arXiv subjects

Paeiz Azmi

Publications and source records attributed to Paeiz Azmi.

25 records · Page 2Linked to original sources

arXiv2018

Compound Poisson Noise Sources in Diffusion-based Molecular Communication

Diffusion-based molecular communication (DMC) is one of the most promising approaches for realizing nano-scale communications for healthcare applications. The DMC systems in in-vivo environments may encounter biological entities that release molecules identical to the molecules used for signaling as part of their functionality. Such entities in the environment act as external noise sources from the DMC system's perspective. In this paper, the release of molecules by biological external noise sources is particularly modeled as a compound Poisson process. The impact of compound Poisson noise sources (CPNSs) on the performance of a point-to-point DMC system is investigated. To this end, the noise from the CPNS observed at the receiver is characterized. Considering a simple on-off keying (OOK) modulation and formulating symbol-by-symbol maximum likelihood (ML) detector, the performance of DMC system in the presence of the CPNS is analyzed. For special case of CPNS in high-rate regime, the noise received from the CPNS is approximated as a Poisson process whose rate is normally distributed. In this case, it is proved that a simple single-threshold detector (STD) is an optimal ML detector. Our results reveal that in general, adopting the conventional simple homogeneous Poisson noise model may lead to overly optimistic performance predictions, if a CPNS is present.

cs.IT↗

arXiv2018

Secure transmission with covert requirement in untrusted relaying networks

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.

cs.CR↗

arXiv2018

Robust Physical Layer Security for Power Domain Non-orthogonal Multiple Access-Based HetNets and HUDNs, SIC Avoidance at Eavesdroppers

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.

cs.CR↗

arXiv2018

Cross-Layer Energy Efficient Resource Allocation in PD-NOMA based H-CRANs: Implementation via GPU

In this paper, we propose a cross layer energy efficient resource allocation and remote radio head (RRH) selection algorithm for heterogeneous traffic in power domain - non-orthogonal multiple access (PD-NOMA) based heterogeneous cloud radio access networks (H-CRANs). The main aim is to maximize the EE of the elastic users subject to the average delay constraint of the streaming users and the constraints, RRH selection, subcarrier, transmit power and successive interference cancellation. The considered optimization problem is non-convex, NP-hard and intractable. To solve this problem, we transform the fractional objective function into a subtractive form. Then, we utilize successive convex approximation approach. Moreover, in order to increase the processing speed, we introduce a framework for accelerating the successive convex approximation for low complexity with the Lagrangian method on graphics processing unit. Furthermore, in order to show the optimality gap of the proposed successive convex approximation approach, we solve the proposed optimization problem by applying an optimal method based on the monotonic optimization. Studying different scenarios show that by using both PD-NOMA technique and H-CRAN, the system energy efficiency is improved.

eess.SP↗

arXiv2011

Performance Analysis of the Low-Complexity Adaptive Channel Estimation over Non-Stationary Multipath Rayleigh Fading Channels Under Carrier Frequency Offsets

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.

math.NA↗

arXiv2011

A Novel Adaptive Channel Equalization Method Using Variable Step-Size Partial Rank Algorithm

Recently a framework has been introduced within which a large number of classical and modern adaptive filter algorithms can be viewed as special cases. Variable Step-Size (VSS) normalized least mean square (VSSNLMS) and VSS Affine Projection Algorithms (VSSAPA) are two particular examples of the adaptive algorithms that can be covered by this generic adaptive filter. In this paper, we introduce a new VSS Partial Rank (VSSPR) adaptive algorithm based on the generic VSS adaptive filter and use it for channel equalization. The proposed algorithm performs very well in attenuating noise and inter-symbol interference (ISI) in comparison with the standard NLMS and the recently introduced AP algorithms.

cs.IT↗

arXiv2011

Low-Complexity Adaptive Channel Estimation over Multipath Rayleigh Fading Non-Stationary Channels Under CFO

In this paper, we propose novel low-complexity adaptive channel estimation techniques for mob ile wireless chan- n els in presence of Rayleigh fading, carrier frequency offsets (CFO) and random channel variations. We show that the selective p artial update of the estimated channel tap-weight vector offers a better trade-off between the performance and computational complexity, compared to the full update of the estimated channel tap-weight vector. We evaluate the mean-square weight error of th e proposed methods and demonstrate the usefulness of its via simulation studies.

cs.IT↗