Dr Mahtab Mirmohseni

Semantic communication is a new paradigm for information transmission that integrates the essential meaning (semantics) of the message into the communication process. However, like in classic wireless communications, the open nature of wireless channels poses security risks for semantic communications. In this paper, we characterize information-theoretic limits for the secure transmission of a semantic source over a wiretap channel. Under separate secrecy and distortion constrains for semantics and observed data, we present general inner and outer bounds on the rate-distortion-equivocation region. We also reduce the general region to the case of Gaussian source and Gaussian wiretap channel and provide numerical evaluations.

This paper characterizes the optimal Capacity-Distortion (C-D) tradeoff in an optical point-to-point system with Single-Input Single-Output (SISO) for communication and Single-Input Multiple-Output (SIMO) for sensing within an Integrated Sensing and Communication (ISAC) framework. We consider the optimal Rate-Distortion (R-D) region and explore several Inner (IB) and Outer Bounds (OB). We introduce practical, asymptotically optimal Maximum A Posteriori (MAP) and Maximum Likelihood Estimators (MLE) for target distance, addressing nonlinear measurement-to-state relationships and non-conjugate priors. As the number of sensing antennas increases, these estimators converge to the Bayesian Cramér-Rao Bound (BCRB). We also establish that the achievable Rate-Cramér-Rao Bound (R-CRB) serves as an OB for the optimal C-D region, valid for both unbiased estimators and asymptotically large numbers of receive antennas. To clarify that the input distribution determines the tradeoff across the Pareto boundary of the C-D region, we propose two algorithms: i) an iterative Blahut-Arimoto Algorithm (BAA)-type method, and ii) a memory-efficient Closed-Form (CF) approach. The CF approach includes a CF optimal distribution for high Optical Signal-to-Noise Ratio (O-SNR) conditions. Additionally, we adapt and refine the Deterministic-Random Tradeoff (DRT) to this optical ISAC context.

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.

This paper characterizes the optimal capacity-distortion (C-D) tradeoff in an optical point-to-point (P2P) system with single-input single-output for communication and single-input multiple-output for sensing (SISO-COM and SIMO-SEN) within an integrated sensing and communication (ISAC) framework. We consider the optimal rate-distortion (R-D) region and explore several inner (IB) and outer (OB) bounds. We introduce practical, asymptotically optimal maximum a posteriori (MAP) and maximum likelihood estimators (MLE) for target distance, addressing nonlinear measurement-to-state relationships and non-conjugate priors. As the number of sensing antennas increases, these estimators converge to the Bayesian Cram'er-Rao bound (BCRB). We also establish that the achievable rate-CRB (AR-CRB) serves as an OB for the optimal C-D region, valid for both unbiased estimators and asymptotically large numbers of receive antennas. To clarify that the input distribution determines the tradeoff across the Pareto boundary of the C-D region, we propose two algorithms: i) an iterative Blahut-Arimoto algorithm (BAA)-type method, and ii) a memory-efficient closed-form (CF) approach. The CF approach includes a CF optimal distribution for high optical signal-to-noise ratio (O-SNR) conditions. Additionally, we adapt and refine the Deterministic-Random Tradeoff (DRT) to this optical ISAC context.

Non-orthogonal multiple access (NOMA) and massive multiple-input multiple-output (MIMO) systems are highly efficient. Massive MIMO systems are inherently resistant to passive attackers (eavesdroppers), thanks to transmissions directed to the desired users. However, active attackers can transmit a combination of legitimate user pilot signals during the channel estimation phase. This way they can mislead the base station (BS) to rotate the transmission in their direction, and allow them to eavesdrop during the downlink data transmission phase. In this paper, we analyse this vulnerability in an improved system model and stronger adversary assumptions, and investigate how physical layer security can mitigate such attacks and ensure secure (confidential) communication. We derive the secrecy outage probability (SOP) and a lower bound on the ergodic secrecy capacity, using stochastic geometry tools when the number of antennas in the BSs tends to infinity. We adapt the result to evaluate the secrecy performance in massive orthogonal multiple access (OMA). We find that appropriate power allocation allows NOMA to outperform OMA in terms of ergodic secrecy rate and SOP.

