Low-Complexity Design and Implementation of a Software-Defined 5G Energy Detector for Fast Initial Cell Selection

Abstract

Energy detection is crucial during initial cell selection as it effectively assists the User Equipment (UE) in swiftly identifying a suitable Radio Frequency (RF) channel from numerous candidates. Implementing a Software-Defined Modem (SDM) presents a critical challenge of enabling energy detection, which traditionally requires high computational complexity in conventional hardware modems. This paper introduces a software-defined energy detector designed with low complexity, specifically tailored for an SDM. We design and implement an off-the-shelf energy detector that is fully software-based, with the goal of significantly reducing the time required for initial cell selection in an SDM. The software-defined energy detector is specialized for measuring 5G Synchronization Signal Blocks (SSBs). It emphasizes the key feature of the moving average filter which enables efficient computation of signal energy for an SSB. To enable real-time operation, the algorithm for the software-defined energy detector is designed to seamlessly utilize Single Instruction and Multiple Data (SIMD) functions. By implementing the software-defined energy detector, we optimize the detection parameters, thereby enhancing the practical performance of energy detection. The experimental results demonstrate that the software-defined energy detector can accurately evaluate the signal energy of the 5G SSBs with reasonable computational complexity.

Keywords

• Energy detector
• softwarization
• software-defined modem (SDM)
• 5G synchronization signal block (SSB)