Prediction of Reliable Channel Connectivity in URLLC Scenario Base on
RSS Measurement
Abstract
Applying high-reliability and low-latency scenarios of the
fifth-generation mobile communication technology (5G) to large-capacity
and low-latency services in the power system requires meeting the
communication reliability requirements specified by the power system.
However, reliability metrics based on packet loss rate fail to capture
the time-dependent characteristic of time-varying wireless channels and
the healthy transmission duration required for different ultra-reliable
and low-latency communication (URLLC) services. Therefore, to analyze
the performance of channels within a given time interval, this study
employs survival analysis methods to combine URLLC key technologies with
failure rate functions in reliability theory. By utilizing the received
signal strength (RSS), theoretical distribution models and data-driven
models are established to predict the channel reliability within the
next subframe. A case study is conducted by using of the UMa-NLOS-CDL
channel model to compare and analyze the proposed methods. Furthermore,
considering different rain fading conditions, the reliability of
multiple-input multiple-output (MIMO) and multiple-input single-output
(MISO) channel systems is compared and analyzed