Masked Amazon engineer seated at a work table tests a Project Kuiper antenna
Project Kuiper antenna development and testing is occurring at the team's facility in Redmond, Washington.

Nima Mahanfar discusses the science behind Project Kuiper customer terminal antenna

The senior manager of hardware and antenna development for Project Kuiper answers questions related to the development of new custom-built antenna that advances this ambitious project to provide affordable broadband to unserved and underserved communities around the globe.

Amazon today provided an update on Project Kuiper, its initiative to increase broadband access through a constellation of 3,236 low-Earth orbit (LEO) satellites. The team released information on the Ka-band phased array antenna for its low-cost customer terminal, signaling another milestone in the company’s efforts to provide fast and affordable broadband access to communities around the world.

Nima Mahanfar
Nima Mahanfar

The prototype antenna is based on a new architecture designed and developed by the Project Kuiper team. The initial prototype is delivering speeds of up to 400 Mbps, despite a form factor that is approximately 12 inches in diameter and significantly lighter than legacy antenna designs. The reduction in size and complexity will allow Amazon to reduce production costs, contributing to the team’s goal of providing customers a terminal that is affordable and easy to install.

The antenna design and manufacturing effort is led in-house by the Project Kuiper team at Amazon. In advance of today’s announcement, Amazon Science asked Nima Mahanfar, senior manager of antenna development for Project Kuiper, about designing and developing the antenna, the science and engineering challenges his team encountered, tradeoffs the team had to wrestle with, and more.

The Kuiper prototype antenna is smaller and lighter than legacy Ka-band antennas. How did your team achieve that goal? 

The key advancement was combining transmit and receive phased-array antennas into one aperture. This can be done in other frequency bands, but Project Kuiper plans to operate in Ka-Band, which has transmit and receive frequencies that are much further apart from one another. This makes it difficult, nearly impossible in fact, to combine transmit and receive into one aperture. Phased arrays are a class of radiating system, where multiple antennas — it could be two, it could be thousands— are on the same aperture, creating a focused beam of radio waves. The distance between the antennas — or the relation between these antennas — is decided by the frequency. If the frequencies are close to each other, as with Ku-Band, you can combine the transmit and receive function into one and it works. When the frequencies are far apart, as with Ka-Band, it’s much more difficult to utilize the same lattice for both. This has never been done before — until now. 

Our design involves hundreds of antennas in each aperture, with receive antennas operating at 18 to 20 gigahertz (GHz) and transmit antennas operating at 28 to 30 GHz. Our breakthrough came from the realization that we could get to a single lattice by looking at each antenna element uniquely — helping reduce the size and cost of our entire terminal.

What were the science and engineering tradeoffs your team had to wrestle with in developing this new architecture, and what tenets guided your team’s work?

There were several, but I’ll focus on two key ones.

One is balancing the tradeoff between the transmit and receive functionality. From a customer obsession perspective, we realized that what affects the customer most is the receive function. In other words, we typically receive more information than we transmit. So we always err on the side of improving receive performance. On the transmit side, if you compromise performance, you can always increase the transmitted power by a little.

Project Kuiper customer terminal animation
"The key advancement was combining transmit and receive phased-array antennas into one aperture," Nima Mahanfar, senior manager of antenna development for Project Kuiper said. "Our breakthrough came from the realization that we could get to a single lattice by looking at each antenna element uniquely – helping reduce the size and cost of our entire terminal."

The second tradeoff relates to how easy our antenna is to manufacture. If our design was overly complex, it couldn’t be built affordably, or it couldn’t be scaled in production. We had to ask ourselves, at what point does this combined aperture become twice as complex as the single aperture, and would it still make sense? Our objective was to ensure our antenna was mass producible by mainstream circuit board manufacturers, allowing us to take advantage of economies of scale and produce millions at low cost. We had to keep our design as simple as possible to satisfy this objective, and this is an area where collaboration between scientists and manufacturing and hardware engineers was so important.

You received your PhD in high-frequency electronics and microwaves from the Université de Limoges and have been working in this field for a couple of decades. What are some of the key advancements that make Project Kuiper viable today? What are some of the interesting science and engineering challenges still left to address?

There are several important trends that make a project like this possible, and interestingly, few of them have to do with aerospace and satellite technology.

One is silicon. CMOS [complementary metal oxide semiconductor] technology has improved significantly, is available at a low cost, and can operate at higher and higher frequencies. Components that were once a luxury and confined primarily to the space and military industries, now are readily available and cost just a few dollars, or even cents. That has opened up this whole area for exploration.

