Demonstration of LITE: Trajectory-Unaware CSI Estimation as an O-RAN xApp for CF-MaMIMO
We present LITE, a lightweight trajectory-unaware CSI estimation framework implemented as an O-RAN xApp and integrated within a CF-MaMIMO emulator. LITE compresses high-dimensional CSI at the O-DU, transports a compact latent representation over the midhaul, and predicts short-horizon channel gains at the Near-RT RIC using a compact SE-BiLSTM model. The demo highlights end-to-end real-time operation, interactive visualization, fault injection, and fallback mechanisms under realistic impairments such as missing or delayed measurements. Results show stable and accurate per-AP predictions while meeting Near-RT latency constraints, demonstrating the feasibility of embedding bandwidth-aware intelligence in O-RAN-compliant RAN loops.