At the moment, Microsoft is engaged on RAN Analytics and Management applied sciences for virtualized RAN operating on Microsoft Edge platforms. Our aim is to empower any virtualized RAN answer supplier and operators to understand the complete potential of disaggregated and programmable networks. We purpose to develop platform applied sciences that virtualized RAN distributors can leverage to realize analytics insights of their RAN software program operations, and to make use of these insights for operational automations, machine studying, and AI-driven optimizations.

Microsoft has lately made essential progress in RAN analytics and management expertise. Microsoft Azure for Operators is introducing versatile, dynamically loaded service fashions to each the RAN software program stack and cloud/edge platforms internet hosting the RAN, to speed up the tempo of innovation in Open RAN.

The aim of Open RAN is to speed up innovation within the RAN house by means of the disaggregation of features and publicity of inside interfaces for interoperability, controllability, and programmability. The present standardization effort of O-RAN by O-RAN Alliance, specifies the RAN Clever Controller (RIC) structure that exposes a set of telemetry and management interfaces with predefined service fashions (often called the E2 interface). Open RAN distributors are anticipated to implement all E2 service fashions laid out in the usual. Close to-real-time RAN controls are made doable with xApp functions accessing these service fashions.

Microsoft’s innovation extends this standard-yet-static interface. It introduces the aptitude of getting detailed inside states and real-time telemetric information out of the reside RAN software program in a dynamic trend for brand spanking new RAN management functions. With this expertise, along with detailed platform telemetry, operators can obtain higher community monitoring and efficiency optimization for his or her 5G networks, and allow new AI, analytics, and automation capabilities that weren’t doable earlier than.

This 12 months, Microsoft, along with contributions from Intel and Capgemini, has developed an analytics and management method that was acknowledged with the Mild Studying Editor’s Selection award beneath the class of Excellent Use case: Service supplier AI. This innovation requires dynamic providers fashions for Open RAN.

Dynamic service fashions for real-time RAN management

There are lots of RAN management use circumstances that require dynamic service fashions past these laid out in O-RAN in the present day, similar to entry to IQ samples, RLC and MAC queue sizes, and packet retransmission data. These high-volume real-time information have to be aggregated and compressed earlier than being delivered to the xApp. Additionally, detailed information from completely different RAN modules throughout completely different layers like L1, L2, and L3 could have to be collected and correlated in real-time earlier than any helpful perception could be derived and shared with xApp. Additional, a virtualized RAN presents so many extra potentialities, that any static interface or service mannequin could also be ineffective in assembly the extra superior real-time management wants.

One such instance happens with interference detection. Right this moment, operators usually have to do a drive check to detect exterior interference in a macro cell. However now, Open RAN has the potential to interchange the costly truck roll with a software program program that detects interference alerts on the RAN’s L1 layer. Nonetheless, this can require a brand new information service mannequin with direct entry to uncooked IQ samples on the bodily layer. One other instance exists in dynamic energy saving. If a RAN energy controller can see the variety of packets queued at numerous locations within the reside RAN system, then it may possibly estimate the pending course of masses and optimize the CPU frequency at a really excessive tempo, to be able to cut back the RAN server energy consumption. Our research has proven that we will cut back the RAN energy consumption by 30 % by means of this technique—even throughout busy intervals. To help this in Open RAN, we are going to want a brand new service mannequin that exposes packet queuing data.

These new use circumstances are envisioned for the time after the present E2 interface has been standardized. To attain them, although, we want new RAN platform applied sciences to shortly prolong this interface to help these and future superior RAN management functions.

The Microsoft RAN analytics and management framework

The Microsoft RAN analytics and management framework extends the present RIC service fashions in O-RAN structure to be each versatile and dynamic. Within the course of, the framework permits RAN answer suppliers and operators to outline their very own service fashions for dynamic RAN monitoring and management. Right here, the underlying expertise is a runtime system that may dynamically load and execute third-party code in a trusted and secure method.

