[{"data":1,"prerenderedAt":105},["ShallowReactive",2],{"SoNgTRjN0XmxfGM7hTYM9pPYfzYh_iQKyCbbV_i3mQ0":3,"_apollo:default":103,"_apollo:identified":104},{"seo":4,"posts":15},{"social":5,"openGraph":11,"__typename":14},{"twitter":6,"__typename":10},{"cardType":7,"username":8,"__typename":9},"summary_large_image","dassault3ds","SEOSocialTwitter","SEOSocial",{"defaultImage":12,"__typename":13},null,"SEOOpenGraph","SEOConfig",{"nodes":16,"__typename":102},[17],{"id":18,"slug":19,"title":20,"uri":21,"excerpt":22,"locale":23,"featuredImage":26,"tableOfContents":34,"content":35,"date":36,"translations":37,"author":38,"tags":51,"globalTags":65,"brands":73,"keywords":84,"seo":90,"__typename":101},"cG9zdDozMDI3MjY=","reconfigurable-intelligent-surfaces-future-satellite-communication","Reconfigurable Intelligent Surfaces and the Future of Satellite Communication","/brands/simulia/reconfigurable-intelligent-surfaces-future-satellite-communication","\u003Cp>Reconfigurable intelligent surfaces, or RIS, sit at one of the most interesting intersections in modern wireless engineering. They draw on metamaterials, electromagnetic (EM) design, signal processing and high-performance computing, all in service of a deceptively simple idea. You can take a flat, low-power panel and make it behave like a steerable antenna. That promise is what makes RIS so relevant to satellite communication. Low-Earth Orbit (LEO) constellations are now real, ground terminals are being asked to do more in smaller packages, and 6G is starting to take shape on the horizon. RIS is moving from research papers into practical antenna systems and simulation is the bridge that gets it there. To explore where the technology stands today, Jonathan Oakley, Director of High-Tech Industry Enablement at Dassault Systèmes, sat down with Rodrigo Enjiu, Global High-Tech Industry Senior Specialist at Dassault Systèmes, to talk through the physics, the simulation workflow, and what comes next.\u003C/p>\n",{"locale":24,"__typename":25},"en_US","Locale",{"node":27,"__typename":33},{"large":28,"__typename":29,"medium_large":28,"thumbnail":30,"srcSet":31,"sizes":32},"https://blog-assets.3ds.com/uploads/2026/05/adobestock_1779786704_50-768x513.jpeg","MediaItem","https://blog-assets.3ds.com/uploads/2026/05/adobestock_1779786704_50-150x150.jpeg","https://blog-assets.3ds.com/uploads/2026/05/adobestock_1779786704_50-300x200.jpeg 300w, https://blog-assets.3ds.com/uploads/2026/05/adobestock_1779786704_50-1024x684.jpeg 1024w, https://blog-assets.3ds.com/uploads/2026/05/adobestock_1779786704_50-768x513.jpeg 768w, https://blog-assets.3ds.com/uploads/2026/05/adobestock_1779786704_50-1536x1026.jpeg 1536w, https://blog-assets.3ds.com/uploads/2026/05/adobestock_1779786704_50-2048x1368.jpeg 2048w","(max-width: 300px) 100vw, 300px","NodeWithFeaturedImageToMediaItemConnectionEdge",[],"\n\u003Ch3 class=\"wp-block-heading\" id=\"h-setting-the-scene-what-is-a-reconfigurable-intelligent-surface\">\u003Cstrong>Setting The Scene: What is a Reconfigurable Intelligent Surface?\u003C/strong>\u003C/h3>\n\n\n\n\u003Cp>\u003Cstrong>Jonathan:\u003C/strong> RIS is getting a lot of attention right now, but the term means different things to different people. How would you describe what a reconfigurable intelligent surface actually is, in the context of satellite communications, and why is the industry paying attention to it now?\u003C/p>\n\n\n\n\u003Cp>\u003Cstrong>Rodrigo:\u003C/strong> A reconfigurable intelligent surface is a type of metasurface, a kind of metamaterial. The defining feature is that we can engineer its behavior, and we can actively control how it interacts with an incoming electromagnetic wave.\u003C/p>\n\n\n\n\u003Cp>The reason the industry is paying attention right now is that we finally have the manufacturing technology to build these panels at scale. It is now becoming viable to use them in real applications, for instance in a ground terminal for satellite communication.