arXiv subjects

Behrouz Maham

Publications and source records attributed to Behrouz Maham.

At least 19 recordsLinked to original sources

arXiv2024

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↗

arXiv2024

Robust 3D Multi-Source Localization with a Movable Antenna Array via Sparse Signal Processing

Accurately localizing multiple sources is a critical task with various applications in wireless communications, such as emergency services, including natural post-disaster search and rescue operations. However, scenarios where the receiver is moving have not been sufficiently addressed in recent studies. This paper tackles the angle of arrival (AOA) 3D-localization problem for multiple sparse signal sources with a moving receiver, which has a limited number of antennas that may be outnumbered by the sources. First, an energy detector algorithm is proposed to leverage signal sparsity for eliminating noisy samples. Subsequently, an iterative algorithm is developed to refine and estimate the AOAs accurately, initialized with previously estimated source locations and coarse elevation and azimuth AOAs obtained via the two-dimensional multiple signal classification (2D-MUSIC) method. To this end, we introduce a sparse recovery algorithm to exploit signal sparsity, followed by a phase smoothing algorithm to refine the estimates. The K-SVD algorithm is then applied to the smoothed output to accurately determine the elevation and azimuth AOAs of the sources. For localization, a new multi-source 3D-localization algorithm is proposed to estimate source positions using the refined AOA estimates over a sequence of time windows. Extensive simulations are carried out to demonstrate the effectiveness of the proposed framework.

eess.SP↗

arXiv2024

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 $\lambda_{{\rm BS}}\rm{[BS/m^2]}$, $\lambda_{{\rm U}}\rm{[U/m^2]}$, and $\lambda_{{\rm IRS}}\rm{[IRS/m^2]}$, 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 ${(\lambda_{\rm IRS})}$ causes increment in powers of both the desired and interference signals. We also observe that the increment of the parameter ${\lambda_{\rm IRS}}$ causes the decrement of outage probability.

cs.IT↗

arXiv2023

Federated Learning: A Cutting-Edge Survey of the Latest Advancements and Applications

Robust machine learning (ML) models can be developed by leveraging large volumes of data and distributing the computational tasks across numerous devices or servers. Federated learning (FL) is a technique in the realm of ML that facilitates this goal by utilizing cloud infrastructure to enable collaborative model training among a network of decentralized devices. Beyond distributing the computational load, FL targets the resolution of privacy issues and the reduction of communication costs simultaneously. To protect user privacy, FL requires users to send model updates rather than transmitting large quantities of raw and potentially confidential data. Specifically, individuals train ML models locally using their own data and then upload the results in the form of weights and gradients to the cloud for aggregation into the global model. This strategy is also advantageous in environments with limited bandwidth or high communication costs, as it prevents the transmission of large data volumes. With the increasing volume of data and rising privacy concerns, alongside the emergence of large-scale ML models like Large Language Models (LLMs), FL presents itself as a timely and relevant solution. It is therefore essential to review current FL algorithms to guide future research that meets the rapidly evolving ML demands. This survey provides a comprehensive analysis and comparison of the most recent FL algorithms, evaluating them on various fronts including mathematical frameworks, privacy protection, resource allocation, and applications. Beyond summarizing existing FL methods, this survey identifies potential gaps, open areas, and future challenges based on the performance reports and algorithms used in recent studies. This survey enables researchers to readily identify existing limitations in the FL field for further exploration.

cs.LG↗

arXiv2022

Rumor Stance Classification in Online Social Networks: The State-of-the-Art, Prospects, and Future Challenges

The emergence of the Internet as a ubiquitous technology has facilitated the rapid evolution of social media as the leading virtual platform for communication, content sharing, and information dissemination. In spite of revolutionizing the way news is delivered to people, this technology has also brought along with itself inevitable demerits. One such drawback is the spread of rumors expedited by social media platforms, which may provoke doubt and fear. Therefore, it is essential to debunk rumors before their widespread use. Over the years, many studies have been conducted to develop effective rumor verification systems. One aspect of such studies focuses on rumor stance classification, which involves the task of utilizing user viewpoints regarding a rumorous post to better predict the veracity of a rumor. Relying on user stances in rumor verification has gained significant importance, for it has resulted in significant improvements in the model performance. In this paper, we conduct a comprehensive literature review of rumor stance classification in complex online social networks (OSNs). In particular, we present a thorough description of these approaches and compare their performances. Moreover, we introduce multiple datasets available for this purpose and highlight their limitations. Finally, challenges and future directions are discussed to stimulate further relevant research efforts.

