelerating industrial adoption of advanced telecom technologies.

Russia’s Research Footprint in the Global Telecom Race

Research into neural LDPC decoding has surged worldwide, with papers regularly appearing in IEEE journals and major conferences. MIET’s work stands out for bridging fundamental science and applied engineering.

If successful, the algorithm could enter international publications or technology transfer initiatives, positioning Russia as a credible contributor to the evolution of digital communications.

The project also underlines a broader principle: innovation does not only emerge from corporate R&D centers but thrives in university labs—where infrastructure, mentorship, and young talent intersect. MIET exemplifies this model, acting as a nucleus for technological sovereignty and next-generation expertise in Russia’s scientific landscape.