Quadrature Amplitude Shift Keying Research Articles

Robust Automatic Modulation Classification Using Convolutional Deep Neural Network Based on Scalogram Information

This study proposed a two-stage method, which combines a convolutional neural network (CNN) with the continuous wavelet transform (CWT) for multiclass modulation classification. The modulation signals’ time-frequency information was first extracted using CWT as a data source. The convolutional neural network was fed input from 2D pictures. The second step included feeding the proposed algorithm the 2D time-frequency information it had obtained in order to classify the different kinds of modulations. Six different types of modulations, including amplitude-shift keying (ASK), phase-shift keying (PSK), frequency-shift keying (FSK), quadrature amplitude-shift keying (QASK), quadrature phase-shift keying (QPSK), and quadrature frequency-shift keying (QFSK), are automatically recognized using a new digital modulation classification model between 0 and 25 dB SNRs. Modulation types are used in satellite communication, underwater communication, and military communication. In comparison with earlier research, the recommended convolutional neural network learning model performs better in the presence of varying noise levels.

A novel demodulation structure for quadrate modulation signals using the segmentary neural network modelling

In digital communication, the baseband information signal is modulated by the high-frequency carrier to produce a passband signal and applied to the transmission line. QASK (quadrature amplitude-shift keying), QFSK (quadrature frequency-shift keying), and QPSK (quadrature phase-shift keying) modulations from Quadrate type digital modulations are used for high-speed communication in passband digital modulations. They are a widespread modulation for fast and easy data transmission, especially in wireless communication and modem devices. In these modulations, four separate carriers are used, and since each carrier represents 2 bits, the transmission rate doubles compared to conventional digital modulation. This study aims to obtain the baseband signal from quadrate type modulation signals. For this purpose, all 8-bit data between Decimal 0–255 were obtained in QASK, QFSK, and QPSK modulations and signal matrices were formed. The various SNR (signal to noise ratio) values of 5 dB-10 dB-15 dB-20 dB noise were added to these signals to examine the system performance during the modulated signal transmission. The generated signals were given to the demodulation system developed using different methods and tested. The best results were obtained in developed a segmentary NN (Neural Network). In this study, it was observed that modulation signal matrices were given directly to an ANN (Artificial Neural Network) and that the results could not be predicted with the application of noise matrices for testing. Then the modulation signals with the proposed method are divided into four parts. Each segment represents a two-bit piece of data. In the case of a column matrix, four parts were applied as input to the neural network model. In the output of ANN, the result matrix to be predicted is created. Each modulation signal applied to the network input was classified between 0 and 3 at the output. Modulation data-carrying 8 bits are applied to the network in 4 steps and classified. 4 separate classification data from the ANN output is converted back to 2-bit logic. Therefore, signals carrying 8 bits of data are obtained in 4 steps. After the formation of the ANN network, baseband digital signal estimation was performed quickly in 4 steps across each byte modulation signals under different noises coming into the network, and demodulation data was successfully achieved.

Deep long short-term memory networks-based automatic recognition of six different digital modulation types under varying noise conditions

In this paper, a new method based on deep learning has been proposed in order to recognize noise-digital modulation signals at varying noise levels automatically. The 8-bit data from six different modulations have been obtained by adding noise levels from 5 to 25 dB. The used digital modulation types are Amplitude Shift Keying, Frequency Shift Keying, Phase Shift Keying, Quadrature Amplitude Shift Keying, Quadrature Frequency Shift Keying, and Quadrature Phase Shift Keying. To recognize the noise-digital modulation signals automatically, a new deep long short-term memory networks (LSTMs) model has been proposed and then applied to these signals successfully. A significant advantage of the proposed system is that deep learning method has been trained and tested with raw digital modulation signals without applying any feature extraction from the signals. In this study, the noise modulation signals of 5–25 dB have been classified and compared with each other. The innovative aspect of the study is to classify the modulation with the LSTM method without dealing with the extraction of signal characteristics. Without noise, added digital modulation signals had been classified as the success rate of 97.22%, while with all noise-added signals have been classified as the success rate of 94.72% with deep LSTM model. The experimental results show that the proposed deep LSTM model has been achieved remarkable results in recognition of noised six different modulation signals with a fully end-to-end structure.

All-optical M-ary ASK signal demultiplexer based on a photonic analog-to-digital conversion

An all-optical M-ary amplitude shift keying (ASK) signal demultiplexer is proposed and demonstrated. It allowed us to seamlessly demultiplex a high bit-rate optical M-ary ASK signal into on-off keying (OOK) signals without O/E conversion. It is composed of multilevel thresholding using self-frequency shift and OOK signal generation using optical interconnection. A level identification signal is provided as a result of multilevel thresholding and it is fed to an optical interconnection circuit which can generate corresponding OOK signals. We demonstrate the quadrature ASK signal demultiplexing at 100 Gsymbol/s and its error free operation at 10 Gb/s.

Frequency-domain echo cancellation in digital multicarrier modulation systems

The data driven frequency-domain echo canceller (EC) for a multicarrier modulation system is considered. An EC in such a system has to deal with both the interchannel and intersymbol interference occurring in the echo signal. For this reason, the main disadvantage of the data driven EC structure is the large computational complexity. Here, the solution of the computational complexity problem is presented. It is based on assumption that in practice, interchannel interference has a limited range. The number of operations per symbol as a measure of the EC computational complexity is given. Simulation results present echo attenuation in the frequency-domain EC, operating in the orthogonally multiplexed quadrature amplitude-shift keying system. Modifications of the proposed EC structure and its computational complexity in the systems with pulse shaping are discussed.