\u003C/p>\n\n\n\n\u003Cfigure class=\"wp-block-image size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"975\" height=\"585\" src=\"https://blog-assets.3ds.com/uploads/2026/05/image-91.png\" alt=\"\" class=\"wp-image-302842\" srcset=\"https://blog-assets.3ds.com/uploads/2026/05/image-91.png 975w, https://blog-assets.3ds.com/uploads/2026/05/image-91-300x180.png 300w, https://blog-assets.3ds.com/uploads/2026/05/image-91-768x461.png 768w\" sizes=\"auto, (max-width: 975px) 100vw, 975px\" />\u003Cfigcaption class=\"wp-element-caption\">\u003Cstrong>Beams radiating from RIS.\u003C/strong>\u003C/figcaption>\u003C/figure>\n\n\n\n\u003Cp>\u003C/p>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"h-the-satcom-problem-ris-solves\">\u003Cstrong>The SATCOM Problem RIS Solves\u003C/strong>\u003C/h3>\n\n\n\n\u003Cp>\u003Cstrong>Jonathan:\u003C/strong> What are the signal propagation or coverage challenges in modern SATCOM (Satellite Communications) systems, particularly for LEO constellations or ground terminals, that make RIS a genuinely useful technology rather than an academic curiosity?\u003C/p>\n\n\n\n\u003Cp>\u003Cstrong>Rodrigo:\u003C/strong> If you want to control where an antenna radiates, you traditionally have two strategies.\u003C/p>\n\n\n\n\u003Cp>The first is a large reflector system on a mechanical gimbal. You physically rotate the dish to steer the beam. Because you have one reflector tilting toward the direction you want, you are limited to a single beam.\u003C/p>\n\n\n\n\u003Cp>The second strategy is a phased array. You sample the aperture with smaller radiators, each with its own transmit and receive chain. You can control how each element radiates, and the contributions interfere constructively in the direction you want. With many channels you can, in theory, support as many beams as you have active elements, so you can keep track of multiple targets at the same time. That matters for LEO constellations, because the satellite is flying across the sky. You need to track it, and ideally have a secondary beam already pointing at the next satellite, so the handover is smooth.\u003C/p>\n\n\n\n\u003Cp>The downside of a phased array is complexity and power. All those transmit and receive chains add up. RIS is where you get a different trade. Instead of discretizing the aperture with active antenna elements, you discretize it with “passive units” that reflect the incoming wave from a feed.\u003C/p>\n\n\n\n\u003Cp>That means you might go from ten transmitters down to a couple, while keeping the beamforming behavior you want. This results in lower power consumption, lower profile, and once you have designed the surface, it modulates its response to whatever feed you put in front of it. It is a software-defined beamformer.\u003C/p>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"h-how-ris-works-physically\">\u003Cstrong>How RIS Works Physically\u003C/strong>\u003C/h3>\n\n\n\n\u003Cp>\u003Cstrong>Jonathan:\u003C/strong> At a hardware level, what is actually happening on the surface? How do the individual unit cells interact with an incoming electromagnetic wave, and what gives the surface its “intelligence”?\u003C/p>\n\n\n\n\u003Cp>\u003Cstrong>Rodrigo:\u003C/strong> The surface works by modulating the phase distribution of the reflection for an incoming wave. Each individual cell, each pixel, controls locally how the phase of the reflection looks.\u003C/p>\n\n\n\n\u003Cp>We can do this in different ways. PIN diodes, varactor diodes, transistors, MEMS switches, liquid crystals. PIN diodes and switches are probably the most widely used today. The intelligence of the panel comes from how we control each cell, how each cell switches and how each cell sets its local reflected phase.\u003C/p>\n\n\n\n\u003Cp>\u003Cstrong>Jonathan:\u003C/strong> And where does the incoming wave actually come from?