Kun Woo Cho will present her FPO "Programmable Smart Radio Environments: From Theory to Hardware Implementation" on October 1, 2024 at 3pm in Friend Center 004

Examiner: Prof. Kyle Jamieson (Advisor, CS), Prof. Yasaman Ghasempour (ECE), Prof. Andrew Appel (CS)

Reader: Prof. Wyatt Lloyd (CS), Prof. Omid Abari (UCLA), Dr. Ranveer Chandra (MSR)

All are welcome to attend.

Title:

Programmable Smart Radio Environments: From Theory to Hardware Implementation

Abstract:

Today’s wireless networks are undergoing a rapid transformation, scaling in traffic vol-

ume, spectral efficiency, and radio count as never seen before. This thesis addresses

the critical challenges emerging from this evolution in next-generation (NextG) wire-

less networks, focusing on realizing three key services: enhanced mobile broadband

(Gbps or above), ultra-reliable low latency communication (order of milliseconds),

and massive machine type communication (up to one million per squared kilometer).

To meet these diverse and demanding requirements, this thesis poses a central

question: Can we build a smarter radio environment controlled and learned by soft-

ware, configuring itself in real-time to meet different application needs? Current

approaches to handle uncontrolled wireless signals are end-to-end. Unfortunately,

sending and receiving endpoints are limited in their ability to shape this inherent

propagation behavior. For instance, although multiple antennas can shape the beam

pattern departing the sender, it cannot control how the resulting signals arrive at the

receiver after traversing environmental obstacles. By focusing on changing the envi-

ronment itself rather than the communication endpoints, this thesis offers a significant

shift in design paradigms for modern wireless networks.

First, millimeter-wave (mmWave) technology offers multi-Gbps data rates due

to its wide spectral bands. However, the high frequency of mmWave signals makes

them vulnerable to blockage by walls, people, and obstacles, significantly limiting

their practical applications. This thesis introduces mmWall, a programmable smart

surface deployed on buildings to fully control the mmWave radio environment. Com-

prising over 4,000 sub-millimeter meta-materials, mmWall can steer signals through

the surface or reflect them, bringing outdoor mmWave signals indoors and bypassing

obstacles. Also, this thesis proposes Wall-Street, a smart surface installed on vehicles

to provide seamless and reliable mmWave connectivity in high-mobility scenarios.

Second, satellite networks uses constellations of thousands of satellites to provide

low latency communication and global coverage. However, these networks face two

significant challenges: outages due to transient blockage, and complications in beam

alignment between users and satellites due to the use of different frequency sub-bands

in the uplink and downlink directions. Extending the concept of a programmable

smart radio to satellite communications, this thesis introduces Wall-E, a dual-band

smart surface that mitigates signal blockage and enhances reliability of satellite-to-

ground links, and Monolith, a smart surface that boosts inter-satellite link capacity.

Third, while these smart surfaces address challenges at the physical layer, we

also tackle issues at the link/MAC layer, particularly in massive Internet of Things

(IoT) networks. This thesis introduces Cross-Link Channel Prediction (CLCP), a ma-

chine learning technique that learns the radio environment and accordingly allocates

networking resources to a large number of IoT devices. This AI-driven approach com-

plements my programmable surfaces, creating a comprehensive smart radio solution

for NextG networks.