Smart Electromagnetic Cities 🌆🌐

TL;DR

This study proposes a planning strategy that combines electromagnetic skins, smart repeaters, and IAB nodes to build smart electromagnetic environments, cutting urban wireless blind spots by ~90% while balancing cost and energy efficiency.

Breaking it down

Why Our Cities Need Smart EM Environments 🌐⚡

Imagine walking through a busy city street while streaming ultra-HD video, joining a VR meeting, or even operating a drone delivery system 🚁. For all these futuristic services, we need wireless networks that never fail, no matter the obstacles—buildings, cars, trees, or even rain.

But today’s networks still suffer from dead zones (places where your phone signal drops), shadowing (signals blocked by buildings), and interference. The traditional fix? Just add more base stations and crank up the power 💡📡. But that approach is expensive, energy-hungry, and creates more electromagnetic noise.

Here’s where the idea of a Smart Electromagnetic Environment (SEME) comes in. Instead of treating the environment as a problem, we turn it into a solution—by embedding smart electromagnetic entities (SEEs) into walls, poles, and surfaces around us.

The research we’re exploring today presents a planning strategy to make this futuristic vision real. Let’s unpack how it works, what they found, and what’s next.

What Are Smart Electromagnetic Entities (SEEs)? 🤔

Before diving into the planning, let’s get to know the main actors of this story:

1. Electromagnetic Skins (EMSs) 🖼️

• Think of them like smart wallpapers for buildings.
• They can reflect, redirect, or shape wireless signals.
• Two flavors:
  • Static Passive EMSs (SP-EMSs): Cheap, simple, need no power.
  • Reconfigurable Passive EMSs (RP-EMSs): More advanced, can change behavior on demand (using diodes, liquid crystals, etc.).

2. Smart Repeaters (SRs) 🔄📡

• Upgrade of old-school repeaters.
• They amplify and redirect signals intelligently.
• Useful for covering tricky corners of cities.

3. Integrated Access and Backhaul Nodes (IABs) 🏗️

• Like mini base stations without the fiber cable.
• They connect wirelessly to the main network and then distribute signals locally.
• Perfect for rapid deployment in dense city areas.

Together, these entities can fill blind spots, improve quality of service (QoS), and make networks more efficient. But the big challenge is: where and how do we place them? That’s where this research shines.

The Planning Problem 📍🧩

Imagine you’re tasked with making a city like Trento (Italy) 100% connected. You have:

• A set of candidate spots (like building walls or poles) where SEEs could be installed.
• Different types of SEEs, each with their cost 💰, power consumption ⚡, and signal properties 📶.
• A map of blind spots where the base station struggles to reach.

The goal: Find the best mix of SEEs and their positions to maximize coverage while keeping costs and energy low.

This is not just guesswork. The researchers turned it into a mathematical optimization problem—balancing three conflicting objectives:

1. Coverage improvement (no blind spots!).
2. Cost minimization (don’t blow the budget).
3. Energy efficiency (keep networks green 🌱).

To solve this, they used a multi-objective genetic algorithm (NSGA-II) 🧬. In simple terms, it’s like digital evolution—trying many deployment strategies, keeping the best, and gradually improving until you get a set of “Pareto-optimal” solutions.

Testing in Real Cities 🏙️

To see if this strategy actually works, the team tested it in two real-world scenarios in Trento, Italy:

1. Industrial Zone (Trento Nord) 🏭
   • Wide streets, medium-sized buildings, some parks.
   • Lots of obstacles causing shadowing.
   • Several “blind spots” identified.
2. Residential Area (San Martino District) 🏘️
   • Denser buildings, narrower streets.
   • Even trickier for signals to pass.

They simulated wireless coverage at 3.5 GHz (5G band) using advanced tools (WinProp, HFSS) and then applied their planning strategy.

What They Found 🔍📊

Here are the key takeaways from the simulations and optimizations:

1. Coverage Can Improve Dramatically 📶✨

In both scenarios, blind spots were reduced by up to ~90% with smart deployment of SEEs.
Example: In Trento Nord, blind-spot areas shrank by ~86–89% after optimal placement of EMSs, SRs, and IABs.

2. Trade-Offs Matter ⚖️

• The best coverage-only solution (maximizing signal everywhere) required multiple active devices (IABs + SRs).
• But this came with high cost and high power consumption.
• On the other hand, the best balanced solution used a mix:
  • Mostly cheap SP-EMSs,
  • A few RP-EMSs,
  • And a handful of SRs.
• This combo achieved strong coverage improvements without breaking the bank.