\u003C/p>\n\n\n\n\u003Cp>\u003Cstrong>Rodrigo:\u003C/strong> It can come from different places. The most traditional layout replaces a classical reflectarray. The RIS is a flat panel, with a horn antenna or other radiator sitting in front of it, and the radiation reflects off the panel like a normal reflector system. The feed could be done in other ways too. The point is that the panel does not care, it just modulates whatever wave you put on it.\u003C/p>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"h-the-simulation-challenge\">\u003Cstrong>The Simulation Challenge\u003C/strong>\u003C/h3>\n\n\n\n\u003Cp>\u003Cstrong>Jonathan:\u003C/strong> Designing something that manipulates EM waves at the unit cell level, across a structure that could have thousands of elements, sounds computationally demanding. What makes simulating a RIS so different from simulating a conventional antenna or reflector?\u003C/p>\n\n\n\n\u003Cp>\u003Cstrong>Rodrigo:\u003C/strong> The answer is twofold. There is the challenge of simulating the unit cell itself, and there is the challenge of solving the full panel with thousands of elements.\u003C/p>\n\n\n\n\u003Cp>For traditional reflectors, and even for conventional phased arrays, we have very established simulation methods. For RIS, fewer established workflows exist.\u003C/p>\n\n\n\n\u003Cp>On the unit-cell side, the first job is to find a suitable cell. You want phase stability, and you want low losses, across the entire bandwidth of interest. That sounds simple. In practice, it is hard. If we take a 1-bit phase resolution RIS, the instinct is, “I will load the cell with a delay line through a switch, and when the switch is on I get 180 degrees of phase compensation.” Conceptually, that is correct. The challenge is keeping that 180-degree phase difference stable across the bandwidth, while also constrained by the size of the unit cell, the number of elements and the mounting. Not every starting design will give you that stability when loaded.\u003C/p>\n\n\n\n\u003Cp>The second part is beamforming. With a phased array, you can compute amplitudes and phases for each element to achieve a target beam shape using established methods. With a reflecting surface, more variables come into play. The radiation pattern of the feed matters. The set of states each pixel can take is limited. The distance between feed and panel matters. There is no closed form calculation. You optimize.\u003C/p>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"h-bridging-scales\">\u003Cstrong>Bridging Scales\u003C/strong>\u003C/h3>\n\n\n\n\u003Cp>\u003Cstrong>Jonathan:\u003C/strong> RIS design seems to sit at the intersection of very fine-scale unit cell physics and large system-level behavior. How do engineers manage that jump in scale, and where does simulation fit into that workflow?\u003C/p>\n\n\n\n\u003Cp>\u003Cstrong>Rodrigo:\u003C/strong> The short answer is, with a dedicated simulation strategy. If you have the right method, you can solve a full-sized panel with thousands of elements in a matter of seconds, on a working laptop.\u003C/p>\n\n\n\n\u003Cp>That speed is what makes the workflow useful. You can take simulated panel data as synthetic data, and feed it directly into your beamforming algorithms.\u003C/p>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"h-tools-in-practice\">\u003Cstrong>Tools in Practice\u003C/strong>\u003C/h3>\n\n\n\n\u003Cp>\u003Cstrong>Jonathan:\u003C/strong> When you are optimizing a RIS design for a specific SATCOM scenario, what does that simulation workflow actually look like? Which tools and methods are you using, and how do they connect?\u003C/p>\n\n\n\n\u003Cp>\u003Cstrong>Rodrigo:\u003C/strong> The first step is the unit cell. We use a combination of design of experiments to explore the parameter design space of the unloaded cell, plus an optimization loop for the loaded states we are interested in.\u003C/p>\n\n\n\n\u003Cp>In practice, that means orchestrating \u003Ca href=\"https://www.3ds.com/products/simulia/cst-studio-suite\">CST Studio Suite\u003C/a> simulations of the unit cell using Process Composer. The DOE loop sweeps over substrate characteristics, geometric features, unit cell size. For each candidate, we then check whether, once loaded with a delay line, the cell delivers stable phase reflection and low losses across the bandwidth. From that pool, we pick the best designs.