6G Cognitive Information Theory: A Mailbox Perspective

Abstract

With the rapid development of 5G communications, enhanced mobile broadband, massive machine type communications and ultra-reliable low latency communications are widely supported. However, a 5G communication system is still based on Shannon’s information theory, while the meaning and value of information itself are not taken into account in the process of transmission. Therefore, it is difficult to meet the requirements of intelligence, customization, and value transmission of 6G networks. In order to solve the above challenges, we propose a 6G mailbox theory, namely a cognitive information carrier to enable distributed algorithm embedding for intelligence networking. Based on Mailbox, a 6G network will form an intelligent agent with self-organization, self-learning, self-adaptation, and continuous evolution capabilities. With the intelligent agent, redundant transmission of data can be reduced while the value transmission of information can be improved. Then, the features of mailbox principle are introduced, including polarity, traceability, dynamics, convergence, figurability, and dependence. Furthermore, key technologies with which value transmission of information can be realized are introduced, including knowledge graph, distributed learning, and blockchain. Finally, we establish a cognitive communication system assisted by deep learning. The experimental results show that, compared with a traditional communication system, our communication system performs less data transmission quantity and error.

Making Sense of Meaning: A Survey on Metrics for Semantic and Goal-Oriented Communication

“…where MAX denotes the maximum possible number of image pixels and MSE represents the mean squared error between a reference image and a reconstructed image. The following conclusion can be drawn from the definition in (24): as the MSE between the transmitted image and the reconstructed image becomes smaller, the PSNR 20 gets larger, meaning a 20 PSNR can also be employed to assess the quality of video transmission since a video is made of several image frames [55].…”

“…To address this limitation, Netflix researchers adopted an ML-based model to design the metric VMAF [225], [226], which seeks to reflect the HVS in terms of video quality [226]. VMAF is similar 24 to VQM_VFD in spirit 23 PSNR_VFD is the PSNR calculated after the original clip has been VFD-matched to the processed clip [224]. 24 The main difference between VQM_VFD and VMAF is that the former extracts features at lower levels than the latter does, such as spatial and temporal gradients [226].…”

“…VMAF is similar 24 to VQM_VFD in spirit 23 PSNR_VFD is the PSNR calculated after the original clip has been VFD-matched to the processed clip [224]. 24 The main difference between VQM_VFD and VMAF is that the former extracts features at lower levels than the latter does, such as spatial and temporal gradients [226]. [226] and therefore discussed next.…”

Revolution or Evolution? Technical Requirements and Considerations towards 6G Mobile Communications

“…Meanwhile, in [115], a cognitive information transmission based on a 6G "mailbox theory" has been proposed. The mailbox theory requires a smaller amount of data for transmission while achieving higher reliability of decision-making using cognitive information transmission.…”

Digital medical education empowered by intelligent fabric space

“…Figure 2 shows the system architecture of the intelligent fabric space. When integrated with 6G intelligence networking technology [38], intelligent fabric space can renovate a wide range of future applications in terms of smart cities, smart living, medical care and education.…”