3. Active vs Passive Balance 🧮

• Active devices (SRs, IABs) gave huge improvements but consumed energy.
• Passive devices (EMSs) were cheaper, eco-friendly, and surprisingly effective in many cases.
• The sweet spot? Hybrid deployments combining both.

4. Smarter Planning Beats Just Boosting Power 🔋🚫

• Without SEEs, the only way to match the coverage was to increase base station power by 500%+.
• That’s totally inefficient and unsustainable.
• With smart EM planning, you get better results at a fraction of the energy cost.

Why This Matters 🌍📡

This research isn’t just theory. It shows a realistic path for making 5G and future 6G networks:

• Cheaper to deploy (fewer big towers, more clever surfaces).
• Greener (lower energy use).
• More reliable (bye-bye, dead zones).
• Flexible (easy to adapt as cities grow).

It could also empower metaverse applications, telemedicine, AR/VR, autonomous cars, and drones—all of which need seamless, ultra-reliable wireless connectivity.

Future Prospects 🔭

The authors see exciting directions for the future:

1. Indoor Applications 🏢
   • Think shopping malls, airports, or hospitals.
   • Smart EM skins could solve indoor dead zones where normal base stations struggle.
2. Wi-Fi Integration 📶 Not just for mobile networks—Wi-Fi routers could also benefit from these strategies.
3. Multi-Hop Smart Networks 🔗 SEEs could talk to each other, creating mesh-like electromagnetic highways for signals.
4. AI-Driven Planning 🤖 Instead of manual planning, AI could learn to continuously optimize SEE placement as cities evolve.
5. Sustainability 🌱 More focus on energy harvesting and low-power designs to make networks eco-friendly.

Building Smarter, Greener Cities 🌆💡

This study is a milestone in turning cities into smart electromagnetic environments. By carefully planning the mix of electromagnetic skins, smart repeaters, and IAB nodes, they showed that we can:

• Cut blind spots by almost 90% 🟢
• Reduce costs compared to traditional fixes 💸
• Save massive amounts of energy ⚡

Instead of endlessly adding bigger, costlier towers, this approach transforms the urban environment itself into part of the network.

As we step into the 6G era and beyond, strategies like this will be crucial to support the connected world—from the metaverse to autonomous vehicles. The future isn’t just about faster base stations—it’s about smarter cities that talk back to our devices.

Terms to Know

Electromagnetic (EM) Waves 🌊📡 Invisible waves that carry wireless signals (like Wi-Fi, 5G, or radio). - More about this concept in the article "Innovative Insights into Fibrous Media: Revolutionizing Permittivity Estimation ⚡️ 🕸️".

Smart Electromagnetic Environment (SEME) 🏙️⚡ A city or space where walls, poles, and surfaces are “smart” and help wireless signals travel better instead of blocking them.

Smart Electromagnetic Entities (SEEs) 🧩 The building blocks of a SEME. They include devices like smart skins, repeaters, and mini base stations that improve signal coverage.

Electromagnetic Skins (EMSs) 🖼️ Thin panels (like smart wallpapers) that reflect or redirect wireless signals. - More about this concept in the article "Smart Skins for the Future: Frequency-Selective Surfaces Revolutionizing Buildings 🏠⚙️" - Two types:

• SP-EMS (Static Passive): Cheap, fixed behavior, no power needed.
• RP-EMS (Reconfigurable Passive): Can adapt signal direction in real time.

Smart Repeaters (SRs) 🔄 Devices that grab a weak wireless signal, boost it, and send it back out to cover hidden areas.

Integrated Access and Backhaul Nodes (IABs) 🏗️ Mini base stations that connect wirelessly to the main tower (no fiber cables needed) and then serve local users.

Blind Spots 🚫📶 Areas where your device can’t connect well because the signal is blocked by buildings or other obstacles.

Quality of Service (QoS) 📊 A measure of how good the network feels for users—fast, reliable, and with no annoying drops.

Multi-Objective Optimization (MOP) ⚖️ A smart planning method that tries to balance multiple goals at once (like best coverage, lowest cost, and lowest energy use). - More about this concept in the article "AUV Solar Optimization 🌊 The Next Wave in Marine Robotics".

Pareto-Optimal Solutions 🎯 The “sweet spot” solutions where you can’t improve one thing (like coverage) without making another worse (like cost or energy). - More about this concept in the article "Harnessing Nature: How Harris Hawks Optimization Is Revolutionizing Power Grids 🦅 ⚡".

Source: Arianna Benoni, Marco Salucci, Baozhu Li, Andrea Massa. A Planning Strategy for Building a Heterogeneous Smart EM Environment. https://doi.org/10.48550/arXiv.2509.08378

From: IEEE; University of Trento; Xidian University; ELEDIA Research Center.