Non-orthogonal multiple access(NOMA), featuring high spectrum efficiency, massive connectivity and low latency, holds immense potential to be a novel multi-access technique in fifth-generation(5G) communication. Succe...Non-orthogonal multiple access(NOMA), featuring high spectrum efficiency, massive connectivity and low latency, holds immense potential to be a novel multi-access technique in fifth-generation(5G) communication. Successive interference cancellation(SIC) is proved to be an effective method to detect the NOMA signal by ordering the power of received signals and then decoding them. However, the error accumulation effect referred to as error propagation is an inevitable problem. In this paper,we propose a convolutional neural networks(CNNs) approach to restore the desired signal impaired by the multiple input multiple output(MIMO) channel. Especially in the uplink NOMA scenario,the proposed method can decode multiple users' information in a cluster instantaneously without any traditional communication signal processing steps. Simulation experiments are conducted in the Rayleigh channel and the results demonstrate that the error performance of the proposed learning system outperforms that of the classic SIC detection. Consequently, deep learning has disruptive potential to replace the conventional signal detection method.展开更多
目的分析我国外科护理学教学研究热点和发展趋势,为外科护理学教学领域研究提供参考。方法检索中国知网、万方、维普、中国生物医学文献、PubMed、Web of Science数据库中2011年—2021年收录的我国外科护理学教学相关文献,采用CiteSpace...目的分析我国外科护理学教学研究热点和发展趋势,为外科护理学教学领域研究提供参考。方法检索中国知网、万方、维普、中国生物医学文献、PubMed、Web of Science数据库中2011年—2021年收录的我国外科护理学教学相关文献,采用CiteSpace 6.1可视化软件进行文献分析。结果共纳入文献3863篇,其中中文文献3861篇,英文文献2篇。主要研究主题为教学方法改革、教学效果评价、临床实践教学,在线教学为新的研究方法。结论外科护理教育相关研究数量持续增长,但是体系化研究有所欠缺,建议从注重知识整合、丰富评价方式、加强医教协同、在线教学质控等方面开展更多研究。展开更多
基金supported by the National Natural Science Foundation of China (61471021)。
文摘Non-orthogonal multiple access(NOMA), featuring high spectrum efficiency, massive connectivity and low latency, holds immense potential to be a novel multi-access technique in fifth-generation(5G) communication. Successive interference cancellation(SIC) is proved to be an effective method to detect the NOMA signal by ordering the power of received signals and then decoding them. However, the error accumulation effect referred to as error propagation is an inevitable problem. In this paper,we propose a convolutional neural networks(CNNs) approach to restore the desired signal impaired by the multiple input multiple output(MIMO) channel. Especially in the uplink NOMA scenario,the proposed method can decode multiple users' information in a cluster instantaneously without any traditional communication signal processing steps. Simulation experiments are conducted in the Rayleigh channel and the results demonstrate that the error performance of the proposed learning system outperforms that of the classic SIC detection. Consequently, deep learning has disruptive potential to replace the conventional signal detection method.
文摘目的分析我国外科护理学教学研究热点和发展趋势,为外科护理学教学领域研究提供参考。方法检索中国知网、万方、维普、中国生物医学文献、PubMed、Web of Science数据库中2011年—2021年收录的我国外科护理学教学相关文献,采用CiteSpace 6.1可视化软件进行文献分析。结果共纳入文献3863篇,其中中文文献3861篇,英文文献2篇。主要研究主题为教学方法改革、教学效果评价、临床实践教学,在线教学为新的研究方法。结论外科护理教育相关研究数量持续增长,但是体系化研究有所欠缺,建议从注重知识整合、丰富评价方式、加强医教协同、在线教学质控等方面开展更多研究。
