Performance of the Adaptive Coding and Modulation(ACM) strongly depends on the retrieved Channel State Information(CSI),which can be obtained using the channel estimation techniques relying on pilot symbol transmissio...Performance of the Adaptive Coding and Modulation(ACM) strongly depends on the retrieved Channel State Information(CSI),which can be obtained using the channel estimation techniques relying on pilot symbol transmission.Earlier analysis of methods of pilot-aided channel estimation for ACM systems were relatively little.In this paper,we investigate the performance of CSI prediction using the Minimum Mean Square Error(MMSE)channel estimator for an ACM system.To solve the two problems of MMSE:high computational operations and oversimplified assumption,we then propose the Low-Complexity schemes(LC-MMSE and Recursion LC-MMSE(R-LC-MMSE)).Computational complexity and Mean Square Error(MSE) are presented to evaluate the efficiency of the proposed algorithm.Both analysis and numerical results show that LC-MMSE performs close to the wellknown MMSE estimator with much lower complexity and R-LC-MMSE improves the application of MMSE estimation to specific circumstances.展开更多
Satellite communication develops rapidly due to its global coverage and is unrestricted to the ground environment. However, compared with the traditional ground TCP/IP network, a satellite-to-ground link has a more ex...Satellite communication develops rapidly due to its global coverage and is unrestricted to the ground environment. However, compared with the traditional ground TCP/IP network, a satellite-to-ground link has a more extensive round trip time(RTT) and a higher packet loss rate,which takes more time in error recovery and wastes precious channel resources. Forward error correction(FEC) is a coding method that can alleviate bit error and packet loss, but how to achieve high throughput in the dynamic network environment is still a significant challenge. Inspired by the deep learning technique, this paper proposes a signal-to-noise ratio(SNR) based adaptive coding modulation method. This method can maximize channel utilization while ensuring communication quality and is suitable for satellite-to-ground communication scenarios where the channel state changes rapidly. We predict the SNR using the long short-term memory(LSTM) network that considers the past channel status and real-time global weather. Finally, we use the optimal matching rate(OMR) to evaluate the pros and cons of each method quantitatively. Extensive simulation results demonstrate that our proposed LSTM-based method outperforms the state-of-the-art prediction algorithms significantly in mean absolute error(MAE). Moreover, it leads to the least spectrum waste.展开更多
Error Estimating Code (EEC) is a new channel coding method to estimate the Bit Error Rate (BER) information of the transmitted sequence. However, the estimated BER is not precise enough if the practical value of BER i...Error Estimating Code (EEC) is a new channel coding method to estimate the Bit Error Rate (BER) information of the transmitted sequence. However, the estimated BER is not precise enough if the practical value of BER is high. A weighted EEC estimation method is proposed to improve the accuracy performance of BER estimation by classifying the raw estimation results into intervals and multiplying them by different coefficients separately. The applications of weighted EEC in modulation selection scheme and distributed video coding are discussed. Simulation results show that the EEC-based modulation selection method can achieve better performance at a cost of little redundancy and computation, and the EEC-based rate estimation method in distributed video coding can save the decoding time.展开更多
基金supported by the 2011 China Aerospace Science and Technology Foundationthe Certain Ministry Foundation under Grant No.20212HK03010
文摘Performance of the Adaptive Coding and Modulation(ACM) strongly depends on the retrieved Channel State Information(CSI),which can be obtained using the channel estimation techniques relying on pilot symbol transmission.Earlier analysis of methods of pilot-aided channel estimation for ACM systems were relatively little.In this paper,we investigate the performance of CSI prediction using the Minimum Mean Square Error(MMSE)channel estimator for an ACM system.To solve the two problems of MMSE:high computational operations and oversimplified assumption,we then propose the Low-Complexity schemes(LC-MMSE and Recursion LC-MMSE(R-LC-MMSE)).Computational complexity and Mean Square Error(MSE) are presented to evaluate the efficiency of the proposed algorithm.Both analysis and numerical results show that LC-MMSE performs close to the wellknown MMSE estimator with much lower complexity and R-LC-MMSE improves the application of MMSE estimation to specific circumstances.
基金supported by the National High Technology Research and Development Program of China (No. 2020YFB1806004)。
文摘Satellite communication develops rapidly due to its global coverage and is unrestricted to the ground environment. However, compared with the traditional ground TCP/IP network, a satellite-to-ground link has a more extensive round trip time(RTT) and a higher packet loss rate,which takes more time in error recovery and wastes precious channel resources. Forward error correction(FEC) is a coding method that can alleviate bit error and packet loss, but how to achieve high throughput in the dynamic network environment is still a significant challenge. Inspired by the deep learning technique, this paper proposes a signal-to-noise ratio(SNR) based adaptive coding modulation method. This method can maximize channel utilization while ensuring communication quality and is suitable for satellite-to-ground communication scenarios where the channel state changes rapidly. We predict the SNR using the long short-term memory(LSTM) network that considers the past channel status and real-time global weather. Finally, we use the optimal matching rate(OMR) to evaluate the pros and cons of each method quantitatively. Extensive simulation results demonstrate that our proposed LSTM-based method outperforms the state-of-the-art prediction algorithms significantly in mean absolute error(MAE). Moreover, it leads to the least spectrum waste.
基金supported bythe 111 Project under Grant No. B08004the major project of Ministry of Industry and Information Technology of the People's Republic of China under Grant No. 2010ZX03002-006China Fundamental Research Funds for the Central Universities
文摘Error Estimating Code (EEC) is a new channel coding method to estimate the Bit Error Rate (BER) information of the transmitted sequence. However, the estimated BER is not precise enough if the practical value of BER is high. A weighted EEC estimation method is proposed to improve the accuracy performance of BER estimation by classifying the raw estimation results into intervals and multiplying them by different coefficients separately. The applications of weighted EEC in modulation selection scheme and distributed video coding are discussed. Simulation results show that the EEC-based modulation selection method can achieve better performance at a cost of little redundancy and computation, and the EEC-based rate estimation method in distributed video coding can save the decoding time.
