scholarly journals Feature-Based Digital Modulation Recognition Using Compressive Sampling

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Zhuo Sun ◽  
Sese Wang ◽  
Xuantong Chen
Keyword(s):  
Signal To Noise Ratio ◽  
Phase Shift Keying ◽  
Modulation Recognition ◽  
Digital Modulation ◽  
Multiple Phase ◽  
Spectrum Detection ◽  
Main Challenge ◽  
Shift Keying ◽  
Compositional Feature ◽  
Feature Based

Compressive sensing theory can be applied to reconstruct the signal with far fewer measurements than what is usually considered necessary, while in many scenarios, such as spectrum detection and modulation recognition, we only expect to acquire useful characteristics rather than the original signals, where selecting the feature with sparsity becomes the main challenge. With the aim of digital modulation recognition, the paper mainly constructs two features which can be recovered directly from compressive samples. The two features are the spectrum of received data and its nonlinear transformation and the compositional feature of multiple high-order moments of the received data; both of them have desired sparsity required for reconstruction from subsamples. Recognition of multiple frequency shift keying, multiple phase shift keying, and multiple quadrature amplitude modulation are considered in our paper and implemented in a unified procedure. Simulation shows that the two identification features can work effectively in the digital modulation recognition, even at a relatively low signal-to-noise ratio.

A Novel Symbol Rate Estimation Algorithm for Phase Modulating Signals in Wireless Communications

2013 ◽  
Vol 443 ◽  
pp. 392-396
Author(s):  
Peng Zhou ◽  
Chi Sheng Li
Keyword(s):  
Signal To Noise Ratio ◽  
Estimation Algorithm ◽  
Frequency Resolution ◽  
Phase Shift Keying ◽  
Phase Jump ◽  
Rate Estimation ◽  
Awgn Channel ◽  
Symbol Rate ◽  
Shift Keying ◽  
Simulation Results

In this paper, we proposed a new symbol rate estimation algorithm for phase shift keying (PSK) and qua drawtube amplitude modulation (QAM) signals in AWGN channel First we constructe a delay-multiplied signal, from which we obtaine the modulated information. Then we calculated the instantaneous autocorrelation of the delay-multiplied signal to pick out the phase jump. To eliminate the restriction of frequency resolution in fast Fourier transform, we performed a Chirp-Z transform to find out the exact spectral line which represente the symbol rate of the signal to be analyzed. Compared with the existing algorithms, it is a simple solution that has a better performance and accuracy in low signal-to-noise-ratio channel conditions. Simulation results show that the probability of relative estimating deviation below 0.1% reaches 100% and the average and standard variance of absolute estimation deviation are at the magnitude of 10-2 when SNR is over 2dB.

Digital Modulation Recognition in Different Environments

2014 ◽  
Vol 1049-1050 ◽  
pp. 2084-2087 ◽  
Author(s):  
Rong Li
Keyword(s):  
Gaussian Noise ◽  
Signal To Noise Ratio ◽  
Automatic Recognition ◽  
Modulation Recognition ◽  
Signal To Noise ◽  
Digital Modulation ◽  
Multipath Interference ◽  
Modulation Signal ◽  
Simulation Results ◽  
Recognition Success

For the using of multi-modulation, the precondition of receiving and demodulating signal is to determine the type of the modulation, so automatic recognition of modulation signal has significant influence on the analysis of the signals. In this paper, digital modulation recognition is studied respectively in different environment of White Gaussian Noise (WGN), stationary interference and multipath interference. The simulation results show that the recognition success rate is the highest in stationary interference environment and the lowest in multipath interference environment with the same signal to noise ratio (SNR).

The Application of DFT Technology in Soft Demodulation of π/4-DQPSK Signals

2014 ◽  
Vol 644-650 ◽  
pp. 4439-4442
Author(s):  
Yan Jun Wu ◽  
Gang Fu ◽  
Peng Yu
Keyword(s):  
Simple Structure ◽  
Signal To Noise Ratio ◽  
Software Radio ◽  
Stable Region ◽  
Sampling Point ◽  
Receiver Design ◽  
Phase Shift Keying ◽  
Soft Demodulation ◽  
Shift Keying ◽  
Demodulation Method