The second trend comes from cellular technology and the cloud. As adoption and demand for these technologies has increased, we’ve seen higher frequency materials, and components available at larger scale and lower cost.  At one time, building a printed circuit board at 30GHz was a niche thing.  There were only a couple of manufacturers in the United States who could do this. They were expensive and they didn’t scale. Right now with 5G and even 4G cellular technology, basically we have more and more mass production of radio frequency (RF) at scale and at very high frequencies and customers are benefitting from this. 

So those are the two technology trends that are helping us innovate easier, better and cheaper. The whole area of RF used to be exclusive to the space industry, and the military.  That’s not the case anymore, and that’s great news for engineers like myself.

As for the challenges left to solve, I feel we can make phased array technology even more affordable. Not just by buying cheaper materials, but by developing new technologies and architectures that could be fundamentally different from today’s approach. We should be open-minded about the possibilities, and we are pursuing many of them already.

Another relates to the phased array technology we are building for our satellites in space, where the challenges are a little different. Cost is still important, but more importantly, we want to reduce watts per gigabits per second. Solving power challenges in space is hard, and dissipating the heat from that power is even harder. There’s no air to cool it. So having a low-power system that can provide many gigabytes of service to customers is key. How can we reduce the power consumption of these space-borne phased arrays? That’s one of the other big challenges facing anyone deploying phased array antennas in low earth orbit.

What type of scientist and engineer are you seeking to help address those challenges?

We’re seeking individuals with strong, fundamental science skills who understand the physical limits of what’s possible, and can deliver performance to that physical limit, or who can explain the imperfections for why we can’t. We want to deliver the best possible performance at the lowest possible price for our customers. To do this, we need to understand what possible based on physics rather than an arbitrary limit based on what’s been achieved in legacy systems. 

Project Kuiper is made up of engineers and scientists with decades of experience in satellite communications, many of whom hold multiple patents for their work. Most of the folks I work with are PhDs, many in the field of electromagnetics, who aren’t fearful of doing original work. This is particularly germane for phased array technology where we’ve shifted to using printed circuit board technology versus expensive ceramics and other materials. So we’re seeking individuals who can recognize science projects from the real thing, and can then build advanced designs that come close to the physical limits of what’s possible.  If this resonates with any of your readers, I hope they will visit our jobs page.

View from space of a connected network around planet Earth representing the Internet of Things.
Sign up for our newsletter

