arXiv subjects

Mahtab Mirmohseni

Publications and source records attributed to Mahtab Mirmohseni.

At least 37 records · Page 2Linked to original sources

arXiv2024

A Novel Stochastic Model for IRS-Assisted Communication Systems Based on the Sum-Product of Nakagami-$m$ Random Variables

This paper presents exact formulas for the probability distribution function (PDF) and moment generating function (MGF) of the sum-product of statistically independent but not necessarily identically distributed (i.n.i.d.) Nakagami-$m$ random variables (RVs) in terms of Meijer's G-function. Additionally, exact series representations are also derived for the sum of double-Nakagami RVs, providing useful insights on the trade-off between accuracy and computational cost. Simple asymptotic analytical expressions are provided to gain further insight into the derived formula, and the achievable diversity order is obtained. The suggested statistical properties are proved to be a highly useful tool for modeling parallel cascaded Nakagami-$m$ fading channels. The application of these new results is illustrated by deriving exact expressions and simple tight upper bounds for the outage probability (OP) and average symbol error rate (ASER) of several binary and multilevel modulation signals in intelligent reflecting surfaces (IRSs)-assisted communication systems operating over Nakagami-$m$ fading channels. It is demonstrated that the new asymptotic expression is highly accurate and can be extended to encompass a wider range of scenarios. To validate the theoretical frameworks and formulations, Monte-Carlo simulation results are presented. Additionally, supplementary simulations are provided to compare the derived results with two common types of approximations available in the literature, namely the central limit theorem (CLT) and gamma distribution.

cs.IT↗

arXiv2023

Outage Tradeoff Analysis in a Downlink Integrated Sensing and Communication Network

This paper aims to analyze the stochastic performance of a multiple input multiple output (MIMO) integrated sensing and communication (ISAC) system in a downlink scenario, where a base station (BS) transmits a dual-functional radar-communication (DFRC) signal matrix, serving the purpose of transmitting communication data to the user while simultaneously sensing the angular location of a target. The channel between the BS and the user is modeled as a random channel with Rayleigh fading distribution, and the azimuth angle of the target is assumed to follow a uniform distribution. We use a maximum ratio transmission (MRT) beamformer to share resource between sensing and communication (S \& C) and observe the trade-off between them. We derive the approximate probability density function (PDF) of the signal-to-noise ratio (SNR) for both the user and the target. Subsequently, leveraging the obtained PDF, we derive the expressions for the user's rate outage probability (OP), as well as the OP for the Cramer-Rao lower bound (CRLB) of the angle of arrival (AOA). In our numerical results, we demonstrate the trade-off between S \& C, confirmed with simulations.

cs.IT↗

arXiv2022

Abnormality Detection and Localization Schemes using Molecular Communication Systems: A Survey

Abnormality detection and localization (ADL) have been studied widely in wireless sensor networks (WSNs) literature, where the sensors use electromagnetic waves for communication. Molecular communication (MC) has been introduced as an alternative approach for ADL in particular areas such as healthcare, being able to tackle the shortcomings of conventional WSNs, such as invasiveness, bio-incompatibility, and high energy consumption. In this paper, we introduce a general framework for MC-based ADL, which consists of multiple tiers for sensing the abnormality and communication between different agents, including the sensors, the fusion center (FC), the gateway (GW), and the external node (e.g., a local cloud), and describe each tier and the agents in this framework. We classify and explain different abnormality recognition methods, the functional units of the sensors, and different sensor features. Further, we describe different types of interfaces required for converting the internal and external signals at the FC and GW. Moreover, we present a unified channel model for the sensing and communication links. We categorize the MC-based abnormality detection schemes based on the sensor mobility, cooperative detection, and cooperative sensing/activation. We also classify the localization approaches based on the sensor mobility and propulsion mechanisms and present a general framework for the externally-controllable localization systems. Finally, we present some challenges and future research directions to realize and develop MC-based systems for ADL. The important challenges in the MC-based systems lie in four main directions as implementation, system design, modeling, and methods, which need considerable attention from multidisciplinary perspectives.

cs.IT↗

arXiv2022

IRS-User Association in IRS-Aided MISO Wireless Networks: Convex Optimization and Machine Learning Approaches

