Code On’s proprietary coding technology, Random Linear Network Coding (RLNC), enables the powerful, next-generation multicast features required for satellite, mobile 5G, connected cars, video streaming and much more.

Target Markets

RLNC provides not only considerable performance boosts, but also new ways of carrying out multicasting in the following markets:

  • Wireless Multicasting and Crowded WiFi
  • Broadcasting and Live Content Distribution
  • Content Distribution Networks (CDNs)
  • IPTV
  • Stadium Wireless Access
  • Software Defined Networking (SDN) and Network Function Virtualization (NFV)
  • Satellite Broadcasting 


In addition, RLNC-based solutions can act as substitutes for all current point-to-multipoint applications.


WiFi in Crowded Spaces - Crowded WiFi settings require architectures capable of managing an unprecedented volume of connections. Such architectures are designed to support new services and applications that are required at crowded WiFi venues, such as broadcast support in stadiums to access popular or live videos simultaneously. Our algorithm represents a technological leap in broadcasting and multicasting services, both in performance and management.

Satellite Broadcasting - Multicast solutions using RLNC can be applied in Satellite broadcasting, including maritime communications, mid-air (airplane) internet connectivity, remote location internet access, and others.

Satellite links are characterized by long round trip times (RTTs) and harsh channel conditions that are symptoms of very lossy connections. While packet losses depend on physical channel coding, packet and frame dimensioning, and flow rates, satellite link loss rates can reach 50% in extreme conditions.

Current solutions to counter the high and bursty packet losses are based on implementing multiple layers of redundancy, which can be inflexible and inefficient, especially in conditions where spectrum is very expensive.

Our technology offers new link implementations that optimize bandwidth usage by removing unnecessary redundancy. It is particularly effective in dynamic satellite conditions with fluctuating signal levels because of RLNC’s flexible and tuneable properties.

How It Works

As the number of receivers increases, managing feedback with individual receivers is not scalable, hence the advent of complex multicasting protocols such as NORM. Overall, exploiting RLNC enables significant reduction of feedback while enabling high-QoE broadcast solutions.

RLNC’s straightforward multicasting usage is as a simple erasure code: Coded packets are more efficient in retransmissions as a single coded packet can substitute for multiple missing packets at different receivers. Coding thus simplifies multicast protocols and provides tremendous bandwidth gains compared to non-coded alternatives. As a multicasting erasure code, RLNC is the only code that benefits from sliding window coding


In broadcast applications, RLNC is a superior technical alternative to both legacy block codes, and also advanced rateless codes. Recent implementations suggest that RLNC is more efficient than Raptor codes and leads to a better user experience.

RLNC’s recoding feature enables a second multicasting method that is unique among codes. By using RLNC, cooperating devices can generate their own redundancy via transmission of recoded combinations of their received packets to neighbouring nodes, thus offloading the broadcasting node. A recent LTE study shows that such a use of RLNC eliminates the need for most of the redundancy transmitted on the cellular link in a simulated eMBMS system.

Our partner Steinwurf has already developed a multicast reference design which is ready to use. For more information on RLNC Multicast products contact us. 

Performance Improvements


  • RLNC-based protocols multiply the throughput of NACK-based protocols in satellite multicast networks with a large number of receivers


  • RLNC multiplies energy-per-bit savings for mobile devices in WiFi networks
  • Energy-per-bit ratio for RLNC coding shrinks by orders of magnitude compared to WiFi transmissions