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Mahtab Mirmohseni

Publications and source records attributed to Mahtab Mirmohseni.

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Fundamental Limits of Random Downlink Integrated Sensing and Communication over Rician Channels

This paper studies the stochastic performance of a downlink multiple-input multiple-output integrated sensing and communication (ISAC) system over Rician fading channels. Rician fading is important in line-of-sight (LoS)-dominated deployments, where a deterministic propagation component can strongly affect sensing and communication reliability. The base station (BS) simultaneously serves a user and senses a target. The BS-user channel contains LoS and non-line-of-sight components. The user LoS angle may be fixed or random, and the target angle may follow an arbitrary distribution potentially correlated with the user angle. Compared with Rayleigh fading, the deterministic LoS component introduces angle-dependent terms and leads to generally independent but non-identically distributed random vectors, requiring new analysis. We analyze two beamforming strategies: subspace joint beamforming (SJB), optimal for the shared waveform structure, and linear beamforming (LB), a practical alternative using separate sensing and communication beamformers. For both schemes, we derive communication outage probability (OP) and sensing OP based on the Cramer--Rao bound (CRB). We also identify special cases with simpler expressions. For LB, we derive upper and lower bounds on sensing OP and a tractable approximation. We characterize large-system and high-power scaling laws. LB without dirty paper coding (DPC) is interference-limited at high power due to radar self-interference. Results show the Rician K-factor affects communication more strongly than sensing, with non-monotonic behavior across regimes. LB with DPC achieves the best overall performance in strong LoS environments and is the only scheme achieving ultra-high communication reliability in Rayleigh fading, while SJB provides a robust lower-complexity alternative across operating conditions.

cs.IT

Secure Joint Source-Channel Coding of Multimodal Semantic Sources

We study the problem of secure joint source-channel coding for multimodal semantic sources transmitted over noisy wiretap channels. The source model consists of $m$ modalities (e.g., image, audio, and sensor data), all represented as random variables. The encoder observes independent and identically distributed samples of an arbitrary non-empty subset of modalities. The samples are encoded and transmitted over a discrete memoryless wiretap channel. The legitimate receiver reconstructs all modalities. We extend the rate-distortion-perception problem formulation to multimodal sources. We establish converse and achievability bounds on the fundamental limits of transmission rate, fidelity, and secrecy, under per-modality distortion and perception constraints, and per-subset equivocation constraints. We show that the fundamental limit for secrecy consists of three operationally distinct components: the level of compression, the secret key rate, and the statistics of the wiretap channel.

cs.IT

Secure Semantic Communication over Wiretap Channels: Rate-Distortion-Equivocation Tradeoff

This paper investigates an information-theoretic model of secure semantic-aware communication. For this purpose, we consider the lossy joint source-channel coding (JSCC) of a memoryless semantic source transmitted over a memoryless wiretap channel. The source consists of two correlated parts that represent semantic and observed aspects of the information. Our model assumes separate fidelity and secrecy constraints on each source component and, in addition, encompasses two cases for the source output, in order to evaluate the performance gains if the encoder has an extended access to the source. Specifically, in Case 1, the encoder has direct access only to the samples from a single (observed) source component, while in Case 2 it has additional direct access to the samples of the underlying semantic information. We derive single-letter converse and achievability bounds on the rate-distortion-equivocation region. The converse bound explicitly contains rate-distortion functions, making it easy to evaluate, especially for some common distributions. The proposed achievability coding scheme involves novel stochastic superposition coding with two private parts to enable analysis of the equivocation for each source component, separately. Our results generalise some of the previously established source and source-channel coding problems. The general results are further specialised to Gaussian and Bernoulli sources transmitted over Gaussian and binary wiretap channels, respectively. The numerical evaluations illustrate the derived bounds for these distributions.

cs.IT

Secure Integrated Sensing and Communication Networks: Stochastic Performance Analysis

This paper analyzes the stochastic security performance of a multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system in a downlink scenario. A base station (BS) transmits a multi-functional signal to simultaneously communicate with a user, sense a target's angular location, and counteract eavesdropping threats. The attack model considers a passive single-antenna communication eavesdropper intercepting communication data, as well as a multi-antenna sensing eavesdropper attempting to infer the target's location. We also consider a malicious target scenario where the target plays the role of the communication eavesdropper. The BS-user and BS-eavesdroppers channels follow Rayleigh fading, while the target's azimuth angle is uniformly distributed. To evaluate the performance in this random network, we derive the ergodic secrecy rate (ESR) and the ergodic Cramer-Rao lower bound (CRB), for target localization, at both the BS and the sensing eavesdropper. This involves computing the probability density functions (PDFs) of the signal-to-noise ratio (SNR) and CRB, leveraging the central limit theorem for tractability. We characterize the boundary of the CRB-secrecy rate region, and interpret the performance tradeoffs between communication and sensing while guaranteeing a level of security and privacy in the random ISAC networks.

