A. Rajesh

Amplitude normalization in blind modulation classification

The classification of digital modulation schemes plays an important role in communication intelligence (COMINT) and other related applications. The existing algorithms for modulation classification consider a semi-blind scenario, where certain signal parameters are assumed to be known. The pre-processing accuracy of signal parameters like the symbol rate, the center frequency, the carrier phase and the signal amplitude etc. has direct implication on classification. Here we address the case of model mismatch due to the amplitude uncertainty in maximum likelihood (ML) classification and propose a new approach to mitigate the situation. The method is based on the normalization of received signal amplitude using fuzzy clustering algorithm. Simulation results are presented to show the robustness of the algorithm for blind scenario. Concluding remarks are made with the scope for future work.

On the equivalence of the ACE and the EMD of a cycle for the ACE spectrum constrained LDPC codes

The Extrinsic Message Degree (EMD) of a cycle in the Tanner graph of a low density parity check (LDPC) code measures the connectivity of the cycle. As it is difficult to calculate the EMD, the Approximate EMD (ACE) is generally used. However, the ACE of a cycle is not always equal to its EMD. This paper presents some sufficient conditions for the equivalence of the ACE and the EMD of a cycle for the ACE spectrum constrained LDPC codes.

An improved technique to find the trapping sets of the irregular LDPC codes

This paper presents an efficient technique to find the dominant trapping sets of the irregular low density parity check (LDPC) codes. This technique is based on the approach of progressively finding the larger trapping sets from the smaller ones. The proposed technique is applied to some of the most commonly studied irregular codes and it is found to obtain more number of trapping sets compared to those of the techniques using the same approach and others as well.

Comparison of the Detrimental Effects of Trapping Sets in LDPC Codes

This paper presents a method to compare the detrimental effect of different trapping sets in the LDPC codes for an AWGN channel. The messages from the check nodes in the trapping set induced sub-graph are divided into two groups: one from the mis-satisfied check nodes and the other from the unsatisfied check nodes. The message densities for these two groups are computed to find out the joint probability of all the variable nodes in the trapping set being in error in the successive iterations. These joint probabilities are used to compare the detrimental effects of different trapping sets.

Performance of pulse shape modulation of UWB signals using composite hermite pulses

The existing literature shows that the transmitting and receiving antennas behave as a differentiators in the case of pulse based UWB radiations. This paper studies the effects of such antennas on the spectrally efficient composite Hermite pulses (CHPs) in pulse shape modulation (PSM) based UWB communications. The study shows that the CHPs are not much altered in terms of the power spectra and autocorrelation characteristics though the received pulses lose orthogonality. A simplified suboptimal structure for non-matched correlation detection is proposed. The received pulse is correlated with the locally generated Hermite functions and the resulting vector is projected to the columns of the coefficients matrix of the CHPs. This results in the correlations of the received pulse with all the CHPs. The CHP having the maximum absolute correlation with the received pulse is declared as the transmitted pulse.

A simplified counter approach to primary user emulation attacks from secondary user perspective

Spectrum sensing systems affected by Primary User Emulation Attacks (PUEAs) have recently gained focus in research. These attacks occur when a malicious unlicensed transmitter emulates the primary user (PU) signal to misdirect other secondary users (SUs). PUEAs are harmful to individual as well as cooperative spectrum sensing (CSS) systems. In this paper, a CSS model under PUEAs has been considered. A simple weighted combination scheme has been proposed for signal combination at the fusion center (FC). The calculation of weights is aimed to maximize the throughput of the SUs while keeping a limit on the interference to the PU. Simulation results prove the effectiveness of the proposed schemes.

An improved puncturing method for rate-compatible LDPC codes

This paper presents an improvement of a puncturing technique for rate-compatible low density parity check (LDPC) codes originally proposed by Asvadi and Banihashemi. In the original technique, the puncturing bits are selected by progressively reducing the search space according to a certain sequence of criteria. The last criterion is based on the ACE (approximate cycle extrinsic message degree) values of the short cycles present in the Tanner graph of the code. In this paper, we propose to substitute the last criterion with one which is based on the absorbing sets of the code. Simulation results show that this scheme improves the performance compared to the original and some other scheme available in the literature.

A linear model for the iterative decoding of random LDPC codes in the high SNR region

This paper presents a linear model for the sum-product decoding of random low-density parity-check (LDPC) codes, specifically in the high signal-to-noise ratio (SNR) region. The sum-product algorithm is first approximated as the min-sum algorithm and then a linear model is estimated for the latter. To formulate the model, the dominant trapping sets of the particular code are found. We consider a criterion based on the channel log-likelihood-ratio values to estimate the linear model. The bit error rate performance predicted by the linear model is compared with that obtained through importance sampling. This confirms that the linear model can accurately predict the performance of LDPC codes in the high SNR region.

A cycle-based rate-compatible puncturing technique for non-binary LDPC codes

This paper presents a cycle-based rate-compatible puncturing technique for non-binary (NB) low-density parity-check (LDPC) codes. The proposed puncturing technique is based on the connectivity of the short non-binary (NB) cycles present in the Tanner graph. The connectivity of a cycle is measured by the extrinsic message degree (EMD). The short cycles with low values of EMD degrade the performance of iterative decoders significantly. The proposed technique selects the variable nodes for puncturing by reckoning their involvements in the short NB cycles with a low EMD. Simulations in different contexts are performed to check the efficiency of the proposed technique.

Improved PSK classification using spectral correlation functions

This paper proposes an improved PSK classifier using the spectral correlation function(SCF). It shows why the SCF is unable to classify higher order PSK signals. A set of new features are extracted from SCF and used for classification as a solution to this problem. It also explains the differentiating capability of the newly extracted features.