Smarter beams promise faster and more reliable 5G 

The technology powering today’s 5G networks isn’t just faster, it’s smarter. At the heart of it is a technique called multiple input multiple output (MIMO), which uses multi-antennas to send and receive signals. By coordinating the antenna elements at the base station (and sometimes at the user device), engineers can precision steer energy in specific directions, a technique known as beamforming.  

The technique increases the received signal quality and can reduce interference. This kind of spatial processing, together with the wider bandwidths used in 5G, is behind the continuing improvements in the coverage, spectral efficiency and capacity of wireless communications. 

But packing many antennas close together introduces new challenges. When multiple elements transmit at once, their electromagnetic fields collide, a phenomenon called mutual coupling. This results in the distortion of intended signal paths, limiting how precisely network performance can be analyzed and optimized. 

“Our model [can] help engineers design smarter beamforming and focusing strategies for next-generation systems, improving both signal strength and energy efficiency.” 

Sami Muhaidat 

Researchers at Khalifa University have proposed more realistic models for wireless networks to account for these electromagnetic effects. By combining detailed analyses of wave propagation with practical multi-antenna configurations, they are establishing a more solid physical foundation for evaluating and improving today’s advanced wireless systems. This can support the design of more effective beamforming and MIMO algorithms, enabling faster and more reliable data transfer. 

“Our model can be applied to many areas in wireless communications,” says Sami Muhaidat from the College of Computing and Mathematical Sciences. “This helps engineers design smarter beamforming and focusing strategies for next-generation systems, improving both signal strength and energy efficiency.” 

The model is among the first to incorporate a “unified and physically consistent view of wireless channels,” he says. “It provides both theoretical insight and practical guidance for real-world system design.”  

With colleagues from around the world, the KU team is working to improve the model further. The goal is to simulate with greater accuracy how signals from closely spaced antennas interact. This often leads to uneven energy distribution across the antennas, which can reduce efficiency and create unwanted side beams in signal transmission. Capturing these effects more precisely will make the model directly applicable to practical scenarios such as signal optimization, interference control and secure communication design. 

KU is an ideal place to work on such challenges, Muhaidat says. “The university combines world-class expertise in wireless and electromagnetic technologies with a very collaborative atmosphere. It’s a place where ideas move easily from theory to practice, exactly what we need to push forward electromagnetic-compliant modelling and future communication systems.” 

Reference

L. Wei et al., “Electromagnetic Channel Modeling and Capacity Analysis for HMIMO Communications,”  IEEE Transactions on Wireless Communications 24, no. 5, pp. 4500-4514.