Related content

US, CA, San Francisco
About Twitch Launched in 2011, Twitch is a global community that comes together each day to create multiplayer entertainment: unique, live, unpredictable experiences created by the interactions of millions. We bring the joy of co-op to everything, from casual gaming to world-class esports to anime marathons, music, and art streams. Twitch also hosts TwitchCon, where we bring everyone together to celebrate, learn, and grow their personal interests and passions. We’re always live at Twitch. Stay up to date on all things Twitch on Linkedin, Twitter and on our Blog. About the role: Twitch builds data-driven machine learning solutions across several rich problem spaces: Natural Language Processing (NLP), Recommendations, Semantic Search, Classification/Categorization, Anomaly Detection, Forecasting, Safety, and HCI/Social Computing/Computational Social Science. As an Intern, you will work with a dedicated Mentor and Manager on a project in one of these problem areas. You will also be supported by an Advisor and participate in cohort activities such as research teach backs and leadership talks. This position can also be located in San Francisco, CA or virtual. You Will: Solve large-scale data problems. Design solutions for Twitch's problem spaces Explore ML and data research
US, CA, San Francisco
About Twitch Launched in 2011, Twitch is a global community that comes together each day to create multiplayer entertainment: unique, live, unpredictable experiences created by the interactions of millions. We bring the joy of co-op to everything, from casual gaming to world-class esports to anime marathons, music, and art streams. Twitch also hosts TwitchCon, where we bring everyone together to celebrate, learn, and grow their personal interests and passions. We’re always live at Twitch. Stay up to date on all things Twitch on Linkedin, Twitter and on our Blog. About the role: Twitch builds data-driven machine learning solutions across several rich problem spaces: Natural Language Processing (NLP), Recommendations, Semantic Search, Classification/Categorization, Anomaly Detection, Forecasting, Safety, and HCI/Social Computing/Computational Social Science. As an Intern, you will work with a dedicated Mentor and Manager on a project in one of these problem areas. You will also be supported by an Advisor and participate in cohort activities such as research teach backs and leadership talks. This position can also be located in San Francisco, CA or virtual. You Will: Solve large-scale data problems. Design solutions for Twitch's problem spaces Explore ML and data research
LU, Luxembourg
Are you a talented and inventive scientist with a strong passion about modern data technologies and interested to improve business processes, extracting value from the data? Would you like to be a part of an organization that is aiming to use self-learning technology to process data in order to support the management of the procurement function? The Global Procurement Technology, as a part of Global Procurement Operations, is seeking a skilled Data Scientist to help build its future data intelligence in business ecosystem, working with large distributed systems of data and providing Machine Learning (ML) and Predictive Modeling expertise. You will be a member of the Data Engineering and ML Team, joining a fast-growing global organization, with a great vision to transform the Procurement field, and become the role model in the market. This team plays a strategic role supporting the core Procurement business domains as well as it is the cornerstone of any transformation and innovation initiative. Our mission is to provide a high-quality data environment to facilitate process optimization and business digitalization, on a global scale. We are supporting business initiatives, including but not limited to, strategic supplier sourcing (e.g. contracting, negotiation, spend analysis, market research, etc.), order management, supplier performance, etc. We are seeking an individual who can thrive in a fast-paced work environment, be collaborative and share knowledge and experience with his colleagues. You are expected to deliver results, but at the same time have fun with your teammates and enjoy working in the company. In Amazon, you will find all the resources required to learn new skills, grow your career, and become a better professional. You will connect with world leaders in your field and you will be tackling Data Science challenges to ensure business continuity, by taking the right decisions for your customers. As a Data Scientist in the team, you will: -be the subject matter expert to support team strategies that will take Global Procurement Operations towards world-class predictive maintenance practices and processes, driving more effective procurement functions, e.g. supplier segmentation, negotiations, shipping supplies volume forecast, spend management, etc. -have strong analytical skills and excel in the design, creation, management, and enterprise use of large data sets, combining raw data from different sources -provide technical expertise to support the development of ML models to facilitate intelligent digital services, such as Contract Lifecycle Management (CLM) and Negotiations platform -cooperate closely with different groups of stakeholders, e.g. data/software engineers, product/program managers, analysts, senior leadership, etc. to evaluate business needs and objectives to set up the best data management environment -create and share with audiences of varying levels technical papers and presentations -deal with ambiguity, prioritizing needs, and delivering results in a dynamic environment Basic qualifications -Master’s Degree in Computer Science/Engineering, Informatics, Mathematics, or a related technical discipline -3+ years of industry experience in data engineering/science, business intelligence or related field -3+ years experience in algorithm design, engineering and implementation for very-large scale applications to solve real problems -Very good knowledge of data modeling and evaluation -Very good understanding of regression modeling, forecasting techniques, time series analysis, machine-learning concepts such as supervised and unsupervised learning, classification, random forest, etc. -SQL and query performance tuning skills Preferred qualifications -2+ years of proficiency in using R, Python, Scala, Java or any modern language for data processing and statistical analysis -Experience with various RDBMS, such as PostgreSQL, MS SQL Server, MySQL, etc. -Experience architecting Big Data and ML solutions with AWS products (Redshift, DynamoDB, Lambda, S3, EMR, SageMaker, Lex, Kendra, Forecast etc.) -Experience articulating business questions and using quantitative techniques to arrive at a solution using available data -Experience with agile/scrum methodologies and its benefits of managing projects efficiently and delivering results iteratively -Excellent written and verbal communication skills including data visualization, especially in regards to quantitative topics discussed with non-technical colleagues
US, CA, San Francisco
About Twitch Launched in 2011, Twitch is a global community that comes together each day to create multiplayer entertainment: unique, live, unpredictable experiences created by the interactions of millions. We bring the joy of co-op to everything, from casual gaming to world-class esports to anime marathons, music, and art streams. Twitch also hosts TwitchCon, where we bring everyone together to celebrate, learn, and grow their personal interests and passions. We’re always live at Twitch. Stay up to date on all things Twitch on Linkedin, Twitter and on our Blog. About the role: Twitch builds data-driven machine learning solutions across several rich problem spaces: Natural Language Processing (NLP), Recommendations, Semantic Search, Classification/Categorization, Anomaly Detection, Forecasting, Safety, and HCI/Social Computing/Computational Social Science. As an Intern, you will work with a dedicated Mentor and Manager on a project in one of these problem areas. You will also be supported by an Advisor and participate in cohort activities such as research teach backs and leadership talks. This position can also be located in San Francisco, CA or virtual. You Will: Solve large-scale data problems. Design solutions for Twitch's problem spaces Explore ML and data research
