Cluster Modulation: A Generalized Modulation Scheme Leading to NOMA or Adaptive Modulation

The need for higher data rate and higher systems capacity leads to several solutions including higher constellation size, spatial multiplexing, adaptive modulation and Non-Orthogonal Multiple Access (NOMA). Adaptive Modulation makes use of the user’s location from his base station, such that, closer users get bigger constellation size and hence higher data rate. A similar idea of adaptive modulation that makes use of the user’s locations is the NOMA technique. Here the base station transmits composite signals each for a different user at a different distance from the base station. The transmitted signal is formed by summing different user’s constellations with different weights. The closer the users the less average power constellation is used. This will allow the closer user to the base station to distinguish his constellation and others constellation. The far user will only distinguish his constellation and other user’s data will appear as a small interference added to his signal. In this paper, it is shown that the Adaptive modulation and the NOMA are special cases of the more general Cluster Modulation technique. Therefore, a general frame can be set to design both modulation schemes and better understanding is achieved. This leads to designing a multi-level NOMA and/or flexible adaptive modulation with combined channel coding.

Adaptive modulation in MIMO optical wireless communication systems

In the intensity modulation and direct detection （IM/DD） multiple-input multiple-output （MIMO） optical wireless communication systems, a direct-current-biased adaptive modulation scheme is proposed to guarantee the nonnegative property of transmitted signals, and the MIMO channel is converted to a parallel channel by using a singular value decomposition. Besides, a QR decomposition and successive interference cancellation based adaptive modulation scheme is proposed, and the MIMO channel can be simplified to a parallel channel under the bit error ratio （BER） target constraint. The power is optimally allocated to each sub-channel to maximize the data rate. Simulation results show that the proposed adaptive modulation schemes can effectively improve the transmission rate of the systems under the BER target and constant optical power constraints. The proposed adaptive modulation schemes make use of the multiplexing gain of the MIMO techniques, and can further improve the spectrum efficiency of optical wireless systems.

CSI Feedback-based CS for Underwater Acoustic Adaptive Modulation OFDM System with Channel Prediction

In this paper, we investigate the performance of adaptive modulation （AM） orthogonal frequency division multiplexing （OFDM） system in underwater acoustic （UWA） communications. The aim is to solve the problem of large feedback overhead for channel state information （CSI） in every subcarrier. A novel CSI feedback scheme is proposed based on the theory of compressed sensing （CS）. We propose a feedback from the receiver that only feedback the sparse channel parameters. Additionally, prediction of the channel state is proposed every several symbols to realize the AM in practice. We describe a linear channel prediction algorithm which is used in adaptive transmission. This system has been tested in the real underwater acoustic channel. The linear channel prediction makes the AM transmission techniques more feasible for acoustic channel communications. The simulation and experiment show that significant improvements can be obtained both in bit error rate （BER） and throughput in the AM scheme compared with the fixed Quadrature Phase Shift Keying （QPSK） modulation scheme. Moreover, the performance with standard CS outperforms the Discrete Cosine Transform （DCT） method.

Discrete-Rate Adaptive Modulation with Variable Threshold for Distributed Antenna System in the Presence of Imperfect CSI

Discrete-rate adaptive modulation （AM） scheme for distributed antenna system （DAS） with imperfect channel state information （CSI） is developed, and the corresponding performance is investigated in composite Rayleigh channel. Subject to target bit error rate （BER） constraint, an improved fixed switching threshold （FST） for the AM scheme is presented by means of tightly-approximate BER expression, and it can avoid the performance loss fxom conventional FST. Based on the imperfect CSI, the variable switching threshold （VST） is derived by utilizing the maximum a posteriori method. This VST includes the improved FST as a special case, and may lower the impact of estimation error on the performance. By the switching thresholds, the spectrum efficiency （SE） and average BER of the system are respectively derived, and resulting closed- form expressions are attained. With these expressions, the system performance can be effectively evaluated. Simulation results show that the derived theoretical SE and BER can match the simulations well. Moreover, the AM with the presented FST has higher SE than that with the conventional one, and the AM with VST can tolerate the large estimation error while maintaining the target BER.

