scholarly journals On the Uncontrollability of Nonabelian Group Codes with Uncoded Group

2011 ◽  
Vol 2011 ◽  
pp. 1-12 ◽  
Author(s):  
Jorge Pedraza Arpasi
Keyword(s):  
Additive White Gaussian Noise ◽  
Error Correcting Codes ◽  
Phase Shift Keying ◽  
Group Code ◽  
Nonabelian Group ◽  
Group Codes ◽  
Transmission Errors ◽  
Finite State ◽  
Shift Keying ◽  
Binary Group

Error-correcting encoding is a mathematical manipulation of the information against transmission errors over noisy communications channels. One class of error-correcting codes is the so-calledgroup codes. Presently, there are many good binary group codes which are abelian. A group code is a family of bi-infinite sequences produced by a finite state machine (FSM) homomorphic encoder defined on the extension of two finite groups. As a set of sequences, a group code is a dynamical system and it is known that well-behaved dynamical systems must be necessarily controllable. Thus, a good group code must be controllable. In this paper, we work with group codes defined over nonabelian groups. This necessity on the encoder is because it has been shown that the capacity of an additive white Gaussian noise (AWGN) channel using abelian group codes is upper bounded by the capacity of the same channel using phase shift keying (PSK) modulation eventually with different energies per symbol. We will show that when the trellis section group is nonabelian and the input group of the encoder is a cyclic group with, elements, prime, then the group code produced by the encoder is noncontrollable.

Performance Comparison between DPSK and OQPSK modulation approaches in multi environments channels with Matlab Simulink models

2019 ◽  
Vol 7 (1) ◽  
pp. 30-39
Author(s):  
Fatima faydhe Al- Azzawi ◽  
Faeza Abas Abid ◽  
Zainab faydhe Al-Azzawi
Keyword(s):  
Phase Shift ◽  
Fading Channels ◽  
Additive White Gaussian Noise ◽  
Block Codes ◽  
Performance Comparison ◽  
Phase Shift Keying ◽  
Differential Phase Shift ◽  
Matlab Simulink ◽  
Communication Industry ◽  
Shift Keying

Phase shift keying modulation approaches are widely used in the communication industry. Differential phase shift keying (DPSK) and Offset Quadrature phase shift keying (OQPSK) schemes are chosen to be investigated is multi environment channels, where both systems are designed using MATLAB Simulink and tested. Cross talk and unity of signals generated from DPSK and OQPSK are examined using Cross-correlation and auto-correlation, respectively. In this research a proposed system included improvement in bit error rate (BER) of both systems in  the additive white Gaussian Noise (AWGN) channel, by using the convolutional and block codes, by increasing the ratio of energy in the specular component to the energy in the diffuse component (k) and  the diversity order BER in the fading channels will be improved in both systems.    

Design of Modified Minsum Decoder of LDPC Code in the Simplified Difference-Domain

2013 ◽  
Vol 385-386 ◽  
pp. 1576-1581
Author(s):  
Zhong Xun Wang ◽  
Xing Long Gao
Keyword(s):  
Belief Propagation ◽  
Additive White Gaussian Noise ◽  
Ldpc Code ◽  
Phase Shift Keying ◽  
Computation Complexity ◽  
Decoding Algorithm ◽  
Ldpc Decoding ◽  
Shift Keying ◽  
Log Domain ◽  
Binary Phase Shift Keying

In this paper, we propose the modified minsum decoding algorithm of LDPC(Low-Density Parity-Check) code in the simplified difference-domain on the basis of detailed analysis of LDPC decoding algorithm in difference-domain. The simulation indicates that the proposed decoding algorithm offers almost no performance degradation compared with the BP(Belief Propagation) decoding algorithm in log-domain and the decoding algorithm in difference-domain and offers better performance than minsum decoding algorithm in log-domain and greatly reduces the computation complexity in AWGN(Additive White Gaussian Noise) channel and under BPSK(Binary Phase Shift Keying) modulation.

scholarly journals Wiener's Loop Filter for PLL-Based Carrier Recovery of OQPSK and MSK-Type Modulations

2008 ◽  
Vol 2008 ◽  
pp. 1-4
Author(s):  
Arnaldo Spalvieri ◽  
Maurizio Magarini
Keyword(s):  
Phase Noise ◽  
Additive White Gaussian Noise ◽  
Phase Lock Loop ◽  
Phase Detector ◽  
Phase Shift Keying ◽  
Carrier Recovery ◽  
Loop Filter ◽  
Quadrature Phase ◽  
Shift Keying ◽  
The Mean

This letter considers carrier recovery for offset quadrature phase shift keying (OQPSK) and minimum shift keying-type (MSK-type) modulations based on phase-lock loop (PLL). The concern of the letter is the optimization of the loop filter of the PLL. The optimization is worked out in the light of Wiener's theory taking into account the phase noise affecting the incoming carrier, the additive white Gaussian noise that is present on the channel, and the self-noise produced by the phase detector. Delay in the loop, which may affect the numerical implementation of the PLL, is also considered. Closed-form expressions for the loop filter and for the mean-square error are given for the case where the phase noise is characterized as a first-order process.

