Operation of Cellular Networks Found Similar to Bacteria Growth in Petri Dish
Scientists at HSE University have discovered an approach to analysing mobile communication quality by applying the principles of surface physics
Scientists at the HSE Laboratory for Computational Physics have developed a new model for analysing communication networks that can significantly enhance the speed of mobile communications. To achieve this, the researchers used computational physics methods and phase transition models. It turns out that the functioning of cellular networks is in many ways similar to the growth of surfaces in physics. The study was performed using the HPC cHARISMa cluster at HSE University. The study findings have been published in Frontiers in Physics.
Mobile networks enable making calls, sending messages, and using the internet. However, for these networks to function smoothly, it is essential to be able to simulate their operation. Simulations help predict how a network will behave in various situations, including extreme conditions, and identify areas for improvement.
One of the key tools for studying mobile networks is parallel discrete-event simulation (PDES). This method is based on splitting a system into numerous subsystems to enable parallel modelling of various processes. Each of these subsystems has its own local virtual time, which does not align with the actual time. When the local times significantly diverge from each other, leading to process desynchronisation, the network may experience slower operation or errors. Lev Shchur and Liliia Zhukova, scientists at HSE MIEM, studied the evolution of local virtual time profiles in a cellular communication model and discovered similarities with the surface growth processes in physics.
Associate Professor, School of Applied Mathematics, HSE Tikhonov Moscow Institute of Electronics and Mathematics
After conducting a thorough analysis of the processes, we observed similarities between changes in local time in cellular communication modelling and alterations in a surface profile as it grows, eg through spray application, as the time only progresses forward. Surface physics is a well-established field with equations that facilitate analysis and modelling of various processes. We have transferred knowledge from this domain to computing technologies and constructed a model simulating the evolution of local virtual time profiles.
By comparing their findings with a model of a real mobile network, the scientists have found that the proposed method enables accurate prediction of critical moments when the network's performance may deteriorate, so that issues can be addressed proactively, leading to improved network operation.
Head, Laboratory for Computational Physics, HSE Tikhonov Moscow Institute of Electronics and Mathematics
With the help of computational physics algorithms, it becomes possible to determine the moment when local time ceases to progress, referred to in physics as the phase transition point. We can describe the events occurring around it and anticipate potential communication disruptions or alterations in load distribution at a cellular communication station. With this model, we can provide the industry with better tools for planning, constructing, and operating mobile networks.
The researchers emphasise that understanding the mechanics of parallel computing in actual high-load networks will facilitate faster and more efficient simulation of mobile networks and other systems employing similar calculations across various domains such as engineering, computer science, economics, and transportation.
See also:
Narcissistic and Workaholic Leaders Guide Young Firms to Success
Scientists at HSE University—St. Petersburg studied how the founder's personal characteristics impact a young firm's performance. It turns out that a narcissist and workaholic who also fosters innovation will effectively grow their company. The paper has been published in IEEE Transactions on Engineering Management.
Biologists at HSE University Warn of Potential Errors in MicroRNA Overexpression Method
Researchers at HSE University and the RAS Institute of Bioorganic Chemistry have discovered that a common method of studying genes, which relies on the overexpression of microRNAs, can produce inaccurate results. This method is widely used in the study of various pathologies, in particular cancers. Errors in experiments can lead to incorrect conclusions, affecting the diagnosis and treatment of the disease. The study findings have been published in BBA.
Green Energy Patents Boost Company Profitability
An ESG strategy—Environmental, Social, and Corporate Governance—not only helps preserve the environment but can also generate tangible income. Thus, the use of renewable energy sources (RES) and green technologies in the energy sector enhances return on investment and profitability. In contrast, higher CO2 emissions result in lower financial performance. This has been demonstrated in a collaborative study by the HSE Faculty of Economic Sciences and the European University at St. Petersburg. Their findings have been published in Frontiers in Environmental Science.
Neuroscientists from HSE University Learn to Predict Human Behaviour by Their Facial Expressions
Researchers at the Institute for Cognitive Neuroscience at HSE University are using automatic emotion recognition technologies to study charitable behaviour. In an experiment, scientists presented 45 participants with photographs of dogs in need and invited them to make donations to support these animals. Emotional reactions to the images were determined through facial activity using the FaceReader program. It turned out that the stronger the participants felt sadness and anger, the more money they were willing to donate to charity funds, regardless of their personal financial well-being. The study was published in the journal Heliyon.
Physicists from Russia and Brazil Unveil Mystery behind Complex Superconductor Patterns
Scientists at HSE MIEM and MIPT have demonstrated that highly complex spatial structures, similar to the intricate patterns found in nature, can emerge in superconductors. Mathematically, these patterns are described using the Ginzburg–Landau equation at a specific combination of parameters known as the Bogomolny point. The paper has been published in the Journal of Physics: Condensed Matter.
Adhesive Tape Helps Create Innovative THz Photodetector
An international team of researchers, including scientists at HSE University and Moscow Pedagogical State University (MPGU), has developed a novel photodetector composed of a thin superconducting film, capable of detecting weak terahertz (THz) radiation. This discovery holds promise for studying objects in space, developing wireless broadband communication systems, and making advancements in spectroscopy. The study has been published in Nano Letters.
The Saudi Arabian National Team, Medal Winners at the International Physics Olympiad, Trained at HSE University
At the recent International Physics Olympiad (IPhO 2024) in Iran, students from Saudi Arabia achieved the best results in their country's history, winning one silver and three bronze medals. The team from the Kingdom made their first visit to Russia to receive their final training at the HSE Faculty of Physics.
Spelling Sensitivity in Russian Speakers Develops by Early Adolescence
Scientists at the RAS Institute of Higher Nervous Activity and Neurophysiology and HSE University have uncovered how the foundations of literacy develop in the brain. To achieve this, they compared error recognition processes across three age groups: children aged 8 to 10, early adolescents aged 11 to 14, and adults. The experiment revealed that a child's sensitivity to spelling errors first emerges in primary school and continues to develop well into the teenage years, at least until age 14. Before that age, children are less adept at recognising misspelled words compared to older teenagers and adults. The study findings have beenpublished in Scientific Reports .
HSE Researchers Demonstrate Effectiveness of Machine Learning in Forecasting Inflation
Inflation is a key indicator of economic stability, and being able to accurately forecast its levels across regions is crucial for governments, businesses, and households. Tatiana Bukina and Dmitry Kashin at HSE Campus in Perm have found that machine learning techniques outperform traditional econometric models in long-term inflation forecasting. The results of the study focused on several regions in the Privolzhskiy Federal District have been published in HSE Economic Journal.
Ruthenium Complexes Can Accelerate the Development of New Medicines
A group of scientists at INEOS RAS, HSE University, and MIPT have synthesised catalysts containing a ruthenium atom and an aromatic ring. The scientists have isolated the mirror forms of these catalysts and investigated their effectiveness in producing heterocycles, which are commonly found in the structures of drugs. The research findings have been published in Chemical Communications.