Before a cell tower is installed or an autonomous vehicle begins operating in a city, engineers need to understand how the underlying waves behave in that specific setting. For decades, wireless propagation modeling has provided a way to model and predict that by turning the physical world into predictive data.
But the models traditionally used were developed for an earlier era — simpler networks, broader performance tolerances, and far fewer connected devices. Modern sensing platforms require much greater precision, often down to the millimeter, along with the ability to account for constantly changing surroundings.
Addressing this gap is researcher Anuraag Bodi. His approach starts not with statistical probabilities, but with the physical laws that govern signal behavior. One of his key developments is a ray tracer that can simulate how radio waves reflect, scatter, and diffract in complex three-dimensional spaces, from concrete high-rises to dense tree canopies.
The result is a simulation method that captures the fine details of urban, industrial, and safety-critical environments with a level of accuracy uncommon in the field.
His Work Building Advanced Wireless Models
Anuraag Bodi’s approach to wireless modeling is built on an interdisciplinary background in electrical engineering and computer science. Early in his academic work, he specialized in wireless channel modeling and network optimization — an interest that evolved into a position for a large technology research company, where he focuses on connecting advanced theory with practical engineering solutions.
He specifically zeroes in on how, as wireless technology has advanced, predicting how signals behave in real-world settings has become more complex. Expanding cities, taller buildings, and denser infrastructure create more surfaces for signals to reflect from or be blocked by. Natural elements like foliage add further interference, while the presence of multiple existing wireless systems introduces additional variables.
These factors make accurate modeling especially challenging for advanced networks, like 5G and 6G, that demand a more thorough mapping of their surroundings.
To address these challenges, Bodi has worked to develop tools that can more accurately capture the physical conditions in which wireless systems operate. One example is the Context-Aware Channel Sounder, which links raw wireless measurement data to the specific physical objects causing reflections or scattering. By connecting this information to real-world sources, the system enables more precise insight into signal paths than generalized averages.
A Modern Ray Tracer Engine
One of Bodi’s major projects in this lane has been the development of a custom ray tracer. A technique originally used in computer graphics to simulate how light interacts with a 3D scene, Bodi realized that this could be adapted for wireless engineering to calculate how radio waves behave in complex environments.
This tool addresses the lack of flexibility that most commercial wireless tracking tools have when it comes to handling non-standard scenarios or incorporating new types of environmental data. They also struggle to accurately calculate how smaller-scale effects, such as subtle diffraction patterns or multi-path interference, can have a larger impact on signal strength.
Bodi’s ray tracer aims to solve these issues by modeling how signals reflect off buildings, scatter from different types of objects, and lose strength when they reflect from harder materials like concrete. It can simulate entire wireless networks with location-specific accuracy, integrate real-world measurement data, and evaluate the performance of different antenna arrays.
A key capability is its assessment of beamforming — the process of focusing a wireless signal toward a specific receiver rather than sending it in all directions, which improves signal quality and reduces interference. This method, while technically sound, currently proves difficult to implement, as selecting the optimal beam pattern for each device involves heavy computational power and algorithmic capabilities that many systems lack.
The ray tracer solves this by analyzing how network resources are distributed and detecting patterns that minimize interference. It can also model how beams from multiple devices interact, an important factor in networks with high demand or with large physical infrastructure.
When paired with network simulators such as NS-3, the system can then act as a controlled environment for testing protocols like beamforming before installing larger wireless systems into real-world locations, shortening development cycles, lowering expenses in field trials, and increasing confidence in network performance before rollout.
Mapping Out Environments With Greater Precision
The impact of Bodi’s work goes beyond research, as it can influence the ongoing construction of technical standards for upcoming technologies such as 6G and integrated sensing and communications. These standards determine how spectrum is assigned, how networks are built, and what performance targets they must meet.
His models are designed to reflect real-world conditions, accounting for the physical and environmental factors that affect wireless signals. This gives wireless companies better data for investments, infrastructure planning, and the design of broader architectural decisions that can adapt to the unique requirements of increasingly connected cities and fields, ensuring that next-generation networks not only maintain high-quality standards but are also more reliable and efficient in how they use available resources.
Through projects like the custom ray tracer, Anuraag Bodi is contributing to the technical progress of wireless systems and the strategic choices that will guide their rollout. His work is helping define how future networks will sense, interpret, and react to the environments in which they operate.