\u003C/p>\n\n\n\n\u003Cp>For the full panel we switch tools. Now we move to a workflow that uses \u003Ca href=\"https://www.3ds.com/products/simulia/wasp-net\">WASP Net\u003C/a> technology in the background. WASP Net is one of the dedicated electromagnetic software in the SIMULIA portfolio, originally built for very electrically large problems like reflector systems and slotted waveguide antennas, among others. We recently added a dedicated solver inside WASP Net to tackle RIS specifically.\u003C/p>\n\n\n\n\u003Cp>With it, we simulate how the panel interacts with the actual feed (a horn antenna in our examples), and how each pixel state affects the reflected wave. A panel with a thousand plus elements, with a useful number of bits of phase resolution, solves in seconds on a laptop.\u003C/p>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"h-building-confidence-in-the-simulated-data\">\u003Cstrong>Building Confidence in the Simulated Data\u003C/strong>\u003C/h3>\n\n\n\n\u003Cp>\u003Cstrong>Jonathan:\u003C/strong> How do we build confidence in the simulated data before we go to production?\u003C/p>\n\n\n\n\u003Cp>\u003Cstrong>Rodrigo:\u003C/strong> The first step is numerical validation. We are fortunate at \u003Ca href=\"https://www.3ds.com/products/simulia\">SIMULIA\u003C/a> to have a roster of solvers to choose from. Some run more slowly at the scale of a full panel. They make up for it by letting us load a full beamformer model with no simplifications, and run a single scenario, one specific phase distribution.\u003C/p>\n\n\n\n\u003Cp>Then we compare those results against the fast method we ran in WASP Net. Two completely different numerical techniques, two different meshes, two different model construction strategies. When the curves sit on top of each other, that is how we build confidence.\u003C/p>\n\n\n\n\u003Cp>This kind of cross-validation is especially important because the unit cell approach itself contains assumptions. We treat each cell as if it were identical, surrounded by infinite identical neighbors, all in the same state. On a real RIS, that is not strictly true. Different pixels are in different states. RIS is, more accurately, a quasi-periodic structure. The validation step, plus the optimization cycle around the unit cell, is how we keep that assumption honest.\u003C/p>\n\n\n\n\u003Cfigure class=\"wp-block-image size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"681\" height=\"608\" src=\"https://blog-assets.3ds.com/uploads/2026/05/image-92.png\" alt=\"\" class=\"wp-image-302843\" srcset=\"https://blog-assets.3ds.com/uploads/2026/05/image-92.png 681w, https://blog-assets.3ds.com/uploads/2026/05/image-92-300x268.png 300w\" sizes=\"auto, (max-width: 681px) 100vw, 681px\" />\u003Cfigcaption class=\"wp-element-caption\">1\u003Cstrong>bit phase resolution 42×42 RIS showing example of pixel control.\u003C/strong>\u003C/figcaption>\u003C/figure>\n\n\n\n\u003Cp>\u003C/p>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"h-where-simulation-still-falls-short\">\u003Cstrong>Where Simulation Still Falls Short\u003C/strong>\u003C/h3>\n\n\n\n\u003Cp>\u003Cstrong>Jonathan:\u003C/strong> What are the current limits of EM simulation for RIS design? Are there physical effects, environmental factors or system-level interactions that are hard to capture today?\u003C/p>\n\n\n\n\u003Cp>\u003Cstrong>Rodrigo:\u003C/strong> A few things. The unit cell technique I just described has its premise (an infinite, uniformly excited periodic environment) that does not perfectly hold for a real RIS. That is one limitation we keep in mind and one reason validation matters.