Paeiz Azmi

Sayed A. Hadei, Paeiz Azmi

This paper provides analytical performance of the low-complexity family of affine projection algorithms on the estimation of multipath Rayleigh fading channels in the presence of carrier frequency offsets (CFO) and random channel variations. Our analysis is based on the calculation of the error correlation matrix of the estimation, the mean-square weight error (MSWE) and the mean-square estimation error (MSE) parameters. The analysis does not use strong assumptions like small or large step-size, and explicit closed-form expressions for the MSE of estimation are obtained only from common hypotheses in wireless communication context. In this paper, the optimum stepsize parameters minimizing the MSE of estimation are analytically derived without any simplified assumptions. For the sake of comparison with other analytical approaches, we also investigate the performance of the introduced algorithms by the energy conservation relation. Likewise for exact performance analysis, we evaluate all the moment terms that appear in closed form expressions for the MSE of estimation. Simulations are conduced to corroborate the presented studies and show that the theoretical results agree well with the simulation results over non-stationary multipath Rayleigh fading channels.

Jafar Norolahi, Paeiz Azmi

In this study, we propose a novel machine learning based algorithm to improve the performance of beyond 5 generation (B5G) wireless communication system that is assisted by Orthogonal Frequency Division Multiplexing (OFDM) and Non-Orthogonal Multiple Access (NOMA) techniques. The non-linear soft margin support vector machine (SVM) problem is used to provide an automatic modulation classifier (AMC) and a signal power to noise and interference ratio (SINR) estimator. The estimation results of AMC and SINR are used to reassign the modulation type, codding rate, and transmit power through frames of eNode B connections. The AMC success rate versus SINR, total power consuming, and sum capacity are evaluated for OFDM-NOMA assisted 5G system. Results show improvement of success rate compared of some published method. Furthermore, the algorithm directly computes SINR after signal is detected by successive interference cancellation (SIC) and before any signal decoding. Moreover, because of the direct sense of physical channel, the presented algorithm can discount occupied symbols (overhead signaling) for channel quality information (CQI) in network communication signaling. The results also prove that the proposed algorithm reduces the total power consumption and increases the sum capacity through the eNode B connections. Simulation results in compare to other algorithms show more successful AMC, efficient SINR estimator, easier practical implantation, less overhead signaling, less power consumption, and more capacity achievement.

Jafar Norolahi, Paeiz Azmi

In this study, an algorithm to blind and automatic modulation classification has been proposed. It well benefits combined machine leaning and signal feature extraction to recognize diverse range of modulation in low signal power to noise ratio (SNR). The presented algorithm contains four. First, it advantages spectrum analyzing to branching modulated signal based on regular and irregular spectrum character. Seconds, a nonlinear soft margin support vector (NS SVM) problem is applied to received signal, and its symbols are classified to correct and incorrect (support vectors) symbols. The NS SVM employment leads to discounting in physical layer noise effect on modulated signal. After that, a k-center clustering can find center of each class. finally, in correlation function estimation of scatter diagram is correlated with pre-saved ideal scatter diagram of modulations. The correlation outcome is classification result. For more evaluation, success rate, performance, and complexity in compare to many published methods are provided. The simulation prove that the proposed algorithm can classified the modulated signal in less SNR. For example, it can recognize 4-QAM in SNR=-4.2 dB, and 4-FSK in SNR=2.1 dB with %99 success rate. Moreover, due to using of kernel function in dual problem of NS SVM and feature base function, the proposed algorithm has low complexity and simple implementation in practical issues.

Moslem Forouzesh, Paeiz Azmi, Ali Kuhestani

In this paper, we study the problem of secure transmission with covert requirement in untrusted relaying networks. Our considered system model consists of one source, one destination, one untrusted relay, and one Willie. The untrusted relay tries to extract the information signal, while the goal of Willie is to detect the presence of the information signal transmitted by the source, in the current time slot. To overcome these two attacks, we illustrate that the destination and the source should inject jamming signal to the network in phase I and phase II, respectively. Accordingly, the communication in our proposed system model is accomplished in two phases. In the first phase, when the source transmits its data to the untrusted relay the destination broadcasts its jamming signal. In the second phase, when the relay retransmits the received signal, the source transmits a jamming signal with one of its antennas. For this system model, we propose a power allocation strategy to maximize the instantaneous secrecy rate subject to satisfying the covert requirements in both of the phases. Since the proposed optimization problem is non-convex, we adopt the Successive Convex Approximation (SCA) approach to convert it to a convex optimization problem. Next, we extend our system model to a practical system model where there are multiple untrusted relays and multiple Willies under two scenarios of noncolluding Willies and colluding Willies. Our findings highlight that unlike the direct transmission scheme, the achievable secrecy rate of the proposed secure transmission scheme improve as the number of untrusted relays increases.

Moslem Forouzesh, Paeiz Azmi, Nader Mokari et al.

In this paper, we investigate the physical layer security in downlink of Power Domain Non Orthogonal Multiple Access based heterogeneous cellular network in presence of multiple eavesdroppers. Our aim is to maximize the sum secrecy rate of the network. To this end, we formulate joint subcarrier and power allocation optimization problems to increase sum secrecy rate. Moreover, we propose a novel scheme at which the eavesdroppers are prevented from doing Successive Interference Cancellation, while legitimate users are able to do it. In practical systems, availability of eavesdroppers Channel State Information is impractical, hence we consider two scenarios: 1 Perfect CSI of the eavesdroppers, 2 imperfect CSI of the eavesdroppers. Since the proposed optimization problems are nonconvex, we adopt the well known iterative algorithm called Alternative Search Method. In this algorithm, the optimization problems are converted to two subproblems, power allocation and subcarrier allocation. We solve the power allocation problem by the Successive Convex Approximation approach and solve the subcarrier allocation subproblem, by exploiting the Mesh Adaptive Direct Search algorithm. Moreover, in order to study the optimality gap of the proposed solution method, we apply the monotonic optimization method. Moreover, we evaluate the proposed scheme for secure massive connectivity in 5G networks. Numerical results highlight that the proposed scheme significantly improves the sum secrecy rate compared with the conventional case at which the eavesdroppers are able to apply SIC.

Moslem Forouzesh, Paeiz Azmi, Nader Mokari et al.

Information-theoretic secrecy, in particular the wiretap channel formulation, provides protection against interception of a message by adversary Eve and has been widely studied in the last two decades. In contrast, covert communications under an analogous formulation provides protection against even the detection of the presence of the message by an adversary, and it has drawn significant interest recently. These two security topics are generally applicable in different scenarios; however, here we explore what can be learned by studying them under a common framework. Under a similar but not identical mathematical formulation, we introduce power optimization problems for each of the secrecy and the covert communications scenario, and we exploit common aspects of the problems to employ similar tools in their respective optimizations. Moreover, due to the practical limitations, we assume only channel