cs.SI↗

arXiv2021

Modeling RIS Empowered Outdoor-to-Indoor Communication in mmWave Cellular Networks

With the increasing adoption of millimeter-waves (mmWave) over cellular networks, outdoor-to-indoor (O2I) communication has been one of the challenging research problems due to high penetration loss of buildings. To address this, we investigate the practicability of utilizing reconfigurable intelligent surfaces (RISs) for assisting such O2I communication. We propose a new notion of prefabricated RIS-empowered wall consisting of a large number of chipless radio frequency identification (RFID) sensors. Each sensor maintains its own bank of delay lines. These sensors which are built within the building walls can potentially be controlled by a main integrated circuit (IC) to regulate the phase of impinging signals. To evaluate our idea, we develop a thorough performance analysis of the RIS-based O2I communication in the mmWave network using stochastic-geometry tools for blockage models. Our analysis facilitates two closed-form approximations of the downlink signal-to-noise ratio (SNR) coverage probability for RIS-based O2I communication. We perform extensive simulations to evaluate the accuracy of the derived expressions, thus providing new observations and findings.

eess.SP↗

arXiv2020

3D Channel Characterization and Performance Analysis of UAV-Assisted Millimeter Wave Links

Recently, the use of millimeter wave (mmW) frequencies has emerged as a promising solution for wirelessly connecting unmanned aerial vehicles (UAVs) to ground users. However, employing UAVassisted directional mmW links is challenging due to the random fluctuations of hovering UAVs. In this paper, the performance of UAV-based mmW links is investigated when UAVs are equipped with square array antennas. The 3GPP antenna propagation patterns are used to model the square array antenna. It is shown that the square array antenna is sensitive to both horizontal and vertical angular vibrations of UAVs. In order to explore the relationship between the vibrations of UAVs and their antenna pattern, the UAV-based mmW channels are characterized by considering the large scale path loss, small scale fading along with antenna patterns as well as the random effect of UAVs' angular vibrations. To enable effective performance analysis, tractable and closed-form statistical channel models are derived for aerial-to-aerial (A2A), ground-to-aerial (G2A), and aerial-to-ground (A2G) channels. The accuracy of analytical models is verified by employing Monte Carlo simulations. Analytical results are then used to study the effect of antenna pattern gain under different conditions for the UAVs' angular vibrations for establishing reliable UAV-assisted mmW links in terms of achieving minimum outage probability.

eess.SP↗

arXiv2017

Mobility Management for Heterogeneous Networks: Leveraging Millimeter Wave for Seamless Handover

One of the most promising approaches to overcome the uncertainty and dynamic channel variations of millimeter wave (mmW) communications is to deploy dual-mode base stations that integrate both mmW and microwave ($μ$W) frequencies. In particular, if properly designed, such dual-mode base stations can enhance mobility and handover in highly mobile wireless environments. In this paper, a novel approach for analyzing and managing mobility in joint $μ$W-mmW networks is proposed. The proposed approach leverages device-level caching along with the capabilities of dual-mode base stations to minimize handover failures and provide seamless mobility. First, fundamental results on the caching capabilities, including caching probability and cache duration, are derived for the proposed dual-mode network scenario. Second, the average achievable rate of caching is derived for mobile users. Then, the impact of caching on the number of handovers (HOs) and the average handover failure (HOF) is analyzed. The derived analytical results suggest that content caching will reduce the HOF and enhance the mobility management in heterogeneous wireless networks with mmW capabilities. Numerical results corroborate the analytical derivations and show that the proposed solution provides significant reductions in the average HOF, reaching up to 45%, for mobile users moving with relatively high speeds.

cs.IT↗

arXiv2017

A Colonel Blotto Game for Interdependence-Aware Cyber-Physical Systems Security in Smart Cities

Smart cities must integrate a number of interdependent cyber-physical systems that operate in a coordinated manner to improve the well-being of the city's residents. A cyber-physical system (CPS) is a system of computational elements controlling physical entities. Large-scale CPSs are more vulnerable to attacks due to the cyber-physical interdependencies that can lead to cascading failures which can have a significant detrimental effect on a city. In this paper, a novel approach is proposed for analyzing the problem of allocating security resources, such as firewalls and anti-malware, over the various cyber components of an interdependent CPS to protect the system against imminent attacks. The problem is formulated as a Colonel Blotto game in which the attacker seeks to allocate its resources to compromise the CPS, while the defender chooses how to distribute its resources to defend against potential attacks. To evaluate the effects of defense and attack, various CPS factors are considered including human-CPS interactions as well as physical and topological characteristics of a CPS such as flow and capacity of interconnections and minimum path algorithms. Results show that, for the case in which the attacker is not aware of the CPS interdependencies, the defender can have a higher payoff, compared to the case in which the attacker has complete information. The results also show that, in the case of more symmetric nodes, due to interdependencies, the defender achieves its highest payoff at the equilibrium compared to the case with independent, asymmetric nodes.