This paper concentrates on the problem of associating an intelligent reflecting surface (IRS) to multiple users in a multiple-input single-output (MISO) downlink wireless communication network. The main objective of the paper is to maximize the sum-rate of all users by solving the joint optimization problem of the IRS-user association, IRS reflection, and BS beamforming, formulated as a non-convex mixed-integer optimization problem. The variable separation and relaxation are used to transform the problem into three convex sub-problems, which are alternatively solved through the convex optimization (CO) method. The major drawback of the proposed CO-based algorithm is high computational complexity. Thus, we make use of machine learning (ML) to tackle this problem. To this end, first, we convert the optimization problem into a regression problem. Then, we solve it with feed-forward neural networks (FNNs), trained by CO-based generated data. Simulation results show that the proposed ML-based algorithm has a performance equivalent to the CO-based algorithm, but with less computation complexity due to its offline training procedure.

eess.SP↗

arXiv2022

Physical Layer Security in Random NOMA-Enabled Heterogeneous Networks

The performance of physical layer secrecy approach in non-orthogonal multiple access (NOMA)-enabled heterogeneous networks (HetNets) is analyzed in this paper. A $K$-tier multi-cell HetNet is considered, comprising NOMA adopted in all tiers. The base stations, legitimate users (in a two-user NOMA setup), and passive eavesdroppers, all with single-antenna, are randomly distributed. Assuming independent Poisson point processes for node distribution, stochastic geometry approaches are exploited to characterize the ergodic secrecy rate. A lower bound on the ergodic secrecy rate along with closed-form expressions for the lower bound on the ergodic rates of the legitimate users in a special case are derived. Moreover, simpler expressions for the ergodic secrecy rate are obtained in the interference-limited regime with vanishing noise variance. The effect of multi-tier technology, NOMA, and physical layer secrecy are investigated using numerical results. The results reveal that applying HetNet to a secure multi-cell NOMA system improves the spectrum efficiency performance.

cs.IT↗

arXiv2022

Fundamental Limits of Private User Authentication

Most of the security services in the connected world of cyber-physical systems necessitate authenticating a large number of nodes privately. In this paper, the private authentication problem is considered which consists of a certificate authority, a verifier (or some verifiers), many legitimate users (provers), and an arbitrary number of attackers. Each legitimate user wants to be authenticated (using his personal key) by the verifier(s), while simultaneously staying completely anonymous (even to the verifier). On the other hand, an attacker must fail to be authenticated. We analyze this problem from an information-theoretical perspective and propose a general interactive information-theoretic model for the problem. As a metric to measure the reliability, we consider the normalized total key rate whose maximization has a trade-off with establishing privacy. The problem is considered in two different scenarios: single-server scenario (only one verifier is considered, which all the provers are connected to) and multi-server scenario ($N$ verifiers are assumed, where each verifier is connected to a subset of users). For both scenarios, two regimes are considered: finite size regime (i.e., the variables are elements of a finite field) and asymptotic regime (i.e., the variables are considered to have large enough length). We propose achievable schemes that satisfy the completeness, soundness, and privacy properties in both single-server and multi-server scenarios in all cases. In the finite size regime, the main idea is to generate the authentication keys according to a secret sharing scheme. We show that the proposed scheme in the special case of multi-server authentication in the finite size regime is optimal. In the asymptotic regime, we use a random binning based scheme that relies on the joint typicality to generate the authentication keys.

cs.IT↗

arXiv2022

Interference Alignment Using Reaction in Molecular Interference Channels

Co-channel interference (CCI) is a performance limiting factor in molecular communication (MC) systems with shared medium. Interference alignment (IA) is a promising scheme to mitigate CCI in traditional communication systems. Due to the signal-dependent noise in MC systems, the traditional IA schemes are less useful in MC systems. In this paper, we propose a novel IA scheme in molecular interference channels (IFCs), based on the choice of releasing/sampling times. To cancel the aligned interference signals and reduce the signal dependent noise, we use molecular reaction in the proposed IA scheme. We obtain the feasible region for the releasing/sampling times in the proposed scheme. Further, we investigate the error performance of the proposed scheme. Our results show that the proposed IA scheme using reaction improves the performance significantly.\blfootnote{This work was supported in part by the Iran National Science Foundation (INSF) Research Grant on Nano-Network Communications and in part by the Research Center of Sharif University of Technology.

