Non-orthogonal multiple access(NOMA)is proved to be useful to satisfy the requirements of beyond 5th generation such as massive multi-user connection.Here we compare the performances of two NOMA schemes:low code rate ...Non-orthogonal multiple access(NOMA)is proved to be useful to satisfy the requirements of beyond 5th generation such as massive multi-user connection.Here we compare the performances of two NOMA schemes:low code rate spreading(LCRS)scheme and interleaver division multiple access(IDMA)scheme.It is found that LCRS is superior to IDMA when number of users is small due to coding gain achieved.While IDMA is preferred when number of users is high because repetition applied in IDMA can suppress multi-user interference effectively.And interleaver is important in IDMA for randomizing the interference.Also,this paper evaluates the impact of channel decoder.It is observed that Log-MAP decoder has much better performance than that of Max-Log-MAP when number of users is large.Thus,it is recommended to use Log-MAP decoder in NOMA in high user overloading case.We also compared the performance of NOMA by using different type of channel codes.We find that NOMA using specific convolutional code has a better performance than that of using specific LDPC code when number of users is high.展开更多
With the reduction in manufacturing and launch costs of low Earth orbit satellites and the advantages of large coverage and high data transmission rates,satellites have become an important part of data transmission in...With the reduction in manufacturing and launch costs of low Earth orbit satellites and the advantages of large coverage and high data transmission rates,satellites have become an important part of data transmission in air-ground networks.However,due to the factors such as geographical location and people’s living habits,the differences in user’demand for multimedia data will result in unbalanced network traffic,which may lead to network congestion and affect data transmission.In addition,in traditional satellite network transmission,the convergence of network information acquisition is slow and global network information cannot be collected in a fine-grained manner,which is not conducive to calculating optimal routes.The service quality requirements cannot be satisfied when multiple service requests are made.Based on the above,in this paper artificial intelligence technology is applied to the satellite network,and a software-defined network is used to obtain the global network information,perceive network traffic,develop comprehensive decisions online through reinforcement learning,and update the optimal routing strategy in real time.Simulation results show that the proposed reinforcement learning algorithm has good convergence performance and strong generalizability.Compared with traditional routing,the throughput is 8%higher,and the proposed method has load balancing characteristics.展开更多
Users, especially the non-expert users, commonly experience problems when connecting multiple devices with interoperability. While studies on multiple device connections are mostly concentrated on spontaneous device a...Users, especially the non-expert users, commonly experience problems when connecting multiple devices with interoperability. While studies on multiple device connections are mostly concentrated on spontaneous device association techniques with a focus on security aspects, the research on user interaction for device connection is still limited. More research into understanding people is needed for designers to devise usable techniques. This research applies the Research-through-Design method and studies the non-expert users＇ interactions in establishing wireless connections between devices. The ＂Learning from Examples＂ concept is adopted to develop a study focus line by learning from the expert users＇ interaction with devices. This focus line is then used for guiding researchers to explore the non-expert users＇ difficulties at each stage of the focus line. Finally, the Research-through-Design approach is used to understand the users＇ difficulties, gain insights to design problems and suggest usable solutions. When connecting a device, the user is required to manage not only the device＇s functionality but also the interaction between devices. Based on learning from failures, an important insight is found that the existing design approach to improve single-device interaction issues, such as improvements to graphical user interfaces or computer guidance, cannot help users to handle problems between multiple devices. This study finally proposes a desirable user-device interaction in which images of two devices function together with a system image to provide the user with feedback on the status of the connection, which allows them to infer any required actions.展开更多
基金This work has been performed in the Project“Key technologies for 5G transmission and networking for industry applications”supported by Department of Science and Technology of Guangdong Province(2018B010114001).
文摘Non-orthogonal multiple access(NOMA)is proved to be useful to satisfy the requirements of beyond 5th generation such as massive multi-user connection.Here we compare the performances of two NOMA schemes:low code rate spreading(LCRS)scheme and interleaver division multiple access(IDMA)scheme.It is found that LCRS is superior to IDMA when number of users is small due to coding gain achieved.While IDMA is preferred when number of users is high because repetition applied in IDMA can suppress multi-user interference effectively.And interleaver is important in IDMA for randomizing the interference.Also,this paper evaluates the impact of channel decoder.It is observed that Log-MAP decoder has much better performance than that of Max-Log-MAP when number of users is large.Thus,it is recommended to use Log-MAP decoder in NOMA in high user overloading case.We also compared the performance of NOMA by using different type of channel codes.We find that NOMA using specific convolutional code has a better performance than that of using specific LDPC code when number of users is high.
基金supported by the National Natural Science Foundation of China(No.U21A20451)the Science and Technology Planning Project of Jilin Province,China(No.20220101143JC)the China University Industry-Academia-Research Innovation Fund(No.2021FNA01003)。
文摘With the reduction in manufacturing and launch costs of low Earth orbit satellites and the advantages of large coverage and high data transmission rates,satellites have become an important part of data transmission in air-ground networks.However,due to the factors such as geographical location and people’s living habits,the differences in user’demand for multimedia data will result in unbalanced network traffic,which may lead to network congestion and affect data transmission.In addition,in traditional satellite network transmission,the convergence of network information acquisition is slow and global network information cannot be collected in a fine-grained manner,which is not conducive to calculating optimal routes.The service quality requirements cannot be satisfied when multiple service requests are made.Based on the above,in this paper artificial intelligence technology is applied to the satellite network,and a software-defined network is used to obtain the global network information,perceive network traffic,develop comprehensive decisions online through reinforcement learning,and update the optimal routing strategy in real time.Simulation results show that the proposed reinforcement learning algorithm has good convergence performance and strong generalizability.Compared with traditional routing,the throughput is 8%higher,and the proposed method has load balancing characteristics.
文摘Users, especially the non-expert users, commonly experience problems when connecting multiple devices with interoperability. While studies on multiple device connections are mostly concentrated on spontaneous device association techniques with a focus on security aspects, the research on user interaction for device connection is still limited. More research into understanding people is needed for designers to devise usable techniques. This research applies the Research-through-Design method and studies the non-expert users＇ interactions in establishing wireless connections between devices. The ＂Learning from Examples＂ concept is adopted to develop a study focus line by learning from the expert users＇ interaction with devices. This focus line is then used for guiding researchers to explore the non-expert users＇ difficulties at each stage of the focus line. Finally, the Research-through-Design approach is used to understand the users＇ difficulties, gain insights to design problems and suggest usable solutions. When connecting a device, the user is required to manage not only the device＇s functionality but also the interaction between devices. Based on learning from failures, an important insight is found that the existing design approach to improve single-device interaction issues, such as improvements to graphical user interfaces or computer guidance, cannot help users to handle problems between multiple devices. This study finally proposes a desirable user-device interaction in which images of two devices function together with a system image to provide the user with feedback on the status of the connection, which allows them to infer any required actions.
