ADRF adds PowerSmart software to ADXV DAS, claiming 60% power cut
Advanced RF Technologies (ADRF) has released PowerSmart Control, a software update for its ADXV Series distributed antenna system (DAS) platform that the company says can reduce power consumption by up to 60%. The functionality ships as part of the latest software version for the ADXV Series and is available to operators and enterprise customers at no additional licence cost.
The Burbank, California-based vendor says the savings are achieved through three mechanisms: adjustable output power across all remote units via an automatic level control function, an RF band standby mode that allows individual frequency bands to be scheduled offline during low-demand periods, and the ability to switch MIMO configurations to SISO operation when traffic conditions allow. All three controls are accessible through a web-based graphical user interface on the DAS headend, meaning network managers can make changes without on-site visits to remote units.
How the technology works
Power Output Adjustment lets operators dial down transmitted power to a user-specified level across the remote-unit fleet, rather than running all units at full capacity continuously. RF Band Standby complements this by allowing specific spectrum bands, such as a 5G mid-band carrier, to be suspended overnight in a venue that sees negligible traffic outside business hours. MIMO-to-SISO switching addresses the power draw of additional antenna paths: a four-port MIMO configuration carries a higher RF processing overhead than a two-port SISO configuration, so temporarily collapsing to SISO during off-peak windows reduces load without removing coverage.
Victor Mejia, Product Manager at Advanced RF Technologies, said: "By combining intelligent power management with the proven performance of our ADXV Series DAS platform, customers can significantly reduce energy consumption and operating costs while maintaining the high-quality connectivity their users depend on."
The release frames PowerSmart Control partly in the context of AI-driven power demand, noting that organisations across all sectors are under pressure to reduce energy costs at a time when data-intensive workloads are pushing overall power consumption upward.
Market context and competitive landscape
In-building wireless infrastructure is a sector where energy efficiency has become a differentiated selling point rather than a secondary consideration. DAS deployments in large venues, hospitals, transport hubs and enterprise campuses run continuously, and for neutral host operators managing multiple tenants across a portfolio of buildings, the cumulative electricity cost is a meaningful operating expense. Competing in-building wireless vendors, including CommScope, Corning and Boingo Wireless, have each begun publicising energy-management features in recent product cycles as sustainability commitments from enterprise customers increasingly influence procurement decisions.
Software-driven load management is also consistent with the broader direction of the telecom equipment sector, where vendors are embedding open-loop and closed-loop energy-saving algorithms directly into radio units, in line with guidance from bodies such as the O-RAN Alliance's Working Group 3, which has published specifications for sleep-mode and energy-saving management in open RAN architectures. While ADRF's ADXV Series is a traditional active DAS rather than an O-RAN product, the principle of demand-responsive power scaling is the same.
ADRF holds ISO 9001 and TL 9000 quality certifications and carries Minority Business Enterprise and Women's Business Enterprise designations, which can be relevant to procurement frameworks requiring supplier diversity. The company was established in 1999 and describes itself as focused on in-building wireless for venues of any size.
The company did not publish independent third-party benchmark data to substantiate the 60% reduction figure, and the actual saving will depend on venue type, traffic profile and the DAS configuration deployed. Operators evaluating the feature should model savings against their own traffic patterns before committing to headline projections.