Discover how telcos use AI to transform networks, customer experiences, and open business opportunities.
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Wireless technology has evolved rapidly and the 5G deployments have made good progress around the world. Up until recently, wireless RAN was deployed using closed-box appliance solutions by traditional RAN vendors. This closed-box approach is not scalable, underuses the infrastructure, and does not deliver optimal RAN TCO. It has many shortcomings. We have come to realize that such closed-box��
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The pace of 5G investment and adoption is accelerating. According to the GSMA Mobile Economy 2023 report, nearly $1.4 trillion will be spent on 5G CapEx, between 2023 and 2030. Radio access network (RAN) may account for over 60% of the spend. Increasingly, the CapEx spend is moving from the traditional approach with proprietary hardware, to virtualized RAN (vRAN) and Open RAN architectures��
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5G deployments have been accelerating around the globe. Many telecom operators have already rolled out 5G services and are expanding rapidly. In addition to the telecom operators, there is significant interest among enterprises in using 5G to set up private networks leveraging higher bandwidth, lower latency, network slicing, mmWave, and CBRS spectrum. The 5G ramp comes at an interesting��
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The role of artificial intelligence (AI) in boosting performance and energy efficiency in cellular network operations is rapidly becoming clear. This is especially the case for radio access networks (RANs), which account for over 60% of industry costs. This post explains how AI is transforming the 5G RAN, improving energy and cost efficiency while supporting better use of RAN computing��
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The cellular industry spends over $50 billion on radio access networks (RAN) annually, according to a recent GSMA report on the mobile economy. Dedicated and overprovisioned hardware is primarily used to provide capacity for peak demand. As a result, most RAN sites have an average utilization below 25%. This has been the industry reality for years as technology evolved from 2G to 4G.
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5G CloudRAN is the cloud-native architecture that supports PHY layer processing for high-speed, low bandwidth, software-defined network applications. The Aerial SDK provides libraries and functions to implement L1 layer processing with LDPC optimization and other features. With O-RAN fronthaul and Aerial SDK PHY capabilities, seamless packet flow can be achieved from edge application to COTS��
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NVIDIA Mellanox 5T for 5G technology provides a real-time and high-performance solution for building an efficient, time-synchronized CloudRAN infrastructure. Time synchronization and achieving high time accuracy for network traffic between O-RAN 7.2x compliant front-haul, mid-haul, and back-haul components in a cloud-native RAN (CloudRAN) environment has always been a challenge. Further��
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Fifth-generation networks (5G) are ushering in a new era in wireless communications that delivers 1000X the bandwidth and 100X the speed at 1/10th the latency of 4G. 5G also allows for millions of connected devices per square km and is being deployed as an alternative to WiFi at edge locations like factories and retail stores. These applications demand a new network architecture that is fully��
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