cs.IT

Massive MIMO-NOMA Systems Secrecy in the Presence of Active Eavesdroppers

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.

cs.IT

UAV-Mounted IRS (UMI) in the Presence of Hovering Fluctuations: 3D Pattern Characterization and Performance Analysis

This paper investigates unmanned aerial vehicle (UAV)-mounted intelligent reflecting surfaces (IRS) to leverage the benefits of this technology for future communication networks, such as 6G. Key advantages include enhanced spectral and energy efficiency, expanded network coverage, and flexible deployment. One of the main challenges in employing UAV-mounted IRS (UMI) technology is the random fluctuations of hovering UAVs. Focusing on this challenge, this paper explores the capabilities of UMI with passive/active elements affected by UAV fluctuations in both horizontal and vertical angles, considering the three-dimensional (3D) radiation pattern of the IRS. The relationship between UAV fluctuations and IRS pattern is investigated by taking into account the random angular vibrations of UAVs. A tractable and closed-form distribution function for the IRS pattern is derived, using linear approximation and by dividing it into several sectors. In addition, closed-form expressions for outage probability (OP) are obtained using central limit theorem (CLT) and Gamma approximation. The theoretical expressions are validated through Monte Carlo simulations. The findings indicate that the random fluctuations of hovering UAVs have a notable impact on the performance of UMI systems. To avoid link interruptions due to UAV instability, IRS should utilize fewer elements, even though this leads to a decrease in directivity. As a result, unlike terrestrial IRS, incorporating more elements into aerial IRS systems does not necessarily improve performance due to the fluctuations in UAV. Numerical results show that the OP can be minimized by selecting the optimal number of IRS elements and using active elements.

eess.SP

PLS-Assisted Offloading for Edge Computing-Enabled Post-Quantum Security in Resource-Constrained Devices

With the advent of post-quantum cryptography (PQC) standards, it has become imperative for resource-constrained devices (RCDs) in the Internet of Things (IoT) to adopt these quantum-resistant protocols. However, the high computational overhead and the large key sizes associated with PQC make direct deployment on such devices impractical. To address this challenge, we propose an edge computing-enabled PQC framework that leverages a physical-layer security (PLS)-assisted offloading strategy, allowing devices to either offload intensive cryptographic tasks to a post-quantum edge server (PQES) or perform them locally. Furthermore, to ensure data confidentiality within the edge domain, our framework integrates two PLS techniques: offloading RCDs employ wiretap coding to secure data transmission, while non-offloading RCDs serve as friendly jammers by broadcasting artificial noise to disrupt potential eavesdroppers. Accordingly, we co-design the computation offloading and PLS strategy by jointly optimizing the device transmit power, PQES computation resource allocation, and offloading decisions to minimize overall latency under resource constraints. Numerical results demonstrate significant latency reductions compared to baseline schemes, confirming the scalability and efficiency of our approach for secure PQC operations in IoT networks.

cs.CR

On Stochastic Performance Analysis of Secure Integrated Sensing and Communication Networks

This paper analyzes the stochastic security performance of a multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system in a downlink scenario. A base station (BS) transmits a multi-functional signal to simultaneously communicate with a user, sense a target angular location, and counteract eavesdropping threats. The system includes a passive single-antenna communication eavesdropper and a multi-antenna sensing eavesdropper attempting to infer the target location. The BS-user and BS-eavesdroppers channels follow Rayleigh fading, while the target azimuth angle is uniformly distributed. To evaluate the performance, we derive exact expressions for the secrecy ergodic rate and the ergodic Cramer-Rao lower bound (CRB) for target localization at both the BS and the sensing eavesdropper. This involves computing the probability density functions (PDFs) of the signal-to-noise ratio (SNR) and CRB, leveraging the central limit theorem for tractability. Numerical results validate our findings.

cs.IT

Optical ISAC: Fundamental Performance Limits and Transceiver Design

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.

cs.IT

Hybrid Channel- and Coding-Based Challenge-Response Physical-Layer Authentication