cs.IT↗

arXiv2022

Joint Sensing, Communication and Localization of a Silent Abnormality Using Molecular Diffusion

In this paper, we propose a molecular communication system to localize an abnormality in a diffusion based medium. We consider a general setup to perform joint sensing, communication and localization. This setup consists of three types of devices, each for a different task: mobile sensors for navigation and molecule releasing (for communication), fusion centers (FC)s for sampling, amplifying and forwarding the signal, and a gateway for making decision or exchanging the information with an external device. The sensors move randomly in the environment to reach the abnormality. We consider both collaborative and non-collaborative sensors that simultaneously release their molecules to the FCs when the number of activated sensors or the moving time reach a certain threshold, respectively. The FCs amplify the received signal and forward it to the gateway for decision making using either an ideal or a noisy communication channel. A practical application of the proposed model is drug delivery in a tissue of human body, in order to guide the nanomachine bound drug to the exact location. The decision rules and probabilities of error are obtained for two considered sensors types in both ideal and noisy communication channels.

eess.SP↗

arXiv2022

Distributed Attribute-based Private Access Control

In attribute-based access control, users with certain verified attributes will gain access to some particular data. Concerning with privacy of the users' attributes, we study the problem of distributed attribute-based private access control (DAPAC) with multiple authorities, where each authority will learn and verify only one of the attributes. To investigate its fundamental limits, we introduce an information theoretic DAPAC framework, with $N \in \mathbb{N}$, $N\geq 2$, replicated non-colluding servers (authorities) and some users. Each user has an attribute vector $\mathbf{v^*}=(v_1^*, ..., v_N^*)$ of dimension $N$ and is eligible to retrieve a message $W^{\mathbf{v}^*}$, available in all servers. Each server $n\in [N]$ is able to only observe and verify the $n$'th attribute of a user. In response, it sends a function of its data to the user. The system must satisfy the following conditions: (1) Correctness: the user with attribute vector $\mathbf{v^*}$ is able to retrieve his intended message $W^{\mathbf{v}^*}$ from the servers' response, (2) Data Secrecy: the user will not learn anything about the other messages, (3) Attribute Privacy: each Server~$n$ learns nothing beyond attribute $n$ of the user. The capacity of the DAPAC is defined as the ratio of the file size and the aggregated size of the responses, maximized over all feasible schemes. We obtain a lower bound on the capacity of this problem by proposing an achievable algorithm with rate $\frac{1}{2K}$, where $K$ is the size of the alphabet of each attribute.

cs.IT↗

arXiv2022

Privacy-aware Distributed Hypothesis Testing in Gray-Wyner Network with Side Information

The problem of distributed binary hypothesis testing in the Gray-Wyner network with side information is studied in this paper. An observer has access to a discrete memoryless and stationary source and describes its observation to two detectors via one common and two private channels. The channels are considered error-free but rate-limited. Each detector also has access to its own discrete memoryless and stationary source, i.e., the side information. The goal is to perform two distinct binary hypothesis testings on the joint distribution of observations at detectors. Additionally, the observer aims to keep a correlated latent source private against the detectors. Equivocation is used as the measure of the privacy preserved for the latent source. An achievable inner bound is derived for the general case by introducing a non-asymptotic account of the output statistics of the random binning.

cs.IT↗

arXiv2021

Achievable Rates for Binary Two-hop Channel with Energy Harvesting Relay and Finite Battery

We study the problem of joint information and energy transfer in a binary two-hop channel with an energy harvesting relay. We consider a finite battery size at the relay and energy loss in transmitting energy. In other words, to be able to send an energy-contained symbol, the relay must receive multiple energy-contained symbols. Thus, we face a kind of channel with memory. We model the energy saved in the battery as the channel state with the challenge that the receiver does not know the channel state. We propose two different achievable schemes, the first one is based on state-dependent superposition coding and the second one is based on the equivalent timing channel approach. Both of our schemes are based on block Markov coding and backward decoding techniques. Due to these two approaches, we find achievable rates with a single-letter expression for the model.

cs.IT↗

arXiv2021

On Achievable Degrees of Freedom for the Frequency-Selective K-User Interference Channel in the Presence of an Instantaneous Relay

