MEASUREMENT REPORTING BASED ON MACHINE LEARNING IN WIRELESS COMMUNICATION SYSTEM

Smart overview of the Invention

The disclosure focuses on enhancing measurement reporting in wireless communication systems through machine learning (ML). User equipment (UE) is configured to receive a network configuration for measurement reporting involving multiple ML models. The UE selects a set of ML models based on this configuration, processes inputs through these models to derive measurement results, and transmits at least one result back to the network.

Technical Background

The development of 3rd Generation Partnership Project (3GPP) Long-Term Evolution (LTE) and New Radio (NR) systems aims to meet increasing demands for high-speed communications. These systems require efficient use of frequency bands, reduced costs, and improved service quality. The NR system, in particular, seeks to address diverse usage scenarios such as enhanced Mobile BroadBand (eMBB) and Ultra-Reliable and Low Latency Communications (URLLC) while being forward-compatible.

Methodology

The UE receives configuration data from the network regarding ML models for measurement reporting. It determines which models to use, processes measurement inputs through these models, and sends the results back to the network. This process allows the UE to leverage optimal ML models, improving performance and potentially reducing power consumption.

System Components

The system includes a UE with transceivers, processors, and memory to execute instructions for the described operations. Similarly, network nodes are equipped with transceivers and processors to transmit configurations and receive measurement results. The system architecture supports a variety of wireless multiple access technologies, including CDMA, TDMA, and OFDMA, enhancing adaptability across different communication standards.

Advantages and Applications

Implementing ML in measurement reporting offers several benefits, such as optimized model operation and reduced power consumption. The system's adaptability to various wireless technologies and scenarios ensures broad applicability. The approach is not limited to the described advantages, as further technical effects can be derived from the disclosure's features, potentially leading to enhanced communication system capabilities.