In this paper,we give a systematic description of the 1st Wireless Communication Artificial Intelligence(AI)Competition(WAIC)which is hosted by IMT-2020(5G)Promotion Group 5G+AI Work Group.Firstly,the framework of ful...In this paper,we give a systematic description of the 1st Wireless Communication Artificial Intelligence(AI)Competition(WAIC)which is hosted by IMT-2020(5G)Promotion Group 5G+AI Work Group.Firstly,the framework of full channel state information(F-CSI)feedback problem and its corresponding channel dataset are provided.Then the enhancing schemes for DL-based F-CSI feedback including i)channel data analysis and preprocessing,ii)neural network design and iii)quantization enhancement are elaborated.The final competition results composed of different enhancing schemes are presented.Based on the valuable experience of 1stWAIC,we also list some challenges and potential study areas for the design of AI-based wireless communication systems.展开更多
In this paper,an interference cancellation based neural receiver for superimposed pilot(SIP)in multi-layer transmission is proposed,where the data and pilot are non-orthogonally superimposed in the same time-frequency...In this paper,an interference cancellation based neural receiver for superimposed pilot(SIP)in multi-layer transmission is proposed,where the data and pilot are non-orthogonally superimposed in the same time-frequency resource.Specifically,to deal with the intra-layer and inter-layer interference of SIP under multi-layer transmission,the interference cancellation with superimposed symbol aided channel estimation is leveraged in the neural receiver,accompanied by the pre-design of pilot code-division orthogonal mechanism at transmitter.In addition,to address the complexity issue for inter-vendor collaboration and the generalization problem in practical deployments,respectively,this paper also provides a fixed SIP(F-SIP)design based on constant pilot power ratio and scalable mechanisms for different modulation and coding schemes(MCSs)and transmission layers.Simulation results demonstrate the superiority of the proposed schemes on the performance of block error rate and throughput compared with existing counterparts.展开更多
文摘In this paper,we give a systematic description of the 1st Wireless Communication Artificial Intelligence(AI)Competition(WAIC)which is hosted by IMT-2020(5G)Promotion Group 5G+AI Work Group.Firstly,the framework of full channel state information(F-CSI)feedback problem and its corresponding channel dataset are provided.Then the enhancing schemes for DL-based F-CSI feedback including i)channel data analysis and preprocessing,ii)neural network design and iii)quantization enhancement are elaborated.The final competition results composed of different enhancing schemes are presented.Based on the valuable experience of 1stWAIC,we also list some challenges and potential study areas for the design of AI-based wireless communication systems.
文摘In this paper,an interference cancellation based neural receiver for superimposed pilot(SIP)in multi-layer transmission is proposed,where the data and pilot are non-orthogonally superimposed in the same time-frequency resource.Specifically,to deal with the intra-layer and inter-layer interference of SIP under multi-layer transmission,the interference cancellation with superimposed symbol aided channel estimation is leveraged in the neural receiver,accompanied by the pre-design of pilot code-division orthogonal mechanism at transmitter.In addition,to address the complexity issue for inter-vendor collaboration and the generalization problem in practical deployments,respectively,this paper also provides a fixed SIP(F-SIP)design based on constant pilot power ratio and scalable mechanisms for different modulation and coding schemes(MCSs)and transmission layers.Simulation results demonstrate the superiority of the proposed schemes on the performance of block error rate and throughput compared with existing counterparts.