cs.GT↗

arXiv2017

Caching Meets Millimeter Wave Communications for Enhanced Mobility Management in 5G Networks

One of the most promising approaches to overcome the uncertainty and dynamic channel variations of millimeter wave (mmW) communications is to deploy dual-mode base stations that integrate both mmW and microwave ($μ$W) frequencies. If properly designed, such dual-mode base stations can enhance mobility and handover in highly mobile wireless environments. In this paper, a novel approach for analyzing and managing mobility in joint $μ$W-mmW networks is proposed. The proposed approach leverages device-level caching along with the capabilities of dual-mode base stations to minimize handover failures, reduce inter-frequency measurement energy consumption, and provide seamless mobility in emerging dense heterogeneous networks. First, fundamental results on the caching capabilities, including caching probability and cache duration are derived for the proposed dual-mode network scenario. Second, the average achievable rate of caching is derived for mobile users. Third, the proposed cache-enabled mobility management problem is formulated as a dynamic matching game between mobile user equipments (MUEs) and small base stations (SBSs). The goal of this game is to find a distributed handover mechanism that subject to the network constraints on HOFs and limited cache sizes, allows each MUE to choose between executing an HO to a target SBS, being connected to the macrocell base station (MBS), or perform a transparent HO by using the cached content. The formulated matching game allows capturing the dynamics of the mobility management problem caused by HOFs. To solve this dynamic matching problem, a novel algorithm is proposed and its convergence to a two-sided dynamically stable HO policy is proved. Numerical results corroborate the analytical derivations and show that the proposed solution will provides significant reductions in both the HOF and energy consumption by MUEs.

cs.GT↗

arXiv2016

Truthful Spectrum Auction for Efficient Anti-Jamming in Cognitive Radio Networks

One significant challenge in cognitive radio networks is to design a framework in which the selfish secondary users are obliged to interact with each other truthfully. Moreover, due to the vulnerability of these networks against jamming attacks, designing anti-jamming defense mechanisms is equally important. %providing the security defense is also of great importance. In this paper, we propose a truthful mechanism, robust against the jamming, for a dynamic stochastic cognitive radio network consisting of several selfish secondary users and a malicious user. In this model, each secondary user participates in an auction and wish to use the unjammed spectrum, and the malicious user aims at jamming a channel by corrupting the communication link. A truthful auction mechanism is designed among the secondary users. Furthermore, a zero-sum game is formulated between the set of secondary users and the malicious user. This joint problem is then cast as a randomized two-level auctions in which the first auction allocates the vacant channels, and then the second one assigns the remaining unallocated channels. We have also changed this solution to a trustful distributed scheme. Simulation results show that the distributed algorithm can achieve a performance that is close to the centralized algorithm, without the added overhead and complexity.

cs.NI↗

arXiv2015

A context-aware matching game for user association in wireless small cell networks

Small cell networks are seen as a promising technology for boosting the performance of future wireless networks. In this paper, we propose a novel context-aware user-cell association approach for small cell networks that exploits the information about the velocity and trajectory of the users while also taking into account their quality of service (QoS) requirements. We formulate the problem in the framework of matching theory with externalities in which the agents, namely users and small cell base stations (SCBSs), have strict interdependent preferences over the members of the opposite set. To solve the problem, we propose a novel algorithm that leads to a stable matching among the users and SCBSs. We show that the proposed approach can better balance the traffic among the cells while also satisfying the QoS of the users. Simulation results show that the proposed matching algorithm yields significant performance advantages relative to traditional context-unaware approaches.

cs.NI↗

arXiv2015

Cell Selection in Wireless Two-Tier Networks: A Context-Aware Matching Game

The deployment of small cell networks is seen as a major feature of the next generation of wireless networks. In this paper, a novel approach for cell association in small cell networks is proposed. The proposed approach exploits new types of information extracted from the users' devices and environment to improve the way in which users are assigned to their serving base stations. Examples of such context information include the devices' screen size and the users' trajectory. The problem is formulated as a matching game with externalities and a new, distributed algorithm is proposed to solve this game. The proposed algorithm is shown to reach a stable matching whose properties are studied. Simulation results show that the proposed context-aware matching approach yields significant performance gains, in terms of the average utility per user, when compared with a classical max-SINR approach.