scholarly journals A Coherent Performance for Noncoherent Wireless Systems Using AdaBoost Technique

2019 ◽  
Vol 9 (2) ◽  
pp. 256 ◽  
Author(s):  
Heba Gamal ◽  
Nour Eldin Ismail ◽  
M. R. M. Rizk ◽  
Mohamed E. Khedr ◽  
Moustafa H. Aly
Keyword(s):  
Phase Shift ◽  
Fading Channels ◽  
Additive White Gaussian Noise ◽  
Prediction Rule ◽  
Phase Shift Keying ◽  
Adaptive Boosting ◽  
Adaboost Algorithm ◽  
Modulation Techniques ◽  
Shift Keying ◽  
Precise Prediction

Boosting is a machine learning approach built upon the idea of producing a highly precise prediction rule by combining many relatively weak and imprecise rules. The Adaptive Boosting (AdaBoost) algorithm was the first practical boosting algorithm. It remains one of the most broadly used and studied, with applications in many fields. In this paper, the AdaBoost algorithm is utilized to improve the bit error rate (BER) of different modulation techniques. By feeding the noisy received signal into the AdaBoost algorithm, it is able to recover the transmitted data from the noisy signal. Consequently, it reconstructs the constellation diagram of the modulation technique. This is done by removing the noise that affects and changes the signal space of the data. As a result, AdaBoost shows an improvement in the BER of coherently detected binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK). The AdaBoost is next used to improve the BER of the noncoherent detection of the used modulation techniques. The improvement appears in the form of better results of the noncoherent simulated BER in comparison to that of the theoretical noncoherent BER. Therefore, the AdaBoost algorithm is able to achieve a coherent performance for the noncoherent system. The AdaBoost is simulated for several techniques in additive white Gaussian noise (AWGN) and Rayleigh fading channels so, as to verify the improving effect of the AdaBoost algorithm.

scholarly journals Capacity of 60 GHz Wireless Communications Based on QAM

2014 ◽  
Vol 2014 ◽  
pp. 1-5
Author(s):  
Jingjing Wang ◽  
Na Li ◽  
Wei Shi ◽  
Yangyang Ma ◽  
Xiulong Liang ◽  
...  
Keyword(s):  
Wireless Communications ◽  
Communication Technology ◽  
Gaussian Noise ◽  
Additive White Gaussian Noise ◽  
Radio Spectrum ◽  
60 Ghz ◽  
Phase Shift Keying ◽  
First Choice ◽  
Shift Keying ◽  
Maximum Transmit Power

With apparent advantages of the several GHz license-free spectrums, 10 W maximum transmit power, and so forth, 60 GHz wireless communication technology has become the first choice for Gbps level short-range wireless communications. This paper researches 60 GHz wireless communications over the additive white Gaussian noise channel. Channel capacity with quadrature amplitude modulation (QAM) is investigated for the unlicensed 59–64 GHz radio spectrum set aside by FCC. Moreover, the capacity with QAM is compared to that with phase shift keying (PSK). It is shown that QAM is capable of providing Gbps data rate and outperforms PSK especially when the modulation order is large. The results prove that QAM is an attractive scheme for 60 GHz wireless communications.

scholarly journals Calculation of symbol error rate in a telecommunication system based on amplitude modulation of many components

2021 ◽  
Vol 8 (2) ◽  
pp. 137-149
Author(s):  
I. V. Horbatyi ◽  
Keyword(s):  
Phase Shift ◽  
Error Rate ◽  
Amplitude Modulation ◽  
Additive White Gaussian Noise ◽  
Symbol Error Rate ◽  
Communication Line ◽  
Phase Shift Keying ◽  
Telecommunication System ◽  
Shift Keying ◽  
Arbitrary Location

The known analytical equations for calculating the symbol error rate (SER) in the M-ary telecommunication system are considered. The analytical equations for calculating SER in a telecommunication system based on M-ary amplitude modulation of many components (M-AMMC) and other varieties of amplitude-phase shift keying with arbitrary number and arbitrary location of signal points of the signal constellation, as well as under the action of additive white Gaussian noise in a communication line are proposed. According to the results of the research, it is found that the proposed equations allow us to increase the accuracy of calculating SER when using M-AMMC and other varieties of amplitude-phase shift keying compared to known analytical equations.

scholarly journals Performance of OFDM-Based WiMAX System Using Cyclic Prefix

2016 ◽  
Vol 1 ◽  
Author(s):  
Benriwati Maharmi
Keyword(s):  
Phase Shift ◽  
Orthogonal Frequency Division Multiplexing ◽  
High Speed ◽  
Additive White Gaussian Noise ◽  
Simulation Method ◽  
Cyclic Prefix ◽  
Phase Shift Keying ◽  
Broadband Wireless ◽  
Shift Keying ◽  
High Speed Data