Study of adaptive modulation and LDPC coding in multicarrier systems

An adaptive modulation （AM） algorithm is proposed and the application of the adapting algorithm together with low-density parity-check （LDPC） codes in multicarrier systems is investigated. The AM algorithm is based on minimizing the average bit error rate （BER） of systems, the combination of AM algorithm and LDPC codes with different code rates （half and three-fourths） are studied. The proposed AM algorithm with that of Fischer et al is compared. Simulation results show that the performance of the proposed AM algorithm is better than that of the Fischer＇s algorithm. The results also show that application of the proposed AM algorithm together with LDPC codes can greatly improve the performance of multicarrier systems. Results also show that the performance of the proposed algorithm is degraded with an increase in code rate when code length is the same.

Feedback Stabilization over Wireless Network Using Adaptive Coded Modulation

In this paper,we apply adaptive coded modulation (ACM) schemes to a wireless networked control system (WNCS) to improve the energy efficiency and increase the data rate over a fading channel.To capture the characteristics of varying rate, interference,and routing in wireless transmission channels,the concepts of equivalent delay (ED) and networked condition index (NCI) are introduced.Also,the analytic lower and upper bounds of EDs are obtained.Furthermore,we model the WNCS as a multicontroller switched system (MSS) under consideration of EDs and loss index in the wireless transmission.Sufficient stability condition of the closed-loop WNCS and corresponding dynamic state feedback controllers are derived in terms of linear matrix inequality (LMI). Numerical results show the validity and advantage of our proposed control strategies.

Low Complexity Minimum Mean Square Error Channel Estimation for Adaptive Coding and Modulation Systems

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.

Application of Bit Error Rate Information Based on Weighted Error Estimating Code

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.

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.

A novel adaptive classification scheme for digital modulations in satellite communication

To make the modulation classification system more suitable for signals in a wide range of signal to noise ratios （SNRs）, a novel adaptive modulation classification scheme is presented in this paper. Differ-ent from traditional schemes, the proposed scheme employs a new SNR estimation algorithm for small samples before modulation classification, which makes the modulation classifier work adaptively according to estimated SNRs. Furthermore, it uses three efficient features and support vector machines （SVM） in modulation classification. Computer simulation shows that the scheme can adaptively classify ten digital modulation types （i.e. 2ASK, 4ASK, 2FSK, 4FSK, 2PSK, 4PSK, 16QAM, TFM, π/4QPSK and OQPSK） at SNRS ranging from 0dB to 25dB and success rates are over 95% when SNR is not lower than 3dB. Accuracy, efficiency and simplicity of the proposed scheme are obviously improved, which make it more adaptive to engineering applications.

Proposal for a cross layer scheme for real-time wireless video

This paper focuses on the design of the cross layer between the video application layer and the MIMO physical layer. MIMO physical layer research has promised an enormous increase in the capacity of wireless communication systems. Also MIMO wireless systems operate under fading conditions where the channel faces arbitrary fluctuations. Since the wireless channel changes over each coherence period, the capacity of the wireless channel, given the power constraints, changes. Hence to make efficient use of the available capacity one needs to adapt the video bit rate. However it is impossible to adapt at the application layer as changing the parameters of the video takes more time than the coherence period of the channel. In this paper we address this problem through a novel solution and also investigate its performance through a simulation study.

Adaptive modulation MIMO system based on minimizing transmission power

Adaptive modulation (AM) is an effective technique to approach the theoretical bound of multi-input and multi-output (MIMO) channel. In most previous studies, the AM parameters were obtained by maximizing the transmission rate for a given total transmit power. In this paper, a novel AM-MIMO algorithm is presented, which is based on minimizing total transmit power when the link’s QoS requirements are given. By taking the QoS requirements into account directly, the proposed algorithm not only makes the system more flexible, but also makes the cross layer design of wireless network easier. At last, the numerical results of the proposed scheme are presented.

Simultaneous wireless information and power transfer with fixed and adaptive modulation

Activating Wireless Power Transfer (WPT) in Radio-Frequency (RF) to provide on-demand energy supply to widely deployed Internet of Everything devices is a key to the next-generation energy self-sustainable 6G network. However, Simultaneous Wireless Information and Power Transfer (SWIPT) in the same RF bands is challenging. The majority of previous studies compared SWIPT performance to Gaussian signaling with an infinite alphabet, which is impossible to implement in any realistic communication system. In contrast, we study the SWIPT system in a well-known Nakagami-m wireless fading channel using practical modulation techniques with finite alphabet. The attainable rate-energy-reliability tradeoff and the corresponding rationale are revealed for fixed modulation schemes. Furthermore, an adaptive modulation-based transceiver is provided for further expanding the attainable rate-energy-reliability region based on various SWIPT performances of different modulation schemes. The modulation switching thresholds and transmit power allocation at the SWIPT transmitter and the power splitting ratios at the SWIPT receiver are jointly optimized to maximize the attainable spectrum efficiency of wireless information transfer while satisfying the WPT requirement and the instantaneous and average BER constraints. Numerical results demonstrate the SWIPT performance of various fixed modulation schemes in different fading conditions. The advantage of the adaptive modulation-based SWIPT transceiver is validated.