We consider the anonymous mutual authentication problem, which consists of a certificate authority, single or multiple verifiers, many legitimate users (provers) and any arbitrary number of illegitimate users. The legal verifier and a legitimate user must be mutually authenticated to each other using the user's key, while the identity of the user must stay unrevealed. An attacker (illegitimate prover) as well as an illegal verifier must fail in authentication. A general interactive information theoretic framework in a finite field is proposed, where the normalized total key rate as a metric for reliability is defined. Maximizing this rate has a trade-off with establishing anonymity. The problem is studied in two different scenarios: centralized scenario (one single verifier performs the authentication process) and distributed scenario (authentication is done by N verifiers, distributively). For both scenarios, achievable schemes, which satisfy the completeness, soundness (at both verifier and prover) and anonymity properties, are proposed. Increasing the size of the field, results in the key rate approaching its upper bound.

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

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.

In this letter, we consider a cache-enabled cloud radio access network with single-antenna base stations and single-antenna mobile users. Each base station can access the central processor of the network via a separate backhaul link with limited capacity. We utilize the interference alignment scheme as the transmission strategy between base stations and users. By assuming a block transmission scheme, we define a related data transmission delay. We derive the transmission delay and network power consumption. At last, we solve the problem of joint optimization of data transmission delay and network power consumption using DC programming algorithm. In our numerical results, we investigate the trade-off between delay and power consumption, and compare the results with those of a prior work that does not take the transmission delay into account in its optimization problem.

In attribute-based access control, users with specific verified attributes will gain access to some particular data. Concerning the privacy of the users' attributes, we study the problem of distributed attribute-based private access control (DAPAC) with multiple authorities. 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}}^{\ast}} = \left( {v_1^{\ast}, \ldots,v_N^{\ast}} \right) of dimension N and is eligible to retrieve a message {W^{{{\text{v}}^{\ast}}}, available on all servers. Each server n ∈ [N] can only observe and verify the n'th attribute of a user. In response, it sends a function of its authorized messages to the user. The system must satisfy the following conditions: (1) Correctness: the user with attribute vector v * can retrieve his intended message {W^{{{\text{v}}^{\ast}}} from the servers' responses, (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.

In this paper, we study the zero error capacity of the molecular delay channel when multiple molecule types are available at the transmitter. In the molecular delay channel, each transmitted molecule (of any type) is received by a delay of at most k time slots. Depending on the number of molecules that the transmitter is allowed to release in each time slot, we consider the following three cases: (i) when the maximum number of the released molecules of each type in each time slot is restricted (ii) when the total number of the released molecules (regardless of their type) in each time slot is restricted, and (iii) when the transmitter can use only one molecule type (of its choice) in each time slot. We derive lower bounds on the zero-error capacity of the delay channel for each case, by proposing zero-error codes that are based on the results by Kovačević and Popovski. We also derive upper bounds on the zero-error capacity of the delay channel. In the first case, these bounds match and yield the exact capacity, while in the other two cases, the bounds are shown to be close numerically. Our numerical results show that as the number of available molecule types increases, the capacity of the system increases substantially, compared to using only one molecule type. Furthermore, it is shown that the lower and upper bounds on the zero-error capacity of the delay channel in the second case are generally close to the lower and upper bounds in the third case, respectively, indicating the closeness of the zero-error capacities of the two cases. This result enables one to design a simpler system by employing a high rate code that has only one molecule type in each slot (designed for the third case) in the channel of the second case, without much rate loss.

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.

In this paper, we study the problem of cooperative abnormality detection using mobile sensors in a fluidic medium, based on a molecular communication setup. The sensors are injected into the medium to search the environment for the abnormality. To reduce the effects of sensor imperfection, we propose a cooperative scheme where the sensors activate each other by releasing some molecules (i.e., markers), into the medium after they sense an abnormality. A number of fusion centers (FC) are placed at specific locations in the medium, which absorb all sensors arrived at their locations. By observing the states of the received sensors, each FC decides whether an abnormality exists in its corresponding region or not. Then, it resets the sensors' activation flags and releases them again into the medium to proceed with the next regions. In our model, both sensors' imperfection and markers' background noise are taken into account. We consider two sensor types, the memoryless sensors that get active based on the number of received markers in each sampling time and the aggregate sensors that get active based on the summation of received markers in all sampling times, before they reach the FC. We analyze the related binary hypothesis testing problem and obtain the probabilities of false alarm and misdetection for the memoryless and aggregate sensors. Then, we obtain the probability of error. It is shown that using sensors with the ability of activating each other can significantly improves the performance in terms of probability of error.