Presented to the π / 4 differential quaternary phase shift keying signal (π/4-DQPSK) using the discrete Fourier transform (DFT) for software demodulation algorithm in consideration of the actual received waveform into transition to π/4-DQPSK District and stable region, and only the waveform sampling point DFT transform the region stable recovery decision. simulation gives the demodulation method to achieve the same differential demodulation relatively simple structure, and the anti-noise in the signal to noise ratio greater than 3dB better performance than the differential demodulation performance, expected the algorithm is applied π/4-DQPSK software radio receiver design.

scholarly journals A Novel Kernel for RBF Based Neural Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Wasim Aftab ◽  
Muhammad Moinuddin ◽  
Muhammad Shafique Shaikh
Keyword(s):  
Basis Function ◽  
Distance Measures ◽  
Gaussian Kernel ◽  
Phase Shift Keying ◽  
Multiple Phase ◽  
Cosine Measure ◽  
Symbol Detection ◽  
Shift Keying ◽  
Rbf Kernel ◽  
Artificial Neural Network Ann

Radial basis function (RBF) is well known to provide excellent performance in function approximation and pattern classification. The conventional RBF uses basis functions which rely on distance measures such as Gaussian kernel of Euclidean distance (ED) between feature vector and neuron’s center, and so forth. In this work, we introduce a novel RBF artificial neural network (ANN) where the basis function utilizes a linear combination of ED based Gaussian kernel and a cosine kernel where the cosine kernel computes the angle between feature and center vectors. Novelty of the proposed work relies on the fact that we have shown that there may be scenarios where the two feature vectors (FV) are more prominently distinguishable via the proposed cosine measure as compared to the conventional ED measure. We discuss adaptive symbol detection for multiple phase shift keying (MPSK) signals as a practical example to show where the angle information can be pivotal which in turn justifies our proposed RBF kernel. To corroborate our theoretical developments, we investigate the performance of the proposed RBF for the problems pertaining to three different domains. Our results show that the proposed RBF outperforms the conventional RBF by a remarkable margin.

scholarly journals Comparison of Bit Error Rate Performance of Various Digital Modulation Schemes over AWGN and Rayleigh Fading Channels using Simulink

2021 ◽  
Vol 9 (2) ◽  
pp. 7-16
Author(s):  
Md. Firoz Ahmed ◽  
Md. Faysal Ahmed ◽  
Abu Zafor Md. Touhidul Islam
Keyword(s):  
Fading Channels ◽  
Bit Error Rate ◽  
Rayleigh Fading ◽  
Rayleigh Fading Channels ◽  
Rate Performance ◽  
Phase Shift Keying ◽  
Digital Modulation ◽  
Modulation Techniques ◽  
Shift Keying ◽  
Modulation Schemes

Digital modulation increases information capacity, data security, and system availability while maintaining high communication quality. As a result, digital modulation techniques are in higher demand than analog modulation techniques due to their ability to transmit larger amounts of data. Amplitude Shift Keying (ASK), Frequency Shift Keying (FSK), Phase Shift Keying (PSK), Differential Phase Shift Keying (DPSK), and Quadrature Amplitude Modulation (QAM) are critical components of current communications systems development, particularly for broadband wireless communications. In this paper, the comparison of bit error rate performance of different modulation schemes (BPSK, QPSK, and16-QAM) and various equalization techniques such as constant modulus algorithm (CMA) and maximum likelihood sequence estimate (MLSE) for the AWGN and Rayleigh fading channels is analyzed using Simulink. BPSK outperforms QPSK and 16-QAM when compared to the other two digital modulation schemes. Among the three digital modulation schemes, BPSK is showing better performance as compared to QPSK and 16-QAM.

Automatic Modulation Identification of MPSK Signals Using Differential Signal and its Higher Order Cumulants

2011 ◽  
Vol 403-408 ◽  
pp. 2547-2551
Author(s):  
Zhan Hui Cai ◽  
Yuan Cheng Yao
Keyword(s):  
Signal To Noise Ratio ◽  
Modulation Classification ◽  
Phase Shift Keying ◽  
Eighth Order ◽  
Differential Signal ◽  
Automatic Modulation Classification ◽  
Shift Keying ◽  
Simulation Results ◽  
Intelligent Communication ◽  
Classification Probability

Automatic modulation classification plays a significant role in intelligent communication. A new method based on feature extraction is proposed for the recognition of M-ary Phase Shift Keying (MPSK) signals. As features, fourth and eighth order cumulants of the input samples and phase differential sequences were applied. It is shown that the cumulant-based features have robust anti-noise ability. Simulation results demonstrate that the correct classification probability (Pcc) with the proposed algorithm is higher than the existing approaches at low signal-to-noise ratio (SNR).

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