arXiv subjects

Vahid Jamali

Publications and source records attributed to Vahid Jamali.

At least 73 records · Page 4Linked to original sources

arXiv2022

Parametric Channel Estimation for LoS Dominated Holographic Massive MIMO Systems

Holographic massive multiple-input multiple-output (MIMO), in which a spatially continuous surface is being used for signal transmission and reception, have emerged as a promising solution for improving the coverage and data rate of wireless communication systems. To realize these objectives, the acquisition of accurate channel state information in holographic massive MIMO systems is crucial. In this paper, we propose a channel estimation scheme based on a parametric physical channel model for line-of-sight (LoS) dominated communication in millimeter and terahertz wave bands. The proposed channel estimation scheme exploits the specific structure of the radiated beams generated by the continuous surface to estimate the channel parameters in a dominated LoS channel model. The training overhead and computational complexity of the proposed scheme do not scale with the number of antennas. The simulation results demonstrate that the proposed estimation scheme significantly outperforms other benchmark schemes in poor scattering environment.

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arXiv2022

RIS Assisted Device Activity Detection with Statistical Channel State Information

This paper studies reconfigurable intelligent surface (RIS) assisted device activity detection for grant-free (GF) uplink transmission in wireless communication networks. In particular, we consider mobile devices located in an area where the direct link to an access point (AP) is blocked. Thus, the devices try to connect to the AP via a reflected link provided by an RIS. Therefore, a RIS phase-shift design is desired that covers the entire blocked area with a wide reflection beam because the exact locations and times of activity of the devices are unknown in GF transmission. In order to study the impact of the phase-shift design on the device activity detection, we derive a generalized likelihood ratio test (GLRT) based detector and present an analytical expression for the probability of detection. Assuming knowledge of statistical CSI, we formulate an optimization problem for the phase-shift design for maximization of the guaranteed probability of detection for all locations within a given coverage area. To tackle the non-convexity of the problem, we propose two different approximations of the objective function. The first approximation leads to a design that aims to reduce the variations of the end-to-end channel while taking system parameters such as transmit power, noise power, and probability of false alarm into account. The second approximation can be adopted for versatile RIS deployments because it only depends on the line-of-sight component of the end-to-end channel and is not affected by system parameters. For comparison, we also consider a phase-shift design maximizing the average channel gain and a baseline analytical phase-shift design for large blocked areas. Our performance evaluation shows that the proposed approximations result in phase-shift designs that guarantee high probability of detection across the coverage area and outperform the baseline designs.

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arXiv2022

Power Scaling Law for Optical IRSs and Comparison with Optical Relays

The line-of-sight (LOS) requirement of free-space optical (FSO) systems can be relaxed by employing optical relays and optical intelligent reflecting surfaces (IRSs). Unlike radio frequency (RF) IRSs, which typically exhibit a quadratic power scaling law, the power reflected from FSO IRSs and collected at the receiver lens may scale quadratically or linearly with the IRS size or may even saturate at a constant value. We analyze the power scaling law for optical IRSs and unveil its dependence on the wavelength, transmitter (Tx)-to-IRS and IRS-to-receiver (Rx) distances, beam waist, and lens size. We compare optical IRSs in different power scaling regimes with optical relays in terms of the outage probability, diversity and coding gains, and optimal placement. Our results show that, at the expense of a higher hardware complexity, relay-assisted FSO links yield a better outage performance at high signal-to-noise-ratios (SNRs), but optical IRSs can achieve a higher performance at low SNRs. Moreover, while it is optimal to place relays equidistant from Tx and Rx, the optimal location of IRSs depends on the power scaling regime they operate in.