\u003C/p>\n\n\n\n\u003Cp>The other big challenge is system-level integration. Customers are pushing toward really low-profile antennas, very thin packages, where the feed, the RIS, and the radome are all stacked into a single compact ground terminal. That is hard to model end-to-end today. We can simulate a RIS as a replacement for a traditional reflectarray very well. We cannot yet simulate every integrated stackup our customers are envisioning. We are working on it, and expect to bridge that gap in the coming year.\u003C/p>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"h-the-road-ahead\">\u003Cstrong>The Road Ahead\u003C/strong>\u003C/h3>\n\n\n\n\u003Cp>\u003Cstrong>Jonathan:\u003C/strong> Where do you see RIS technology going more broadly, and how do you expect simulation tools and workflows to evolve to keep pace?\u003C/p>\n\n\n\n\u003Cp>\u003Cstrong>Rodrigo:\u003C/strong> RIS is fundamentally an alternative to conventional antenna arrays, used as the beamforming mechanism inside an antenna system. It is appealing wherever you want the flexibility to reshape your beam over time, with fewer channels than a full active base station, for example, and with much lower power consumption.\u003C/p>\n\n\n\n\u003Cp>Satcom is the obvious case. Looking further out, 6G is shaping up as a network of networks, with Satcom as part of it, and RIS fits that vision. There is also a strong case at the edge of the network. You might want an extra base station presence in a sector that does not justify a full active antenna unit, or where power constraints rule one out. RIS based antennas can fill those gaps.\u003C/p>\n\n\n\n\u003Cp>On the simulation side, the answer is yes, the tooling will keep pace. We are already working on it. The combination of a clearer view of how the industry uses RIS in real antenna systems, plus the speed and integration challenges I mentioned, points to additional workflows and additional solvers across the SIMULIA portfolio. That speed matters especially if you want to use synthetic simulation data to train beamforming models, which is the direction we see customers heading.\u003C/p>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"h-closing-thoughts\">\u003Cstrong>Closing Thoughts\u003C/strong>\u003C/h3>\n\n\n\n\u003Cp>What stands out from the conversation is how much of RIS is still a simulation problem. The hardware concept is elegant. The wave physics is interesting. The leverage, though, is in being able to design a unit cell, validate it against full physics, and then drive a thousand pixel beamforming optimization fast enough to actually iterate. That combination is what turns RIS from a clever surface into a practical building block for the next generation of Satcom and 6G antennas.\u003C/p>\n\n\n\n\u003Cp>If you want to find out more, Rodrigo has presented a series of in-depth webinars, including \u003Ca href=\"https://events.3ds.com/simulia-reflective-intelligent-surfaces\">Reconfigurable Intelligent Surfaces,\u003C/a> which is available to watch on demand. \u003Ca href=\"https://events.3ds.com/exploring-future-6g-advanced-antenna-systems\">Exploring the Future: 6G and Advanced Antenna Systems\u003C/a> offers a broader view on how emerging technologies and advanced antenna systems are influencing the future of wireless technology.\u003C/p>\n\n\n\n\u003Cp>\u003C/p>\n\n\n\n\u003Cfigure class=\"wp-block-image\">\u003Ca href=\"https://www.3ds.com/products-services/simulia/communities/simulia-community/?_gl=1*flg7k7*_ga*MTE2NzE3NTU0OS4xNzAxODA4NTI0*_ga_DYJDKXYEZ4*MTcwMzA5Mjk1NS4xMS4xLjE3MDMwOTQ5NTEuMTQuMC4w#_ga=2.128142988.12672350.1703092955-1167175549.1701808524\" target=\"_blank\" rel=\"noreferrer noopener\">\u003Cimg decoding=\"async\" src=\"https://blog-assets.3ds.com/uploads/2023/03/simulia-communities-email-signature.jpg\" alt=\"\"/>\u003C/a>\u003C/figure>\n\n\n\n\u003Cp>\u003C/p>\n\n\n\n\u003Cp>\u003Cem>Interested in the latest in simulation? Looking for advice and best practices? Want to discuss simulation with fellow users and Dassault Systèmes experts?