In this paper, we study the degrees of freedom (DoF) of the frequency-selective K-user interference channel in the presence of an instantaneous relay (IR) with multiple receive and transmit antennas. We investigate two scenarios based on the IR antennas' cooperation ability. First, we assume that the IR receive and transmit antennas can coordinate with each other, where the transmitted signal of each transmit antenna can depend on the received signals of all receive antennas, and we derive an achievable DoF for this model. In our interference alignment scheme, we divide receivers into two groups, called clean and dirty receivers. We design our scheme such that a part of the message of clean receivers can be demultiplexed at the IR. Thus, the IR can use these message streams for interference cancelation at the clean receivers. Next, we consider an IR, whose antennas do not have coordination with each other, where the transmitted signal of each transmit antenna only depends on the received signal of its corresponding receive antenna, and we derive an achievable DoF for it. We show that the achievable DoF decreases considerably compared with the coordinated case. In both of these models, our schemes achieve the maximum K DoFs, if the number of transmit and receive antennas is more than a finite threshold.

cs.IT↗

arXiv2021

Theoretical Concept Study of Cooperative Abnormality Detection and Localization in Fluidic-Medium Molecular Communication

In this paper, we propose a theoretical framework for cooperative abnormality detection and localization systems by exploiting molecular communication setup. The system consists of mobile sensors in a fluidic medium, which are injected into the medium to search the environment for abnormality. Some fusion centers (FC) are placed at specific locations in the medium, which absorb all sensors arrived at their locations, and by observing its state, each FC decides on the abnormality existence and/or its location. To reduce the effects of sensor imperfection, we propose a scheme where the sensors release some molecules (i.e., markers) into the medium after they sense an abnormality. If the goal is abnormality detection, the released molecules are used to cooperatively activate other sensors. If the goal is abnormality localization, the released molecules are used by the FCs to determine the location. In our model, both sensors' imperfection and markers background noise are taken into account. For the detection phase, we consider two sensor types based on their activation strategy by markers. To make the analysis tractable, we assume some ideal assumptions for the sensors' model. We investigate the related binary hypothesis testing problem and obtain the probabilities of false alarm and miss-detection. It is shown that using sensors with the ability of cooperatively activating each other can significantly improve the detection performance in terms of probability of error. For the localization phase, we consider two types of FCs based on their capability in reading sensors' storage levels. We study their performance and obtain the optimal and sub-optimal decision schemes and also the probability of localization error for both perfect and imperfect sensing regimes.

eess.SP↗

arXiv2021

The Capacity Region of Distributed Multi-User Secret Sharing

In this paper, we study the problem of distributed multi-user secret sharing, including a trusted master node, $N\in \mathbb{N}$ storage nodes, and $K$ users, where each user has access to the contents of a subset of storage nodes. Each user has an independent secret message with certain rate, defined as the size of the message normalized by the size of a storage node. Having access to the secret messages, the trusted master node places encoded shares in the storage nodes, such that (i) each user can recover its own message from the content of the storage nodes that it has access to, (ii) each user cannot gain any information about the message of any other user. We characterize the capacity region of the distributed multi-user secret sharing, defined as the set of all achievable rate tuples, subject to the correctness and privacy constraints. In the achievable scheme, for each user, the master node forms a polynomial with the degree equal to the number of its accessible storage nodes minus one, where the value of this polynomial at certain points are stored as the encoded shares. The message of that user is embedded in some of the coefficients of the polynomial. The remaining coefficients are determined such that the content of each storage node serves as the encoded shares for all users that have access to that storage node.