This letter proposes a new physical layer authentication mechanism operating at the physical layer of a communication system where the receiver has partial control of the channel conditions (e.g., using an intelligent reflecting surface). We aim to exploit both instantaneous channel state information (CSI) and a secret shared key for authentication. This is achieved by both transmitting an identifying key by wiretap coding (to conceal the key from the attacker) and checking that the instantaneous CSI corresponds to the channel configuration randomly selected by the receiver. We investigate the trade-off between the pilot signals used for CSI estimation and the coding rate (or key length) to improve the overall security of the authentication procedure.

cs.IT

Degrees of Freedom of Cache-Aided Interference Channels Assisted by Active Intelligent Reflecting Surfaces

This paper studies cache-aided wireless networks in the presence of active intelligent reflecting surfaces (IRSs) from an information-theoretic perspective. Specifically, we investigate interference management in a cache-aided wireless network assisted by an active IRS to enhance the achievable degrees of freedom (DoF). To this end, we jointly design the content placement, delivery phase, and IRS coefficients, and propose a one-shot achievability scheme. Our scheme exploits transmitters' cooperation, cache contents, interference alignment, and IRS capabilities, based on the network parameters. We derive the achievable one-shot sum-DoF for different cache sizes, network configurations, and numbers of IRS elements, followed by an upper bound. Our results highlight the potential of deploying an IRS in cache-aided wireless communication systems. In particular, they underscore the enhancement of achievable DoF for various parameter regimes, especially when cache sizes are inadequate. Notably, we show that access to an IRS with a sufficient number of elements enables the achievement of the maximum possible DoF for various parameter regimes of interest.

cs.IT

Output Statistics of Random Binning: Tsallis Divergence and Its Applications

Random binning is a widely used technique in information theory with diverse applications. In this paper, we focus on the output statistics of random binning (OSRB) using the Tsallis divergence $T_α$. We analyze all values of $α\in (0, \infty)\cup\{\infty\}$ and consider three scenarios: (i) the binned sequence is generated i.i.d., (ii) the sequence is randomly chosen from an $ε$-typical set, and (iii) the sequence originates from an $ε$-typical set and is passed through a non-memoryless virtual channel. Our proofs cover both achievability and converse results. To address the unbounded nature of $T_\infty$, we extend the OSRB framework using Rényi's divergence with order infinity, denoted $D_\infty$. As part of our exploration, we analyze a specific form of Rényi's conditional entropy and its properties. Additionally, we demonstrate the application of this framework in deriving achievability results for the wiretap channel, where Tsallis divergence serves as a security measure. The secure rate we obtain through the OSRB analysis matches the secure capacity for $α\in (0, 2]\cup\{{\infty}\}$ and serves as a potential candidate for the secure capacity when $α\in (2, \infty)$.

cs.IT

Secure Semantic Communication over Wiretap Channel

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.

cs.IT

On the size of error ball in DNA storage channels

Recent experiments have demonstrated the feasibility of storing digital information in macromolecules such as DNA and protein. However, the DNA storage channel is prone to errors such as deletions, insertions, and substitutions. During the synthesis and reading phases of DNA strings, many noisy copies of the original string are generated. The problem of recovering the original string from these noisy copies is known as sequence reconstruction. A key concept in this problem is the error ball, which is the set of all possible sequences that can result from a limited number of errors applied to the original sequence. Levenshtein showed that the minimum number of noisy copies required for a given channel to recover the original sequence is equal to one plus the maximum size of the intersection of two error balls. Therefore, deriving the size of the error ball for any channel and any sequence is essential for solving the sequence reconstruction problem. In DNA storage systems, multiple types of errors such as deletion, insertion and substitution in a string could occur simultaneously. In this work, we aim to derive the size of the error ball for channels with multiple types of errors and at most three edits. Specifically, we consider the channels with single-deletion double-substitution, single-deletion double-insertion and single-insertion single-substitution errors.

cs.IT

On Stochastic Fundamental Limits 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. Due to the randomness inherent in the network, the challenge is to consider suitable performance metrics for this randomness. To address this issue, for users, we employ the user's rate outage probability (OP) and ergodic rate, while for target, we propose using the OP of the Cramér-Rao lower bound (CRLB) for the angle of arrival and the ergodic CRLB. We have obtained the expressions of these metrics for scenarios where the BS employs two different beamforming methods. Our approach to deriving these metrics involves computing the probability density function (PDF) of the signal-to-noise ratio for users and the CRLB for the target. We have demonstrated that the central limit theorem provides a viable approach for deriving these PDFs. In our numerical results, we demonstrate the trade-off between sensing and communication (S \& C) by characterizing the region of S \& C metrics and by obtaining the Pareto optimal boundary points, confirmed with simulations.

cs.IT

RIS-Assisted D2D Communication in the Presence of Interference: Outage Performance Analysis and DNN-Based Prediction

