In the upcoming sixth-generation (6G) networks, semantic communication has made remarkable strides, where the transceivers utilizing local knowledge bases (KBs) to encode and recover semantic information. In this paper, we propose a universal weighted-KB (UW-KB) endowed with a sample confidence function for an end-to-end (E2E) task-unaware semantic communication system, where both the KB and semantic coding networks at the transceivers are incomplete in the initial stages. This intelligent UW-KB is shaped by receiver feedback during training, autonomously assigning weights to samples to mitigate biases in KB data, which significantly improves the efficiency of semantic coding networks. Simulation results demonstrate the effectiveness of our UW-KB in addressing KB data bias, providing valuable insights to bolster the robustness of task-unaware semantic communication systems.
Universal Weighted-Knowledge Bases for Task-Unaware Semantic Communication Systems
24.06.2024
1443132 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Quantization-Unaware Double JPEG Compression Detection
British Library Online Contents | 2016
|Some 75% of staff unaware of business continuity
British Library Online Contents | 2008
Pilots unaware of procedures risk being shot down
Online Contents | 2001
Sudan A310 crew unaware of tailwind. . Double airbridge collapse damages Cathay A330
Online Contents | 2013