TL;DR
AIIM is an adaptive, learning-driven interference mitigation xApp for 5G O-RAN networks, improving QoS and reducing interference in multi-vendor, heterogeneous deployments through real-world full-stack evaluation.
Contribution
This work introduces AIIM, a novel adaptive interference mitigation solution evaluated in a realistic full-stack O-RAN system, demonstrating practical benefits over traditional methods.
Findings
AIIM improves QoS satisfaction in 5G networks.
AIIM reduces interference-induced PRB loss compared to baseline scheduling.
AIIM maintains comparable aggregate network throughput.
Abstract
Inter-cell interference is a persistent issue in dense 5G deployments, especially in heterogeneous Open Radio Access Network (O-RAN) environments where coordination between base stations is limited. This paper presents AIIM, an adaptive inter-cell interference mitigation xApp for the O-RAN near-real-time RAN Intelligent Controller (near-RT RIC) that performs coordinated physical resource block (PRB) allocation across multiple base stations under diverse traffic demands and channel conditions. Unlike prior studies that rely primarily on simulation or fully hardware-centric testbeds, AIIM is developed and evaluated in a full-stack O-RAN system built on srsRAN, Open5GS, and O-RAN Software Community (ORAN-SC), and deployed on a hybrid experimental platform that simultaneously combines software defined radio (SDR)-based and virtual gNodeBs (gNBs) and user equipment (UEs). This design…
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