Abstract:Semantic communication, as a novel communication paradigm, has attracted the interest of many scholars, with multi-user, multi-input multi-output (MIMO) scenarios being one of the critical contexts. This paper presents a semantic importance-aware based communication system (SIA-SC) over MIMO Rayleigh fading channels. Combining the semantic symbols' inequality and the equivalent subchannels of MIMO channels based on Singular Value Decomposition (SVD) maximizes the end-to-end semantic performance through the new layer mapping method. For multi-user scenarios, a method of semantic interference cancellation is proposed. Furthermore, a new metric, namely semantic information distortion (SID), is established to unify the expressions of semantic performance, which is affected by channel bandwidth ratio (CBR) and signal-to-noise ratio (SNR). With the help of the proposed metric, we derived performance expressions and Semantic Outage Probability (SOP) of SIA-SC for Single-User Single-Input Single-Output (SU-SISO), Single-User MIMO (SU-MIMO), Multi-Users SISO (MU-MIMO) and Multi-Users MIMO (MU-MIMO) scenarios. Numerical experiments show that SIA-SC can significantly improve semantic performance across various scenarios.
Abstract:Multiple access technology is a key technology in various generations of wireless communication systems. As a potential multiple access technology for the next generation wireless communication systems, model division multiple access (MDMA) technology improves spectrum efficiency and feasibility regions. This implies that the MDMA scheme can achieve greater performance gains compared to traditional schemes. Relayassisted cooperative networks, as a infrastructure of wireless communication, can effectively utilize resources and improve performance when MDMA is applied. In this paper, a communication relay cooperative network based on MDMA in dissimilar rayleigh fading channels is proposed, which consists of two source nodes, any number of decode-and-forward (DF) relay nodes, and one destination node, as well as using the maximal ratio combining (MRC) at the destination to combine the signals received from the source and relays. By applying the state transition matrix (STM) and moment generating function (MGF), closed-form analytical solutions for outage probability and resource utilization efficiency are derived. Theoretical and simulation results are conducted to verify the validity of the theoretical analysis.
Abstract:Nowadays, the need for high-quality image reconstruction and restoration is more and more urgent. However, most image transmission systems may suffer from image quality degradation or transmission interruption in the face of interference such as channel noise and link fading. To solve this problem, a relay communication network for semantic image transmission based on shared feature extraction and hyperprior entropy compression (HEC) is proposed, where the shared feature extraction technology based on Pearson correlation is proposed to eliminate partial shared feature of extracted semantic latent feature. In addition, the HEC technology is used to resist the effect of channel noise and link fading and carried out respectively at the source node and the relay node. Experimental results demonstrate that compared with other recent research methods, the proposed system has lower transmission overhead and higher semantic image transmission performance. Particularly, under the same conditions, the multi-scale structural similarity (MS-SSIM) of this system is superior to the comparison method by approximately 0.2.