Category: Research

Signaling Storm is a specific case of DoS or DDoS attack identified by the O-RAN ALLIANCE to be addressed by xApps. When firing this kind of attack, devices authorized (or not) to access the network make repeated attempts to connect to the network, "clogging up" the RACH. In addition, due to the multi-stage nature of the hand-shaking procedure, a whole range of redundant control information is generated in the access and core network. It is, therefore, essential to quickly locate the source of this threat and decide to reject the connection request at an early stage of registration. In this blog, we present a signaling storm detection approach and a proposed algorithm to be implemented as an xApp for O-RAN RIC.

The operating patterns of adversaries attacking the open radio interface are complicated and not obvious, e.g., an adversary carrying out a jamming attack may change the attacked band or periodically interrupt jamming. The prospective defense algorithms should be able to not only detect anomalies but also adapt to a variety of attack mechanisms. This can be done by AI/ML methods, which have been researched over the last years. In this post, we present an AI/ML-based jamming attack detection and analysis mechanism for Near-RT RIC.

Energy consumption is a critical aspect of any service in these modern times. In telecommunications, a flexible approach to network planning, control, and management is extremely beneficial in this aspect. The concept of O-RAN enables the creation of algorithms that allow energy saving in a manner independent of the equipment or RAN software solution used. In this blog post, we present an innovative approach to energy saving using the RIC, which is based on the direct cooperation of Traffic Steering xApp and Energy Saving rApp.

This year, the most crucial topics for further development in O-RAN are security and energy efficiency. In this blog post, we investigate how different players of the O-RAN ecosystem look at the security topic. Those include O-RAN ALLIANCE, the telecommunication business (including operators and providers), governmental bodies, IEEE, and academic researchers.

In this blog post, we provide the description of an algorithm that can be realized as an rApp in the O-RAN architecture aimed at improving the network’s EE through intelligent RF channels on/off switching. First, we provide a general framework for long-timescale EE optimization which can be done in Non-RT RIC. We then propose the implementation of the RF Channel Switching algorithm within the O-RAN framework. Finally, we discuss some opportunities and challenges.

One of the key aspects of the Open RAN is embedding native intelligence within the O-RAN framework. To this end, AI/ML plays a crucial role. Some of the goals for AI/ML within RAN are: decreasing the manual effort of going through large data amounts to diagnose issues and make decisions, or predicting the future to take proactive actions. This is being addressed from the beginning within O-RAN ALLIANCE. In this post, we discuss the overall framework for machine learning within O-RAN, including architectural aspects and use cases.