Signal modelling and coding for linearly detectable CPM

The equivalence between continuous phase modulation (CPM) and offset quadrature amplitude-shift keying (OQPSK) which can be detected using linear receivers is considered, and a hierarchy of such schemes developed based on the degree to which the CPM schemes can be described with a coded offset quadrature amplitude-shift keyed modulation. The nature of the coding required to make the two schemes equivalent (exactly for some forms and approximately in general) is discussed, and the nature of the optimum linear receivers is developed showing that with an appropriate phase offset of carriers, the optimum linear receiver will be an inphase-quadrature receiver. The problem of designing trellis codes for these CPM schemes is considered and it is shown how optimum codes basedon Hamming distance can be transformed into codes for application to these CPM schemes. The results show that it is possible to apply a trellis code with a constraint length of v+1 as described by a Mealy model with 2v states and yet decode the signal using a Viterbi decoder involving only 2v-1 states.

On the self-noise in QASK decision-feedback carrier tracking loops

Quadrature amplitude-shift keying (QASK) is often used for transmitting two digital data streams in bandwidth-constrained communication systems. Previous analyses of the tracking performance of a decision-feedback carrier tracking loop, which can be used to provide a carrier reference for a QASK signal set, have neglected the effects of the self-noise in the derivation of the loop resonance. The authors incorporate the effects of the self-noise will only result in a conservative assessment of the system's performance, contrary to what might be expected. All results obtained are in closed form and can easily be evaluated numerically for performance prediction purposes. >

Universal Carrier Recovery Loop for QASK and PSK Signal Sets

A new carrier recovery loop which applies to quadrature amplitude shift keying (QASK) and phase shift keying (PSK) modulation schemes is presented. This loop is shown to provide significant advantages compared with those already used. Furthermore, the baseband processing of the demodulated signals allows an easy implementation, especially for high-speed digital modems. Both geometrical interpretation and theoretical justification using estimation criteria are provided. Finally, experimental results are reported.

Channel coding with multilevel/phase signals

A coding technique is described which improves error performance of synchronous data links without sacrificing data rate or requiring more bandwidth. This is achieved by channel coding with expanded sets of multilevel/phase signals in a manner which increases free Euclidean distance. Soft maximum--likelihood (ML) decoding using the Viterbi algorithm is assumed. Following a discussion of channel capacity, simple hand-designed trellis codes are presented for 8 phase-shift keying (PSK) and 16 quadrature amplitude-shift keying (QASK) modulation. These simple codes achieve coding gains in the order of 3-4 dB. It is then shown that the codes can be interpreted as binary convolutional codes with a of coded bits into channel signals, which we call mapping by set partitioning. Based on a new distance measure between binary code sequences which efficiently lower-bounds the Euclidean distance between the corresponding channel signal sequences, a search procedure for more powerful codes is developed. Codes with coding gains up to 6 dB are obtained for a variety of multilevel/phase modulation schemes. Simulation results are presented and an example of carrier-phase tracking is discussed.

Data-Derived Symbol Synchronization of MASK and QASK Signals

Much has been said in the literature with regard to the problem of establishing symbol synchronization in binary baseband digital communication systems. By comparison, the literature contains little information relating to the extraction of symbol sync from multilevel baseband data. With the recent interest in multilevel amplitude-shift keying (MASK) and quadrature amplitude-shift keying (QASK) as signaling techniques for multilevel digital communications systems, the problem of providing symbol synchronization in the receivers of such systems becomes paramount. This paper presents a technique for extracting symbol sync from an MASK or QASK signal which has been transmitted over an infinite bandwidth white Gaussian noise channel. The scheme is essentially a generalization of the data transition tracking loop (DTTL) which has heretofore been used in PSK systems. The performance of the loop is analyzed in terms of its mean-squared symbol sync jitter and its effects on the data detection process in MASK and QASK systems.

Decision-Directed Automatic Gain Control for MAPSK Systems

An automatic gain control (AGC) loop is presented for use with M -ary amplitude- and phase-shift keying (MAPSK) systems. The gain control amplifier is regulated by an error signal formed by the difference between the estimated amplitude level and the received amplitude level. The AGC performance is thus independent of the short-term average received signal energy. AGC loop analysis and simulation is presented for M -ary amplitude-shift keying (MASK) and quadrature amplitude-shift keying (QASK). The AGC is shown to have a negligible degradation on the symbol probability of error for most practical cases. A generalized AGC for an arbitrary MAPSK system is also presented.

Carrier Synchronization and Detection of QASK Signal Sets

A carrier regeneration loop which generates highly coherent quadrature reference signals for quadrature amplitude-shift keying (QASK) demodulation is presented. The loop employs the principle of decision feedback and has a structure analogous to a decision feedback loop for quadriphase signals suggested earlier in the literature. The error probabihty performance of QASK is computed in the presence of the noisy carrier reference signals provided by the above loop. It is demonstrated that when the ratio of data rate to loop bandwidth is 50 or greater, then for all practical purposes, ideal QASK error probability performance is achieved.