Vodafone has partnered with AMD to design high-performance silicon chips for 5G base stations, aiming to meet growing demands for AI-driven and digital services. The collaboration focuses on developing adaptive radio hardware that boosts capacity, reduces energy consumption, and shrinks the size of radio antennae, all while maintaining coverage quality. Engineers from both companies are testing AMD’s Zynq™ UltraScale+™ RFSoC devices at Vodafone’s Innovation Centre in Málaga, Spain. These single-chip platforms integrate multiple radio functions, including flexible Arm® processors, making them suitable for dynamic 5G deployments.
AMD’s Zynq UltraScale+ RFSoC chips offer a major advantage with their adaptability. Unlike fixed-function Application Specific Integrated Circuits (ASICs), these chips can be remotely reconfigured after deployment, enabling Vodafone to support evolving AI algorithms, new 5G standards, and increased traffic during peak periods without hardware replacements. Their modular architecture also aligns with Open Radio Access Network (Open RAN) principles, allowing seamless integration with equipment from different vendors. Vodafone is simultaneously evaluating compatible radio units from multiple suppliers, fostering a diverse and efficient chip ecosystem.
Energy efficiency is another key focus of this partnership. Vodafone is testing AMD chipsets to optimize power amplifier (PA) efficiency, which accounts for most network energy consumption. Proprietary 5G algorithms dynamically adjust power use based on customer demand, similar to a thermostat, further enhancing efficiency. By embedding these energy-saving technologies, Vodafone can meet future demands for features like network slicing, which provides dedicated, secure network slices to businesses, hospitals, and other critical users.
• Vodafone and AMD developing 5G base station silicon chips.
• Testing conducted at Vodafone’s Innovation Centre in Málaga, Spain.
• AMD Zynq UltraScale+ RFSoC chips enable remote updates and support Open RAN.
• Focus on reducing antenna size, energy consumption, and network power use.
• Algorithms and advanced technologies drive scalability and energy efficiency.