US, CA, San Francisco
About Twitch Launched in 2011, Twitch is a global community that comes together each day to create multiplayer entertainment: unique, live, unpredictable experiences created by the interactions of millions. We bring the joy of co-op to everything, from casual gaming to world-class esports to anime marathons, music, and art streams. Twitch also hosts TwitchCon, where we bring everyone together to celebrate, learn, and grow their personal interests and passions. We’re always live at Twitch. Stay up to date on all things Twitch on Linkedin, Twitter and on our Blog. About the role: Twitch builds data-driven machine learning solutions across several rich problem spaces: Natural Language Processing (NLP), Recommendations, Semantic Search, Classification/Categorization, Anomaly Detection, Forecasting, Safety, and HCI/Social Computing/Computational Social Science. As an Intern, you will work with a dedicated Mentor and Manager on a project in one of these problem areas. You will also be supported by an Advisor and participate in cohort activities such as research teach backs and leadership talks. This position can also be located in San Francisco, CA or virtual. You Will: Solve large-scale data problems. Design solutions for Twitch's problem spaces Explore ML and data research
US, CA, San Francisco
About Twitch Launched in 2011, Twitch is a global community that comes together each day to create multiplayer entertainment: unique, live, unpredictable experiences created by the interactions of millions. We bring the joy of co-op to everything, from casual gaming to world-class esports to anime marathons, music, and art streams. Twitch also hosts TwitchCon, where we bring everyone together to celebrate, learn, and grow their personal interests and passions. We’re always live at Twitch. Stay up to date on all things Twitch on Linkedin, Twitter and on our Blog. About the role: Twitch builds data-driven machine learning solutions across several rich problem spaces: Natural Language Processing (NLP), Recommendations, Semantic Search, Classification/Categorization, Anomaly Detection, Forecasting, Safety, and HCI/Social Computing/Computational Social Science. As an Intern, you will work with a dedicated Mentor and Manager on a project in one of these problem areas. You will also be supported by an Advisor and participate in cohort activities such as research teach backs and leadership talks. This position can also be located in San Francisco, CA or virtual. You Will: Solve large-scale data problems. Design solutions for Twitch's problem spaces Explore ML and data research
US, CA, San Francisco
About Twitch Launched in 2011, Twitch is a global community that comes together each day to create multiplayer entertainment: unique, live, unpredictable experiences created by the interactions of millions. We bring the joy of co-op to everything, from casual gaming to world-class esports to anime marathons, music, and art streams. Twitch also hosts TwitchCon, where we bring everyone together to celebrate, learn, and grow their personal interests and passions. We’re always live at Twitch. Stay up to date on all things Twitch on Linkedin, Twitter and on our Blog. About the role: Twitch builds data-driven machine learning solutions across several rich problem spaces: Natural Language Processing (NLP), Recommendations, Semantic Search, Classification/Categorization, Anomaly Detection, Forecasting, Safety, and HCI/Social Computing/Computational Social Science. As an Intern, you will work with a dedicated Mentor and Manager on a project in one of these problem areas. You will also be supported by an Advisor and participate in cohort activities such as research teach backs and leadership talks. This position can also be located in San Francisco, CA or virtual. You Will: Solve large-scale data problems. Design solutions for Twitch's problem spaces Explore ML and data research
US, WA, Seattle
We are a team of doers working passionately to apply cutting-edge advances in deep learning in the life sciences to solve real-world problems. As a Senior Applied Science Manager you will participate in developing exciting products for customers. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the leading edge of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with others teams. Location is in Seattle, US Embrace Diversity Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust Balance Work and Life Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives Mentor & Grow Careers Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future. Key job responsibilities • Manage high performing engineering and science teams • Hire and develop top-performing engineers, scientists, and other managers • Develop and execute on project plans and delivery commitments • Work with business, data science, software engineer, biological, and product leaders to help define product requirements and with managers, scientists, and engineers to execute on them • Build and maintain world-class customer experience and operational excellence for your deliverables
US, Virtual
The Amazon Economics Team is hiring Interns in Economics. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets. Some knowledge of econometrics, as well as basic familiarity with Stata, R, or Python is necessary. Experience with SQL, UNIX, Sawtooth, and Spark would be a plus. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis at Internet speed collaborating with economists, data scientists and MBAʼs. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. Roughly 85% of interns from previous cohorts have converted to full time economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com.
US, WA, Seattle
Amazon internships are full-time (40 hours/week) for 12 consecutive weeks with start dates in May - July 2023. Our internship program provides hands-on learning and building experiences for students who are interested in a career in hardware engineering. This role will be based in Seattle, and candidates must be willing to work in-person. Corporate Projects (CPT) is a team that sits within the broader Corporate Development organization at Amazon. We seek to bring net-new, strategic projects to life by working together with customers and evolving projects from ZERO-to-ONE. To do so, we deploy our resources towards proofs-of-concept (POCs) and pilot programs and develop them from high-level ideas (the ZERO) to tangible short-term results that provide validating signal and a path to scale (the ONE). We work with our customers to develop and create net-new opportunities by relentlessly scouring all of Amazon and finding new and innovative ways to strengthen and/or accelerate the Amazon Flywheel. CPT seeks an Applied Science intern to work with a diverse, cross-functional team to build new, innovative customer experiences. Within CPT, you will apply both traditional and novel scientific approaches to solve and scale problems and solutions. We are a team where science meets application. A successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment. As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to create technical roadmaps, and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems.