Via Satellite archive photo (Shutterstock)

Satellite communications have become a lifeline for operations in remote, maritime, military, and industrial environments — the places where terrestrial networks simply don’t reach. But as reliance on these networks grows, so do the challenges that threaten their efficiency, reliability, and sustainability.

Three persistent constraints define the satellite communications landscape: limited bandwidth, high latency, and scarce compute resources. These aren’t new problems, but the way we address them must evolve if satellite connectivity is to keep pace with increasing demand. Let’s take a closer look at each.

Bandwidth is the most obvious and unforgiving constraint. In terrestrial networks, capacity is measured in abundance; in satellite systems, it’s a tightly rationed resource. Uplink bandwidth, in particular, comes at a premium. Every bit transmitted from a remote endpoint to a satellite must be justified. This forces difficult trade-offs between data fidelity, transmission frequency, and timeliness.

Traditional approaches to conserving bandwidth, such as data compression, can help, but they often introduce processing overhead, latency, or complexity that undermine their value, especially in real-time or near-real-time use cases. We can’t solve tomorrow’s bandwidth problem with yesterday’s compression tools. At most, these existing tools are a stop-gap.

Latency is another unavoidable feature of satellite communications. The vast physical distance between orbiting satellites and ground systems introduces inherent delays, compounded by multi-hop routing and protocol layers. In time-sensitive operations like disaster response, military missions, or predictive equipment monitoring, even small delays can create significant consequences.

To make matters worse, latency isn’t just a product of the network itself; it also arises from how we handle and prepare the data for transmission. Encryption, compression, packetization, etc. — each of these steps takes time and computational effort, and can add to the cumulative delay before a message even leaves the transmitter.

Security is non-negotiable in satellite communications. Whether protecting defense data or monitoring critical infrastructure, ensuring that transmissions are confidential and authentic is essential. But encryption, while effective, comes with costs: it consumes compute power, adds even more latency, and may not be feasible for constrained devices operating on limited power or processing capabilities.

This creates a tough question: how do we maintain security without compromising the timeliness and efficiency of data transmission? The answer may lie not in adding more protective layers, but in rethinking the structure of the data itself.

Smarter, Not Just Smaller: Rethinking Data

Solving the challenges of satellite communications requires a shift in thinking — from squeezing data after it’s generated to designing data that is inherently compact, efficient, and transmission-ready from the outset. The goal isn’t just to make data smaller, but to make it smarter. That means optimizing it for minimal bandwidth use, low latency, and compatibility with endpoints that may be low-power, intermittently connected, or operating in harsh environments.

This is where data compaction comes into play; a fundamentally different approach from traditional compression.

Data compaction involves restructuring data at the byte or even bit level to eliminate redundancy before it ever reaches the network stack. Unlike traditional compression algorithms, which prioritize file size and can introduce latency, compaction techniques are optimized for speed, predictability, and minimal overhead. They can significantly reduce the size of telemetry, sensor data, or control messages without burdening the endpoint or adding extra latency to the transmission.

Crucially, compaction does not require trade-offs in data fidelity. Because it’s a format transformation rather than an approximation, the original data can be perfectly reconstructed on the other end without error. That makes it especially attractive for applications where precision and integrity are non-negotiable, such as environmental monitoring, defense operations, or autonomous system control.

In addition, when paired with lightweight encryption techniques, compacted data can be transmitted securely without adding undue burden on already-limited endpoint resources. Smaller payloads mean less data to encrypt and decrypt, which speeds up processing and reduces latency even further.

Compaction transforms the economics of satellite communications. It allows systems to transmit more insight using fewer bits without sacrificing speed, power, or precision. For organizations looking to extend the reach and responsiveness of their networks, this smarter, more adaptive approach to data isn’t just an optimization. It’s a necessity.

By compacting data in a way that’s tailored to the specific needs of satellite networks, rather than applying generic compression, satellite operators can enable real-time communication that’s both efficient and secure.

As satellite systems take on a greater role in global communications by supporting IoT networks, autonomous systems, remote maintenance, and emergency responses, the need for fast, efficient, and secure communications in bandwidth-constrained environments will only intensify. The ability to transmit more information with fewer resources will become a defining advantage.

To do this successfully, the industry must continue to innovate not only in satellite hardware and architecture, but also in the unseen foundation of all communications: the data itself. By adopting a smarter approach to data transmission, satellite operators can expand the reach, resilience, and responsiveness of their networks without needing to increase capacity.

Charles Yeomans is the co-founder and CEO of Atombeam. With 25+ years in executive roles and investment banking, Charles has led multiple firms and founded successful companies, including major insurance brokerages. He’s a former U.S. Navy intelligence officer with an AB from Kenyon and an MBA from Stanford.