\u003C/em> \u003Cem>The \u003C/em>\u003Ca href=\"https://www.3ds.com/products-services/simulia/communities/learning-community/#_ga=2.186231657.1161542608.1587928634-d6a834f0-fe99-11e9-a0d7-7bef9ed67a15\" target=\"_blank\" rel=\"noreferrer noopener\">\u003Cem>SIMULIA Community\u003C/em>\u003C/a>\u003Cem> is the place to find the latest resources for SIMULIA software and to collaborate with other users. The key that unlocks the door of innovative thinking and knowledge building, the SIMULIA Community provides you with the tools you need to expand your knowledge, whenever and wherever\u003C/em>.\u003C/p>\n","2026-05-28T16:03:02",[],{"node":39,"__typename":50},{"nicename":40,"description":41,"slug":40,"name":42,"firstName":43,"lastName":44,"avatar":45,"__typename":49},"rodrigoenjiu|jonathanoakley","Rodrigo Enjiu is a member of the IPS team for the High-Tech Industry in the SIMULIA Brand. With over a decade of dedicated experience in electromagnetic simulation, he specialized in high-frequency applications, handling both pre- and post-sales responsibilities. In his current role, Rodrigo is dedicated to enhancing simulation workflows and designing innovative solutions for first-of-its-kind challenges. He earned his BSc in Science and Technology in 2011 and Information Engineering in 2012, both from UFABC in Brazil. In 2022, he obtaining an MBA from the Frankfurt School of Finance and Management in Germany. Rodrigo's expertise and interests encompass telecommunications (including 5G/6G technologies), meta-materials, and network planning.|Jonathan Oakley is currently Director of High-Tech Industry Enablement at Dassault Systèmes SIMULIA where he is responsible for technical content, advanced engagements, and new methodology. Previously he has held leadership positions at a Silicon Valley start-up company and at CST where he looked after North American sales prior to its acquisition by Dassault Systèmes in 2016. Jonathan has an engineering background in electronics and electromagnetic simulation and holds a B.Sc. in Electronic Engineering.","Rodrigo Enjiu|Jonathan Oakley","Rodrigo|Jonathan","Enjiu|Oakley",{"default":46,"url":47,"__typename":48},"mm","https://blog-assets.3ds.com/uploads/2026/05/rodrigo_enjiu-96x96.png|https://blog-assets.3ds.com/uploads/2026/05/jonathan_oakley-96x96.jpg","Avatar","User","NodeWithAuthorToUserConnectionEdge",{"edges":52,"nodes":60,"__typename":64},[53],{"isPrimary":54,"node":55,"__typename":59},true,{"slug":56,"name":57,"__typename":58},"design-simulation","Design & Simulation","Taxonomy_topic","PostToTaxonomy_topicConnectionEdge",[61],{"id":62,"name":57,"uri":63,"__typename":58},"dGVybTo4NTU5","/topics/design-simulation/","PostToTaxonomy_topicConnection",{"nodes":66,"__typename":72},[67],{"id":68,"name":69,"uri":70,"__typename":71},"dGVybTo4Nzc0","Electromagnetics","/tags/electromagnetics/","Taxonomy_tag","PostToTaxonomy_tagConnection",{"edges":74,"nodes":81,"__typename":83},[75],{"isPrimary":54,"node":76,"__typename":80},{"slug":77,"name":78,"__typename":79},"simulia","SIMULIA","Taxonomy_brand","PostToTaxonomy_brandConnectionEdge",[82],{"name":78,"slug":77,"__typename":79},"PostToTaxonomy_brandConnection",{"nodes":85,"__typename":89},[86],{"name":87,"__typename":88},"CST Studio Suite","Taxonomy_keyword","PostToTaxonomy_keywordConnection",{"title":91,"metaDesc":92,"opengraphAuthor":93,"opengraphDescription":92,"opengraphTitle":20,"opengraphUrl":94,"opengraphSiteName":95,"opengraphPublishedTime":96,"opengraphModifiedTime":97,"twitterTitle":93,"twitterDescription":93,"readingTime":98,"metaRobotsNoindex":99,"__typename":100},"Reconfigurable Intelligent Surfaces","Learn more about Reconfigurable intelligent surfaces, or RIS, through the physics, the simulation workflow, and what comes next.","","https://blog-frontoffice-contrib-prd.itvpc.3ds.com/brands/simulia/reconfigurable-intelligent-surfaces-future-satellite-communication/","Dassault Systèmes blog","2026-05-28T16:03:02+00:00","2026-05-28T16:22:05+00:00",10,"index","PostTypeSEO","Post","RootQueryToPostConnection",{},{},1779985497441]