This method permits operators and trusted third-party builders to put in writing their very own telemetry, management, and inference items of code (referred to as “codelets”) that may be deployed at runtime at numerous factors within the RAN software program stack, with out disrupting the RAN operations. The codelets are executed inline within the reside RAN system and on its essential paths, permitting them to get direct entry to all essential inside uncooked RAN information buildings, to gather statistics, and to make real-time inference and management choices.

To make sure safety and security, the codelets checked with static verified with verification instruments earlier than they are often loaded, and they are going to be mechanically pre-empted if operating longer than the predefined execution budgets. The dynamic code extension system is similar because the Prolonged Berkeley Packet Filter (eBPF), which is a confirmed expertise that has been entrusted to run customized codes in Linux kernels on tens of millions of mission-critical servers across the globe. The inline execution can also be extraordinarily quick, usually incurring lower than one % of overhead on the prevailing RAN operations.

The next picture illustrates the general framework and the dynamic service mannequin denoted by the star circle with the letter D.The image illustrates the overall framework and the dynamic service model for virtual RAN.

The advantage of the dynamic extension framework with low-latency management is that it may possibly open the chance for third-party real-time management algorithms. Historically, because of the tight timing constraint, a real-time management algorithm should be tightly carried out and built-in contained in the RAN system. The Microsoft RAN analytics framework permits RAN software program to delegate sure real-time management to RIC, probably resulting in a future market the place real-time management algorithms, machine studying, and AI fashions for optimizations could also be doable.

Microsoft, Intel, and Capgemini have collectively prototyped this expertise in Intel’s FlexRAN™ reference software program and Capgemini’s 5G RAN. We’ve additionally recognized normal instrumentation factors aligned with the usual 3GPP RAN structure to realize increased visibility into the RAN’s inside state. We’ve additional developed 17 dynamic service fashions, and enabled many new and thrilling functions that had been beforehand not thought doable.

Examples of recent functions of RAN analytics

With this new Analytics and Management Framework, functions of dynamic energy financial savings and interference detection described earlier can now be realized.

RAN-agnostic dynamic energy saving

5G RAN power consumption is a serious OPEX merchandise for any cellular operator. In consequence, it’s paramount for a RAN platform supplier to seek out any alternative to avoid wasting energy when operating the RAN software program. One such alternative could be discovered by stepping down the RAN server CPU frequency when the RAN processing load just isn’t at full capability. That is certainly promising as a result of web visitors is intrinsically “bursty”; even throughout peak hours, the community is never operated at full capability.

Nonetheless, any dynamic RAN energy controller should even have correct load prediction and quick response in millisecond timescale. In any other case, if one a part of RAN is in hibernation, then any immediate visitors burst will trigger severe efficiency points, and even crashes. The Microsoft RAN analytics framework with dynamic service fashions and low-latency control-loop makes it doable to put in writing a novel CPU frequency prediction algorithm primarily based on the variety of lively customers, and modifications in numerous queue sizes. We’ve carried out this algorithm on prime of Capgemini 5G RAN and Intel FlexRAN™ reference software program, and we achieved as much as 30 % power financial savings—even throughout busy intervals.

Interference detection

Exterior wi-fi interference has lengthy been a supply of efficiency points in mobile networks. Detecting exterior wi-fi interference is tough and infrequently requires a truck roll with specialised tools and specialists to detect it. With dynamic service fashions, we will flip an O-RAN 5G base station right into a software-defined radio that may detect and characterize exterior wi-fi interference with out affecting the radio efficiency. We’ve developed a dynamic service mannequin that averages the acquired IQ samples throughout frequency chunks and occasions inside an L1 of the FlexRAN™ reference software program stack. The service mannequin in flip stories the averages to an utility that runs an AI and machine studying mannequin for anomaly detection, to be able to detect when the noise ground will increase.

Virtualized and software-based RAN answer supply immense potential of programmable networks that may leverage AI, machine studying, and analytics to enhance community effectivity. Dynamic service fashions for O-RAN interfaces additional enhances the tempo of innovation with added flexibility and safety.

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