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arXiv2022

Chemical Reactions-based Detection Mechanism for Molecular Communications

In molecular communications, the direct detection of signaling molecules may be challenging due to a lack of suitable sensors and interference in the environment. Motivated by research in molecular biology, we investigate an indirect detection mechanism using chemical reactions between the signaling molecules and a molecular probe to produce an easy-to-measure product at the receiver. We consider two implementations of the proposed detection mechanism, i.e., unrestricted probe movement and probes restricted to a volume around the receiver. The reaction-diffusion equations describing the concentrations of the reactant and product molecules in the system are non-linear and coupled, and cannot be solved in closed form. Therefore, we develop an efficient iterative algorithm by discretizing the time variable and solving for the space variables of the equations in each time step. Our results show that the concentrations of the product molecules and the signalling molecules share a similar characteristic over time, i.e., a single peak and a long tail. The peak and tail values of the product molecule concentration can be controlled by choosing probes with suitable parameters. By carefully choosing the molecular probe and optimizing the decision threshold, the BER can be improved significantly and outperform that of a direct detection system.

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arXiv2022

Compressive Sensing-Based Recovery of Molecular Mixtures with Cross-Reactive Receptor Arrays

In this paper, we propose a novel concept for engineered molecular communication (MC) systems inspired by animal olfaction. We focus on a multi-user scenario where transmitters employ unique mixtures of different types of signaling molecules to convey their messages to a central receiver, which is equipped with an array comprising $R$ different types of receptors to detect the emitted molecule mixtures. The hardware complexity of an MC system employing \textit{orthogonal} molecule-receptor pairs would linearly scale with the number of signaling molecule types $Q$ (i.e., $R=Q$). Natural olfaction systems avoid such high complexity by employing arrays of \textit{cross-reactive} receptors, where each type of molecule activates multiple types of receptors and each type of receptor is predominantly activated by multiple types of molecules albeit with different activation strengths. For instance, the human olfactory system is believed to discriminate several thousands of chemicals using only a few hundred receptor types, i.e., $Q\gg R$. Motivated by this observation, we first develop an end-to-end MC channel model that accounts for the key properties of olfaction. Subsequently, we formulate the molecule mixture recovery as a convex compressive sensing (CS) problem which can be efficiently solved via available numerical solvers. Our simulation results confirm the efficiency of the proposed CS problem for the recovery of the molecular mixture signal and quantify the system performance for various system parameters.

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arXiv2022

Near-Field Hierarchical Beam Management for RIS-Enabled Millimeter Wave Multi-Antenna Systems

In this paper, we present a low overhead beam management approach for near-field millimeter-wave multi-antenna communication systems enabled by Reconfigurable Intelligent Surfaces (RISs). We devise a novel variable-width hierarchical phaseshift codebook suitable for both the near- and far-field of the RIS, and present a fast alignment algorithm for the RIS phase shifts and the transceiver beamformers. Indicative performance evaluation results are shown, verifying the effectiveness of the proposed approach in comparison with various benchmark schemes.

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arXiv2022

Experimental System for Molecular Communication in Pipe Flow With Magnetic Nanoparticles

In the emerging field of molecular communication (MC), testbeds are needed to validate theoretical concepts, motivate applications, and guide further modeling efforts. To this end, this paper presents a flexible and extendable in-vessel testbed for flow-based macroscopic MC, abstractly modeling, e.g., a part of a chemical reactor or a blood vessel. Signaling is based on injecting non-reactive superparamagnetic iron oxide nanoparticles (SPIONs) dispersed in an aqueous suspension into a tube with background flow. A commercial magnetic susceptometer is used for non-intrusive downstream signal reception. To shed light on the operation of the testbed, we identify the physical mechanisms governing the transmission, propagation, and reception of the information-carrying SPIONs. Moreover, to facilitate system design, we propose a closed-form parametric expression for the end-to-end channel impulse response (CIR). The proposed CIR model is shown to consistently capture the experimentally observed distance-dependent impulse response peak heights and peak decays for transmission distances from 5cm to 40cm. Moreover, to validate our testbed, reliable communication is demonstrated based on experimental data for model-agnostic and model-based detection methods.