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.

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.

A Low Complexity Algorithm for Subcarrier-and-Bit Allocation in OFDMA-Based LTE Systems

In this paper, we propose optimum and sub-optimum resource allocation and opportunistic scheduling solutions for orthogonal frequency division multiple access （OFDMA）-based multicellular systems. The applicability, complexity, and performance of the proposed algorithms are analyzed and numerically evaluated. In the initial setup, the fractional frequency reuse （FFR） technique for inter-cell interference cancellation is applied to classify the users into two groups, namely interior and exterior users. Adaptive modulation is then employed according to the channel state information （CSI） of each user to meet the symbol error rate （SER） requirement. There then, we develop subcarrier-and-bit allocation method, which maximizes the total system throughput subject to the constraints that each user has a minimum data rate requirement. The algorithm to achieve the optimum solution requires high computational complexity which hinders it from practicability. Toward this suboptimum method with the reduced to the order of O（NIO, the total number of subcarriers end, we complexity propose a extensively where N and K denote and users, respectively. Numerical results show that the proposed algorithm approaches the optimum solution, yet it enjoys the features of simplicity, dynamic cell configuration, adaptive subearrier-and-bit allocation, and spectral efficiency.

ADAPTIVE MODULATION AND POWER CONTROL FOR THROUGHPUT ENHANCEMENT IN COGNITIVE RADIOS

To regulate the transmit-power and enhance the total throughput, a novel Transmit Power Control Game (TPCG) algorithm and an adaptive Modulation TPCG (M-TPCG) algorithm which combine bandwidth allocation, adaptive modulation and transmit-power control based on Space Time Block Coding (STBC) OFDM-CDMA system are designed and a cross-layer framework of database sharing is proposed. Simulation results show that the TPCG algorithm can regulate their transmitter powers and enhance the total throughput effectively, M-TPCG algorithm can achieve maximal system throughput. The performance of the cognitive radio system is improved obviously.

MAKING FULL USE OF OUTDATED CHANNEL ESTIMATES FOR BLOCK BY BLOCK ADAPTIVE MODULATIONS

This paper explores the potential to use accurate but outdated channel estimates for adaptive modulation. The work is novel in that the research is conditioned on block by block adaptation. First,we define a new quantity,the Tolerable Average Use Delay (TAUD),which can indicate the ability of an adaptation scheme to tolerate the delay of channel estimation results. We find that for the variable-power schemes,TAUD is a constant and dependent on the target Bit Error Rate (BER),average power and Doppler frequency; while for the constant-power schemes,it depends on the ad-aptation block length as well. At last,we investigate the relation between the delay tolerating per-formance and the spectral efficiency and give the system design criterion. The delay tolerating per-formance is improved at the price of lower data rate.

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.

TIME-FREQUENCY 2-D LMS BASED LONG-RANGE CHANNEL PREDICTION FOR WIRELESS OFDM SYSTEMS

Adaptive modulation can optimize the spectrum efficiency and system performance with the channel state information achieved by the long-range channel prediction. To avoid re-estimating channel correlation function as the channel stationarity varies and to track the channel adaptively, LMS （Least-Mean-Square） based long-range channel prediction is discussed in the existing literature, but it needs long observation interval to reach the convergence. Given that all OFDM （Orthogonal Frequency Division Multiplexing） subcarriers have the identical time-domain correlation and stationarity during the same time interval, this paper proposed a 2-D LMS based predictor which updates the filter weights in both time and frequency domain. The proposed scheme can effectively decrease the observation intervals and significantly speed up the convergence than the conventional LMS and Parallel LMS （PLMS）. Complexity analysis and simulation results prove that the proposed scheme can improve the BER （Bit Error Rate） performance and spectrum efficiency with negligible complexity increase.