This paper analyses the performance of reconfigurable intelligent surface (RIS)-assisted device-to-device (D2D) communication systems, focusing on addressing co-channel interference, a prevalent issue due to the frequency reuse of sidelink in the underlay in-band D2D communications. In contrast to previous studies that either neglect interference or consider it only at the user, our research investigates a performance analysis in terms of outage probability (OP) for RIS-assisted D2D communication systems considering the presence of interference at both the user and the RIS. More specifically, we introduce a novel integral-form expression for an exact analysis of OP. Additionally, we present a new accurate approximation expression for OP, using the gamma distributions to approximate the fading of both desired and interference links, thereby yielding a closed-form expression. Nevertheless, both derived expressions, i.e., the exact integral-form and the approximate closed-form, contain special functions, such as Meijer's G-function and the parabolic cylinder function, which complicate real-time OP analysis. To circumvent this, we employ a deep neural network (DNN) for real-time OP prediction, trained with data generated by the exact expression. Moreover, we present a tight upper bound that quantifies the impact of interference on achievable diversity order and coding gain. We validate the derived expressions through Monte Carlo simulations. Our analysis reveals that while interference does not affect the system's diversity order, it significantly degrades the performance by reducing the coding gain. The results further demonstrate that increasing the number of RIS's reflecting elements is an effective strategy to mitigate the adverse effects of the interference on the system performance.

eess.SP

A Physical Layer Security Framework for IRS-Assisted Integrated Sensing and Semantic Communication Systems

In this paper, we propose a physical layer security (PLS) framework for an intelligent reflecting surface (IRS)-assisted integrated sensing and semantic communication (ISASC) system, where a multi-antenna dual-functional semantic base station (BS) serves multiple semantic communication users (SCUs) and monitors a potentially malicious sensing target (MST) in the presence of an eavesdropper (EVE). Both MST and EVE attempt to wiretap information from the signals transmitted to the SCUs. The deployment of the IRS not only enhances PLS by directing a strong beam towards the SCUs, but also improves the localization information for the target without disclosing information about the SCUs. To further strengthen PLS, we employ joint artificial noise (AN) and dedicated sensing signal (DSS), in addition to wiretap coding. To evaluate sensing accuracy, we derive the Cramer-Rao bound (CRB) for estimating the direction of arrival (DoA), and to assess the PLS level of the ISASC system, we determine a closed-form expression for the semantic secrecy rate (SSR). To achieve an optimal trade-off between these two competing objectives, we formulate a multi-objective optimization problem (MOOP) for the joint design of the BS's beamforming (BF) vectors and the IRS's phase shift vector. To tackle this MOOP problem, the $\epsilon$-constraint method is employed, followed by an alternating optimization (AO)-based algorithm that leverages the classical successive convex approximation (SCA) and semidefinite relaxation (SDR) techniques. Simulation results demonstrate that the proposed scheme outperforms the baseline schemes, achieving a superior trade-off between SSR and CRB. Specifically, our proposed approach improves the sensing accuracy by 5 dB compared to the commonly adopted maximal ratio transmission (MRT) approach.

eess.SP

Stochastic Analysis of Homogeneous Wireless Networks Assisted by Intelligent Reflecting Surfaces

In this paper, we study the impact of the existence of multiple IRSs in a homogeneous wireless network, in which all BSs, users (U), and IRSs are spatially distributed by an independent homogeneous PPP, with density $λ_{\rm BS}\rm{[BS/m^2]}$, $λ_{\rm U}\rm{[U/m^2]}$, and $λ_{\rm IRS}\rm{[IRS/m^2]}$, respectively. We utilize a uniformly random serving strategy for BS and IRS to create stochastic symmetry in the network. We analyze the performance of the network and study the effect of the existence of the IRS on the network performance. To this end, for a typical user in the system, we derive analytical upper and lower bounds on the expectation of the power (second statistical moment) of the desired signal and the interference caused by BSs and other users. After that, we obtain analytical upper bounds on the decay of the probability of the power of the desired signal and the interference for the typical user (which results in a lower bound for the cumulative distribution function (CDF)). Moreover, we derive upper bounds on the decay of the probability of the capacity of one typical user, which results in a lower bound for the outage probability. In the numerical results, we observe that the numerical calculation of the power of the desired signal and the interference is near the derived lower bounds and we show that the increment of the parameter ${(λ_{\rm IRS})}$ causes increment in powers of both the desired and interference signals. We also observe that the increment of the parameter ${λ_{\rm IRS}}$ causes the decrement of outage probability.

cs.IT