The WiMax (Worldwide Interoperability for Microwave Access) is a technology in<strong> </strong>broadband wireless access, which employs OFDM (Orthogonal Frequency Division Multiplexing) as an alternative transmission to enable high speed data in communication system. This research aim is to analyze the performance system of the OFDM-Based WiMAX, which used the cyclic prefix. The model was designed in four schemes of simulation method, the BPSK (Binary Phase Shift Keying, QPSK (Quadrature Phase Shift Keying), 16 QAM (Quadrature Amplitude Modulation) and 64 QAM. Each scheme was investigated BER (Bit Error Rate) on AWGN (Additive White Gaussian Noise) channel and multipath Rayleigh fading channel, which had applied the cyclic prefix. By simulation of the cyclic prefix was produced the modulation measurement of the BPSK, QPSK, 16 and 64 QAM. The performance result of Eb/No 15 dB was obtained the BER of BPSK and QPSK of 1.11E-11, the BER of 16 QAM and 64 QAM of 8.69E-06 and 0.00333 respectively. Those results indicated much smaller BER value than EbNo 0 dB which BPSK and QPSK of 1 BER, 1.5 and 1.75 BER for 16 QAM and 64 QAM respectively. In conclusion, a higher value of EbNo, hence the BER value would be lower.

Improved SNR Estimation Technique for BPSK and QPSK Signals

2012 ◽  
Vol 239-240 ◽  
pp. 994-999
Author(s):  
Guang Zu Liu ◽  
Jian Xin Wang
Keyword(s):  
Phase Shift ◽  
Signal To Noise Ratio ◽  
Additive White Gaussian Noise ◽  
Estimation Accuracy ◽  
Estimation Technique ◽  
Phase Shift Keying ◽  
Low Snr ◽  
Mathematical Relation ◽  
Shift Keying ◽  
Binary Phase Shift Keying

To improve the estimation accuracy of non-data-aided (NDA) signal-to-noise ratio (SNR) estimators at low SNR value, A novel estimation technique for binary phase-shift keying and quadrature phase-shift keying signals in complex additive white Gaussian noise channel is proposed. The mathematical relation between SNR and the ratio of two simple statistical computations is derived, then SNR is determined by looking up a table. Its accuracy surpasses other NDA estimators, approaching closely to the Cramer-Rao lower bound at SNR > 5dB.

scholarly journals Performance Examination of OFDM Modulation Techniques in LTE 4G

2019 ◽  
Vol 9 (2) ◽  
pp. 3401-3404
Keyword(s):  
Phase Shift ◽  
Additive White Gaussian Noise ◽  
Phase Shift Keying ◽  
High Data ◽  
Modulation Techniques ◽  
Shift Keying ◽  
Modulation Methods ◽  
Performance Examination ◽  
Binary Phase Shift Keying

The digital modulation methods are being chosen in high data rate systems as Long Term Evolution (LTE) and LTE-A. Quadrature Phase Shift Keying (QPSK) and Binary Phase Shift Keying (BPSK) is the simplest form of the PSK with double carrying capacity when compare to the other traditional techniques in modulation. In conventional method the performance was analyzed in MIMO .In this paper proposed the performance analysis of BPSK and QPSK modulator and demodulator in LTE 4G system models under the Additive white Gaussian Noise (AWGN) and Rayleigh fading by comparing the Bit Error Rate (BER). From the analysis, compare to BPSK QPSK has good BER. Using the MATLAB Simulink tool Implementation is performed.

scholarly journals Classification of Digital Modulated COVID-19 Images in the Presence of Channel Noise Using 2D Convolutional Neural Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Rahim Khan ◽  
Qiang Yang ◽  
Ahsan Bin Tufail ◽  
Alam Noor ◽  
Yong-Kui Ma
Keyword(s):  
Deep Learning ◽  
Phase Shift ◽  
Data Augmentation ◽  
Comprehensive Evaluation ◽  
Additive White Gaussian Noise ◽  
Channel Noise ◽  
Phase Shift Keying ◽  
Shift Keying ◽  
Fully Connected

The wireless environment poses a significant challenge to the propagation of signals. Different effects such as multipath scattering, noise, degradation, distortion, attenuation, and fading affect the distribution of signals adversely. Deep learning techniques can be used to differentiate among different modulated signals for reliable detection in a communication system. This study aims at distinguishing COVID-19 disease images that have been modulated by different digital modulation schemes and are then passed through different noise channels and classified using deep learning models. We proposed a comprehensive evaluation of different 2D Convolutional Neural Network (CNN) architectures for the task of multiclass (24-classes) classification of modulated images in the presence of noise and fading. It is used to differentiate between images modulated through Binary Phase Shift Keying, Quadrature Phase Shift Keying, 16- and 64-Quadrature Amplitude Modulation and passed through Additive White Gaussian Noise, Rayleigh, and Rician channels. We obtained mixed results under different settings such as data augmentation, disharmony between batch normalization (BN), and dropout (DO), as well as lack of BN in the network. In this study, we found that the best performing model is a 2D-CNN model using disharmony between BN and DO techniques trained using 10-fold cross-validation (CV) with a small value of DO before softmax and after every convolution and fully connected layer along with BN layers in the presence of data augmentation, while the least performing model is the 2D-CNN model trained using 5-fold CV without augmentation.

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