Intelligent Decision Making System for Digital Modulation Scheme Classification in Software Radio Using Wavelet Transform and Higher Order Statistical Moments

Periasamy, P.; Madheswaran, M.

doi:10.1007/s11277-008-9621-z

Cited by 13 publications

(4 citation statements)

References 21 publications

(24 reference statements)

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“…DL method can avoid manual extraction of the signal features, but it needs a lot of data and adjustment time to adapt to different electromagnetic environments, which is difficult to achieve in practical applications. PR method mainly includes feature extraction, reduction of the feature space, and classification [9], which greatly reduces the computational burden while ensuring high classification accuracy, and is more widely used in practice. PR method mainly benefits from the extracted features.…”

Section: Automatic Modulation Classification (Amc) Is An Intermediate...mentioning

confidence: 99%

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A Two-Stage Hybrid Feature Selection Method of Communication Signals Based on Combined Scoring and Improved Binary Whale Optimization Algorithm

Liu

Zhao

et al. 2023

Preprint

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Communication signals have many modulation types in the current complex electromagnetic environment, so it is more and more difficult to recognize them accurately. Extracting features from different dimensions can describe the essence of the signals in different aspects and better distinguish various signal modulation formats. However, there may be features with poor anti-noise performance, irrelevant features and redundant features in the original high-dimensional feature set, which not only reduce the recognition probability of the signals but also make the feature selection space grow exponentially. Aiming at the problem of multi-dimensional feature selection of communication signals, this paper proposes a two-stage hybrid feature selection method based on combined scoring and improved binary whale optimization algorithm. In the first stage, the method uses the combined algorithm to initially filter the extracted signal features, and in the second stage, the improved binary whale optimization algorithm is used for further optimization. The results show that, compared with the original feature set, this method can increase the average recognition probability of the signals by up to 17%, and the feature reduction rate up to 81%. Besides, we prove that the proposed algorithm has certain generalization ability for different signal-to-noise ratio (SNR) and classifiers.

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Section: Automatic Modulation Classification (Amc) Is An Intermediate...mentioning

confidence: 99%

“…It is the second predatory behavior of WOA. As shown in(8), the process first calculates the distance between each whale position and the current optimal whale position, and then establishes(9) to simulate the whales'…”

mentioning

confidence: 99%

A Two-Stage Hybrid Feature Selection Method of Communication Signals Based on Combined Scoring and Improved Binary Whale Optimization Algorithm

Liu

Zhao

et al. 2023

Preprint

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“…In [72], the author analyzed the CWT instantaneous features (mean, variance, and central moment values) for recognizing M-ASK, M-PSK, M-FSK, M-QAM, OOK, and MSK. In [73], the histogram peaks in WT magnitude, mean, and HOM of normalized histogram were adopted as features for digital modulation classification. The wavelet variation coefficient difference and similarity measurement functions from statistics were used as the features to classify MASK, MFSK, MPSK, and MQAM [74].…”

Section: Transform Features For Mrmentioning

confidence: 99%

Performance of Feature-Based Techniques for Automatic Digital Modulation Recognition and Classification—A Review

et al. 2019

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The demand for bandwidth-critical applications has stimulated the research community not only to develop new ways of communication, but also to use the existing spectrum efficiently. Networks have become dynamic and heterogeneous. Receivers have received various signals that can be modulated differently. Automatic modulation classification (AMC) is a key procedure for present and next-generation communication networks, and facilitates the demodulation process at the receiver side. Under the presence of noise from the channel, the transmitter and receiver with its unknown parameters, such as carrier frequency, phase offset, signal power, and timing information, have become cumbersome because detecting the modulation scheme of the received signal is a complicated procedure. Two main methods, namely maximum likelihood functions and the signal statistical feature-based (FB) approach, are used for the automatic classification of modulated signals. In this study, a comprehensive survey of various modulation techniques based on FB approach is conducted. In this research, a number of basic features that are usually used in determining and discriminating modulation types were investigated. The classifier that was used in the discrimination process is studied in detail and compared to other types of classifiers to help the reader determine the limitations associated with the FB approach. Both classifiers and basic features were compared, and their advantages and disadvantages were investigated based on previous researches to determine the best type of classifier and the set of features in relation to each discrimination environment. This work serves as a guide for researchers of AMC to determine the suitable features and algorithms.

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“…BER is a unit less performance measure which is often expressed as a percentage (%). A pseudorandom data sequence (15) is used for the analysis in this design. The BER parameter represents the current operating BER of a specific modulation type and in this design the modulation scheme selected is M-PSK.…”

Section: Bit Error Rate (Ber)mentioning

confidence: 99%

LabVIEW Based Design Implementation of M-PSK Transceiver Using Multiple Forward Error Correction Coding Technique for Software Defined Radio Applications

Marriwala¹,

Sahu²,

Vohra³

2014

JEEE

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Software-Defined Radio (SDR) is an enabling technology which is useful in a wide range of areas within wireless systems. SDR offers a perfect solution to the problem of spectrum scarcity in wireless communication. With the significant increase in the demand for reliable, high data rate transmission these days, a different number of modulation techniques need to be adopted. The main objective of this paper is to design and analyze an SDR based M-Phase Shift Keying (PSK) transceiver using LabVIEW (Laboratory Virtual Instrumentation Engineering Workbench) and to measure the Bit Error Rate (BER) in the presence of Additive White Gaussian Noise (AWGN) introduced in the channel. Forward Error Correction (FEC) is used as a channel coding scheme in this paper. FEC codes are used where the re-transmission of the data is not feasible, thus redundant bits are added along with the message bits and transmitted through the channel. This paper describes the fundamental concept for the design & development of an SDR -based transceiver simulation model under PSK Scheme & analyses the performance of two Forward Error Correction channel coding algorithms namely the Convolution and the Turbo Codes. In this paper we have shown that how fast and effectively we can build a PSK transceiver for interactive Software Defined Radio. With the help of this design we are able to see and prove that data errors can be minimized using coding techniques, which in turn improves the Signal to noise ratio (SNR).

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Intelligent Decision Making System for Digital Modulation Scheme Classification in Software Radio Using Wavelet Transform and Higher Order Statistical Moments

Cited by 13 publications

References 21 publications

A Two-Stage Hybrid Feature Selection Method of Communication Signals Based on Combined Scoring and Improved Binary Whale Optimization Algorithm

A Two-Stage Hybrid Feature Selection Method of Communication Signals Based on Combined Scoring and Improved Binary Whale Optimization Algorithm

Performance of Feature-Based Techniques for Automatic Digital Modulation Recognition and Classification—A Review

LabVIEW Based Design Implementation of M-PSK Transceiver Using Multiple Forward Error Correction Coding Technique for Software Defined Radio Applications

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