LSTM-Based Adaptive Modulation and Coding for Satellite-to-Ground Communications

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.

PERFORMANCES OF ADAPTIVE MODULATION AND CODING IN SATELLITE MOBILE CHANNEL

Given that satellite mobile channel is a time-varying channel,Adaptive Modulation and Coding(AMC) was proposed to provide robust and spectrally efficient transmission over satellite mobile channel.Three different kinds of channel environment were considered in this paper:the urban area,the rural area,and the open space.Four combinations of modulation and coding were designed to meet reliable communication on time-varying channel,and spectral efficiency and system throughput of these three kinds of channel environment were simulated.Based on the simulation results,this paper analysed the results and compared the performances of AMC with non-AMC system in these three kinds of channel environment.At last,we come to the conclusions:a system with AMC can achieve higher spectral efficiency and better system throughput;and the spectral efficiency and system throughput of AMC system will be higher on better satellite mobile channel.

Adaptive Modulation and Coding Based on Fuzzy Logic Cognitive Engine

Adaptive modulation and coding( AMC) which depends on channel state information( CSI) can make the modulation and coding scheme( MCS) for the sender changed, and make the spectrum efficiency enhanced. The traditional method of AMC establishes a lookup table of MCSs at first,and then the sender chooses the proper MCS according to the CSI from feedback channel. However,this method is not suitable for frequency selective and fast fading channel. Thus, a method based on fuzzy logic cognitive engine is proposed in this paper. The type of channel is recognized by the fuzzy logic cognitive engine,then the MCSs are modified to suit for the channel type. The simulation results show that the proposed method is more suitable for frequency selective and fast fading channel. And it is more reliability under the condition of meeting the bit error rate( BER).

Research on Threshold Adjustment Algorithm in Adaptive Modulation and Coding

Adaptive Modulation and Coding （AMC） has gained a lot of attentions in the research of High Speed Downlink Packet Access （HSDPA）. The idea is to adapt the transmission to the fast changing channel conditions by the use of different Modulation and Coding Schemes （MCS）. This paper presents an adaptive AMC algorithm and introduces a theoretical analysis model in order to to investigate its throughput and Frame Error Rate （FER）. Subject to the given FER target, our numerical and link level simulation results both show that our algorithm outperforms other existing adaptive algorithms.

A Joint Rate Control and AMC Algorithm for Adaptive Transmission Systems

The traditional communication system is effectively designed for the worst-case channel state and it can not use the spectral efficiently over the time-varying multipath channel. In order to improve the spectral efficiency and ensure robust and spectrally-efficient transmission over the time-varying multipath channel,a joint rate control and adaptive modulation and coding ( AMC) algorithm for adaptive transmission systems is proposed in this paper. Firstly,the proposed algorithm can formulate a modulation and coding scheme ( MCS) switching table according to the offline simulation results and the target bit error rate ( BER) . Then,the optimal MCS is selected in MCS switching table according to the channel state information ( CSI) and then passes to the transmitter and receiver to implement. So the adaptive system which always uses the optimal MCS to transmit signals uses the spectral efficiently. The simulation results validate the proposed algorithm and show that under the premise of meeting the target BER,the adaptive system performing the proposed algorithm has a higher average spectral efficiency ( ASE) than that of the non-adaptive system.

MCS Selection Criteria Based on Performance Simulation for HSDPA

An adaptive modulation and coding (AMC) scheme integrated with multi-code transmission for high speed downlink packet access is presented and some modulation and coding scheme (MCS) selection criteria are proposed to maximize single user data rates. Based on link-level performance analysis, the MCS selection criteria are proposed with the constraints of QoS requirement, modulation level, channel coding rate and the number of available channelization codes. By allowing multiple transmission parameters changing, these criteria make the scheme more flexible to time-varying mobile channel with comparatively low complexity through a look-up table method. The AMC scheme is sensitive to the changes of channel condition and can save the channelization codes in an applicable way by applying these criteria.

A semi-blind joint data and channel estimation based receiver for meteor burst communication

According to the analysis of meteor burst communication (MBC) mechanism, a model of signal processing based on the structure of data frame is suggested for adaptive modulation and coding (AMC) of MBC system in this paper. There are two distinct modes of operation for signal processing: acquisition and tracking. The acquisition mode is a training period to initialize the channel estimation by frame header. The tracking mode is jointly to equalize payload data and to trace channel, where the principle of per-survivor processing (PSP) for maximum likelihood sequence detection (MLSD) is performed. A suboptimal method called D-PSP is adopted to save the computational time and memory size, which agrees with the slow-fading characteristic of meteor channel and makes the MLSD possible for adaptive modulation and coding of MBC system. Computer simulation results are included to support our development.

Switching Between Antenna Subset Selection and Quasi-Orthogonal Space-Time Block Code in Presence of Correlation

We address the problem of adaptive modulation and coding scheme(AMCS) for a multi-input multioutput(MIMO) system in presence of time-varying transmitting correlation.Antenna subset selection and quasiorthogonal space-time block code(QOSTBC) have different error performances with different signal-to-noise ratios(SNRs) and in different spatial correlation scenarios.The error performance can be improved by selecting an appropriate transmission scheme to adapt to various channel conditions.The maximum distance criterion is the simplest and very effective algorithm for the antenna subset selection without needs of complex calculation and channel state information at transmitter(CSIT).The minimum error performance criteria and the simplified linear decision strategy are developed for constant transmission rate traffic to select the optimal transmission scheme.It can dramatically decrease algorithm complexity for obtaining error probability according to the known quantities comparing with using instant CSIT.Simulation results show that,remarkable performances including low SNR and weak spatial correlation at the expense of simple calculation and almost no bandwidth loss by adopting AMCS can be achieved.The proposed AMCS improves robustness of slowly varying spatial correlated channels.

Pragmatic Physical Layer Abstraction Method Based on Bit-LLR-Wise Exponential Effective SNR Mapping for Bit Interleaved Coded Orthogonal Frequency Division Multiplexing System

In this paper, we analyze the physical layer abstraction for bit interleaved coded orthogonal frequency division multiplexing(BIC-OFDM) system from a parallel bit channel perspective. By combining the exponential effective SNR(signal-to-noise ratio) mapping(EESM) with the maximum a posteriori(MAP) algorithm, a bit LLR(log-likelihood ratio) wise EESM(BL-EESM) method is proposed. This method can abstract the link performance with high accuracy, especially for the case when channel estimation is imperfect. Afterward, the BL-EESM method is simplified by utilizing the non-linear quantization idea, which can reduce the times of exponential operation by two orders of magnitude at wide system bandwidth, yet shows little loss in accuracy. Our proposal can be applied to both system level simulations to save the time consumption and to practical terminals to facilitate the adaptive modulation and coding(AMC) procedure, bringing about throughput improvement at low hardware cost.