cs.NI↗

arXiv2015

Power Distribution of Device-to-Device Communications in Underlaid Cellular Networks

Device-to-device (D2D) communications have recently emerged as a novel transmission paradigm in wireless cellular networks. D2D transmissions take place concurrently with the usual cellular connections, and thus, controlling the interference brought to the macro-cellular user equipment (UE) is of vital importance. In this paper, we consider the uplink transmission of a tier of D2D users that operates as an underlay for the traditional cellular network. Using network model based on stochastic geometry, we derive the equilibrium cumulative distribution function (CDF) of the D2D transmit power. Considering interference-limited and relatively lossy environment cases, closed form equations are derived for the power CDF. Finally, a tight closed-form upper-bound for the derived power distribution is proposed, and the analytical results are validated via simulation.

cs.NI↗

arXiv2015

Integer Forcing-and-Forward Transceiver Design for MIMO Multi-Pair Two-Way Relaying

In this paper, we propose a new transmission scheme, named as Integer Forcing-and-Forward (IFF), for communications among multi-pair multiple-antenna users in which each pair exchanges their messages with the help of a single multi antennas relay in the multiple-access and broadcast phases. The proposed scheme utilizes Integer Forcing Linear Receiver (IFLR) at relay, which uses equations, i.e., linear integer-combinations of messages, to harness the intra-pair interference. Accordingly, we propose the design of mean squared error (MSE) based transceiver, including precoder and projection matrices for the relay and users, assuming that the perfect channel state information (CSI) is available. In this regards, in the multiple-access phase, we introduce two new MSE criteria for the related precoding and filter designs, i.e., the sum of the equations MSE (Sum-Equation MSE) and the maximum of the equations MSE (Max-Equation MSE), to exploit the equations in the relay. In addition, the convergence of the proposed criteria is proven as well. Moreover, in the broadcast phase, we use the two traditional MSE criteria, i.e. the sum of the users' mean squred errors (Sum MSE) and the maximum of the users' mean squared errors (Max MSE), to design the related precoding and filters for recovering relay's equations by the users. Then, we consider a more practical scenario with imperfect CSI. For this case, IFLR receiver is modified, and another transceiver design is proposed, which take into account the effect of channels estimation error. We evaluate the performance of our proposed strategy and compare the results with the conventional amplify-and-forward (AF) and denoise-and-forward (DF) strategies for the same scenario. The results indicate the substantial superiority of the proposed strategy in terms of the outage probability and the sum rate.

cs.IT↗

arXiv2015

On the Effect of I/Q Imbalance on Energy Detection and a Novel Four-Level Hypothesis Spectrum Sensing

Direct-conversion transceivers are in demand, due to low implementation cost of analog front-ends. However, these transmitters or receivers introduce imperfections such as in-phase and quadrature-phase (I/Q) imbalances. In this paper, we first investigate the effect of I/Q imbalance on the performance of primary system, and show that these impairments can severely degrade the performance of cognitive radio system that are based on orthogonal frequency division multiplexing (OFDM) multiple access scheme. Next, we design a new four-level hypothesis blind detector for spectrum sensing in such cognitive radio system, and show that the proposed detector is less vulnerable to I/Q imbalance than conventional two-level detectors.

cs.IT↗

arXiv2014

Matching theory for priority-based cell association in the downlink of wireless small cell networks

The deployment of small cells, overlaid on existing cellular infrastructure, is seen as a key feature in next-generation cellular systems. In this paper, the problem of user association in the downlink of small cell networks (SCNs) is considered. The problem is formulated as a many-to-one matching game in which the users and SCBSs rank one another based on utility functions that account for both the achievable performance, in terms of rate and fairness to cell edge users, as captured by newly proposed priorities. To solve this game, a novel distributed algorithm that can reach a stable matching is proposed. Simulation results show that the proposed approach yields an average utility gain of up to 65% compared to a common association algorithm that is based on received signal strength. Compared to the classical deferred acceptance algorithm, the results also show a 40% utility gain and a more fair utility distribution among the users.

cs.IT↗

arXiv2013

Rethinking the Secrecy Outage Formulation: A Secure Transmission Design Perspective

This letter studies information-theoretic security without knowing the eavesdropper's channel fading state. We present an alternative secrecy outage formulation to measure the probability that message transmissions fail to achieve perfect secrecy. Using this formulation, we design two transmission schemes that satisfy the given security requirement while achieving good throughput performance.

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