In non-orthogonal multiple access (NOMA) systems, serving multiple users in shared resource blocks can allow untrusted users to overhear the messages of other users. In this context, we study a network consisting of a base station (BS), a near user and a far user, where the latter attempts to overhear the message of the former. The near user is a full-duplex (FD) node that can also act as a relay. Two operating scenarios are considered: 1) friendly jammer (FJ), where the FD node broadcasts noise for degrading the channel between the BS and the far user, while receiving data from the BS; and 2) friendly jammer relay (FJR), where, in addition to degrading the channel between the BS and the far user, the FD node relays the message of the far user. We investigate the secrecy performance of the network by characterizing the secrecy outage probability (SOP) in both scenarios. We obtain the exact SOP of the FJ case, and an approximation for the SOP of the FJR scenario, both expressed in closed-form. Numerical results confirm the accuracy of the analytical results. For a given BS power budget and power allocation to the users, it is demonstrated that the jamming and relaying powers are prominent factors to make the NOMA-FJR scheme superior to NOMA-FJ, as well as to conventional and cooperative NOMA schemes.

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.

In this paper, we study the DoF of the time-selective M\times N wireless X -network assisted by an IRS. It is well-known that the DoF of the M\times N wireless X -network is {}\frac {MN}{M+N-1} . We show that the maximum DoF of \min \{M,N\} can be achieved when the IRS has enough elements. We consider two kinds of active and passive IRSs. We also consider two different scenarios, where the channel coefficients for IRS elements are either independent or correlated. For the M\times N wireless X -network assisted by an active IRS with independent channel coefficients, we derive the inner and outer bounds on the DoF region and the lower and upper bounds on the sum DoF. We show that the maximum value for the sum DoF, i.e., \min (M,N) , is achievable if the number of elements is more than a threshold for the active IRS, which is equal to the approximate capacity of \min \{M,N\}\log (\rho +1)+o(\log (\rho)) for the IRS-assisted X -network, where \rho is the transmission power. For the M\times N wireless X -network assisted by a passive IRS with the assumption of independent and correlated channel coefficients for IRS elements, we introduce probabilistic inner and outer bounds on the DoF region, and the probabilistic lower and upper bounds on the sum DoF and show that the proposed lower bound for the sum DoF asymptotically approaches \min (M,N) with an order of at least O\left({{}\frac {1}{Q}}\right) for independent channel coefficients (i.e., the sum DoF is \min \{M,N\}\left({1-O\left({\frac {1}{Q}}\right)}\right) ), which is equal to the approximate capacity of \min \{M,N\}\left({1-O\left({{}\frac {1}{Q}}\right)}\right)\log (\rho +1)+o(\log (\rho)) and O\left({{}\frac {1}{\sqrt {Q}}}\right) for correlated channel coefficients (i.e., the sum DoF is \min \{M,N\}\left({1-O\left({{}\frac {1}{\sqrt {Q}}}\right)}\right) , which is equal to the approximate capacity of \min \{M,N\}\left({1-O\left({{}\frac {1}{\sqrt {Q}}}\right)}\right)\log (\rho +1)+o(\log (\rho))) , where Q is the number of IRS elements. Thus, this decrement in the order of convergence shows the performance loss for correlated IRS elements. In addition, we extend the lower bound of the sum DoF proposed for the active IRS with independent channel coefficients to the scenario with correlated channel coefficients, i.e., the sum DoF is the same as independent IRS elements for \min \{M,N\}\le 5 and Q\le 20 , and for other cases, the sum DoF converges to \min \{M,N\} with an order of at least O\left({{}\frac {1}{\sqrt {Q}}}\right) .

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.

In this article, 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 (FCs) for sampling, amplifying, and forwarding the signal, and a gateway (GW) 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 noncollaborative sensors that simultaneously release their molecules to the FCs when the number of activated sensors or the moving time reaches a certain threshold, respectively. The FCs amplify the received signal and forward it to the GW for making a decision using either an ideal or a noisy communication channel. A practical application of the proposed model is drug delivery in a tissue of the human body, to guide the nanomachine-bound drug to the exact location and so to eliminate the adverse effects of the drug on normal cells. Further applications are health-care, treatments of localized disease (e.g., tumors and inflammations), immune system triggering, and nanosurgery. The decision rules and probabilities of error are obtained for two considered sensor types in both ideal and noisy communication channels.