cs.IT↗

arXiv2021

On Molecular Flow Velocity Meters

Flow velocity is an important characteristic of the fluidic mediums. In this paper, we introduce a molecular based flow velocity meter consisting of a molecule releasing node and a receiver that counts these molecules. We consider both flow velocity detection and estimation problems, which are employed in different applications. For the flow velocity detection, we obtain the maximum a posteriori (MAP) decision rule. To analyze the performance of the proposed flow velocity detector, we obtain the error probability, its Gaussian approximation and Chernoff information (CI) upper bound, and investigate the optimum and sub-optimum sampling times accordingly. We show that, for binary hypothesis, the sub-optimum sampling times using CI upper bound are the same. Further, the sub-optimum sampling times are close to the optimum sampling times. For the flow velocity estimation, we obtain the MAP and minimum mean square error (MMSE) estimators. We consider the mean square error (MSE) to investigate the error performance of the flow velocity estimators and obtain the Bayesian Cramer-Rao (BCR) and expected Cramer-Rao (ECR) lower bounds. Further, we obtain the optimum sampling times for each estimator. It is seen that the optimum sampling times for each estimator are nearly the same. The proposed flow velocity meter can be used to design a new modulation technique in molecular communication (MC), where information is encoded in the flow velocity of the medium instead of the concentration, type, or release time of the molecules. The setup and performance analysis of the proposed flow velocity detector and estimator for molecular communication system need further investigation.

cs.IT↗

arXiv2020

Corella: A Private Multi Server Learning Approach based on Correlated Queries

The emerging applications of machine learning algorithms on mobile devices motivate us to offload the computation tasks of training a model or deploying a trained one to the cloud or at the edge of the network. One of the major challenges in this setup is to guarantee the privacy of the client data. Various methods have been proposed to protect privacy in the literature. Those include (i) adding noise to the client data, which reduces the accuracy of the result, (ii) using secure multiparty computation (MPC), which requires significant communication among the computing nodes or with the client, (iii) relying on homomorphic encryption (HE) methods, which significantly increases computation load at the servers. In this paper, we propose $\textit{Corella}$ as an alternative approach to protect the privacy of data. The proposed scheme relies on a cluster of servers, where at most $T \in \mathbb{N}$ of them may collude, each running a learning model (e.g., a deep neural network). Each server is fed with the client data, added with $\textit{strong}$ noise, independent from user data. The variance of the noise is set to be large enough to make the information leakage to any subset of up to $T$ servers information-theoretically negligible. On the other hand, the added noises for different servers are $\textit{correlated}$. This correlation among the queries allows the parameters of the models running on different servers to be $\textit{trained}$ such that the client can mitigate the contribution of the noises by combining the outputs of the servers, and recover the final result with high accuracy and with a minor computational effort. Simulation results for various datasets demonstrate the accuracy of the proposed approach for the classification, using deep neural networks, and the autoencoder, as supervised and unsupervised learning tasks, respectively.

stat.ML↗

arXiv2020

On the Capacity of the Joint Time and Concentration Modulation for Molecular Communications

Most diffusion based molecular channels suffer from low information capacity due to the structure of the diffusion environment. To address this issue, this paper studies the capacity of the diffusion based molecular communication by exploiting both time and concentration level of the released molecules for information transfer. The transmitter releases molecules in one of the sub-intervals with a level of concentration both determined by input data, hereby applying joint time and concentration (JTAC) modulation. The observation time, at the receiver, which is equal to symbol period, is divided to some sub-intervals, not necessarily equal to the number of sub-intervals in the transmitter, and the number of received molecules in each sub-interval is counted. We propose three practical schemes, depending on how the receiver uses the number of molecules counted in the sub-intervals and find the lower bound on capacity in each case. Moreover, the symmetric Kullback-Liebler (KL) divergence metric is used to obtain a computable upper bound on the JTAC channel capacity. Finally, the Blahut-Arimoto algorithm is used to compute the capacity numerically, and to determine how tight the derived bounds are. Our numerical results indicate that our bounds are tight especially in environments with high diffusion coefficient. The improvements compared to the conventional concentration based modulation and timing based modulation are also demonstrated.

cs.IT↗

arXiv2019

Adaptive Release Duration Modulation for Limited Molecule Production and Storage

The nature of molecular transmitter imposes some limitations on the molecule production process and its storage. As the molecules act the role of the information carriers, the limitations affect the transmission process and the system performance considerably. In this paper, we focus on the transmitter's limitations, in particular, the limited molecule production rate and the finite storage capacity. We consider a time-slotted communication where the transmitter opens its outlets and releases the stored molecules for a specific time duration to send bit "1" and remains silent to send bit "0". By changing the release duration, we propose an adaptive release duration modulation. The objective is to find the optimal transmission release duration to minimize the probability of error. We characterize the properties of the optimal release duration and use it to derive upper and lower bounds on the system performance. We see that the proposed modulation scheme improves the performance.

cs.IT↗