In this letter, we propose a novel communication scheme for macro-scale molecular timing channels (MTCs), where the information carrier is the release time of the molecules. Next, the symbol constellation, receiver's sampling time, and receiver's decision rule are designed and analyzed. We further propose a computationally simple yet optimal receiver. Our numerical results show that macro-scale MTC is an approach for achieving ultra-reliable molecular communication.

—In this paper, a multi-hop reconfigurable intelligent surfaces (RIS) aided multiple-input single-output (MISO) system is studied to mitigate significant channel attenuation in Millimeter wave and terahertz communication. The achievable sum rate of the system is maximized via optimizing the passive elements at the RISs with an iterative algorithm. Simulation results imply that the proposed algorithm is able to improve the achievable sum rate by increasing the number of RISs.

—This paper presents a unit cell with high efficiency for simultaneous transmission and reflection (STAR) surface operating at millimeter wave frequencies. Applying two perpendicular metallic gratings in the top and bottom of a dual-C shaped resonator, the unit cells can simultaneously control amplitude and phase of reflected and transmitted waves by adjusting the geometrical parameters. This structure can be leveraged to realize full-space electromagnetic manipulation in a simple way for potential applications in mutlifunctional devices.

The importance of molecular communication (MC) security, due to its sensitive in vivo applications necessitates investigating adversarial activities in MC systems. In this paper, we study the problem of jamming attacks in MC. In our model, a biological/engineered concentration transmitter releases a particular type of molecule to send its message over a diffusive channel to a transparent receiver. However, the jammer tries to disrupt regular communication and prevent the receiver from receiving a reliable message either by transmitting the same molecule type or a molecule type able to react with the date carrier molecule. We propose a jamming-resistant coding scheme to counteract this attack. Our approach is based on splitting each symbol's time slot into subslots where a random pre-shared pattern is used to determine the transmit strategy in these subslots. Two decision rules at the decoder are characterized and a sub-optimal threshold is computed for them. To analyse the performance of the proposed scheme, we derive the probability of error at the receiver. As the jammer can choose different types of molecules in each subslots according to its strategy, an optimal jamming strategy that maximizes the error probability of the message is derived numerically. The numerical results for the proposed scheme confirm the effectiveness of the scheme in protecting against jamming attacks.

In this article, we consider an energy harvesting cooperative network comprised of two data sources and one relay. All nodes transmit based on a predefined slotted Aloha protocol in a random access environment. The main challenge we study is to find how the relay node must share its energy between two sources to optimize their QoS metrics, i.e., throughput and average transmission delay (ATD), separately. Thus, according to our multi-source scenario, we encounter a multi-objective optimization problem (MOOP). Since the relay does not prioritize between two sources, in order to solve the MOOP, we optimize equal-weight linear aggregation of the QoS metrics of two sources. Interestingly, we show that our problem can be modeled as an exact potential game in which the Nash equilibrium strategy is an optimal and stable solution of the related MOOP. The cooperative relaying strategy proposed in this article assures that the throughput and ATD of each source is better than the corresponding metrics without relay. Finally, we present numerical results to show how much the derived cooperative relaying strategies improve the QoS of each source.

Flow velocity is an important characteristic of the fluidic mediums. In this article, 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.

A simultaneously transmitting and reflecting surface (STARS) enabled integrated sensing and communications (ISAC) framework is proposed, where a novel bi-directional sensing-STARS architecture is devised to facilitate the full-space communication and sensing. Based on the proposed framework, a joint optimization problem is formulated, where the Cramér-Rao bound (CRB) for estimating the 2-dimension direction-of-arrival of the sensing target is minimized. An alternating optimization algorithm is proposed. In particular, the maximum number of deployable sensors is obtained in the closed-form expressions. Simulation results validate that: 1) STARS was capable of providing superior sensing performance compared to the conventional reconfigurable intelligent surface, and 2) the maximum likelihood estimator can be adopted in the proposed strategy to achieve high-quality sensing.