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arXiv2022

Olfaction-inspired MCs: Molecule Mixture Shift Keying and Cross-Reactive Receptor Arrays

In this paper, we propose a novel concept for engineered molecular communication (MC) systems inspired by animal olfaction. We focus on a multi-user scenario where several transmitters wish to communicate with a central receiver. We assume that each transmitter employs a unique mixture of different types of signaling molecules to represent its message and the receiver is equipped with an array comprising $R$ different types of receptors in order to detect the emitted molecule mixtures. The design of an MC system based on \textit{orthogonal} molecule-receptor pairs implies that the hardware complexity of the receiver linearly scales with the number of signaling molecule types $Q$ (i.e., $R=Q$). Natural olfaction systems avoid such high complexity by employing arrays of \textit{cross-reactive} receptors, where each type of molecule activates multiple types of receptors and each type of receptor is predominantly activated by multiple types of molecules albeit with different activation strengths. For instance, the human olfactory system is believed to discriminate several thousands of chemicals using only a few hundred receptor types, i.e., $Q\gg R$. Motivated by this observation, we first develop an end-to-end MC channel model that accounts for the key properties of olfaction. Subsequently, we present the proposed transmitter and receiver designs. In particular, given a set of signaling molecules, we develop algorithms that allocate molecules to different transmitters and optimize the mixture alphabet for communication. Moreover, we formulate the molecule mixture recovery as a convex compressive sensing problem which can be efficiently solved via available numerical solvers.

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arXiv2022

Deterministic Identification for Molecular Communications over the Poisson Channel

Various applications of molecular communications (MC) are event-triggered, and, as a consequence, the prevalent Shannon capacity may not be the right measure for performance assessment. Thus, in this paper, we motivate and establish the identification capacity as an alternative metric. In particular, we study deterministic identification (DI) for the discrete-time Poisson channel (DTPC), subject to an average and a peak power constraint, which serves as a model for MC systems employing molecule counting receivers. It is established that the codebook size for this channel scales as $2^{(n\log n)R}$, where $n$ and $R$ are the codeword length and coding rate, respectively. Lower and upper bounds on the DI capacity of the DTPC are developed. The obtained large capacity of the DI channel sheds light on the performance of natural DI systems such as natural olfaction, which are known for their extremely large chemical discriminatory power in biology. Furthermore, numerical simulations for the empirical miss-identification and false identification error rates are provided for finite length codes. This allows us to quantify the scale of error reduction in terms of the codeword length.

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arXiv2021

Low-to-Zero-Overhead IRS Reconfiguration: Decoupling Illumination and Channel Estimation

Most algorithms developed so far for the optimization of Intelligent Reflecting Surfaces (IRSs) require knowledge of full Channel State Information (CSI). However, the resulting acquisition overhead constitutes a major bottleneck for the realization of IRS-assisted wireless systems in practice. In contrast, in this paper, focusing on downlink transmissions from a Base Station (BS) to a Mobile User (MU) that is located in a blockage region, we propose to optimize the IRS for illumination of the area centered around the MU. Hence, the proposed design requires the estimation of the MU's position and not the full CSI. For a given IRS phase-shift configuration, the end-to-end BS-IRS-MU channel can then be estimated using conventional channel estimation techniques. The IRS reconfiguration overhead for the proposed scheme depends on the MU mobility as well as how wide the coverage of the IRS illumination is. Therefore, we develop a general IRS phase-shift design, which is valid for both the near- and far-field regimes and features a parameter for tuning the size of the illumination area. Moreover, we study a special case where the IRS illuminates the entire blockage area, which implies that the IRS phase shifts do not change over time leading to zero overhead for IRS reconfiguration.

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arXiv2021

Degrees of Freedom of the $K$-User Interference Channel in the Presence of Intelligent Reflecting Surfaces

In this paper, we study the degrees of freedom (DoF) region and sum DoF of the time-selective $K$-user interference channel in the presence of intelligent reflecting surfaces (IRSs). We consider four types of IRSs, namely 1) active IRSs, which are able to amplify, attenuate, and add a phase shift to the received signal, 2) passive IRSs, which are able to attenuate and add a phase shift to the received signal, 3) passive lossless IRSs, which are only able to add a phase shift to the received signal, and 4) $\varepsilon$-relaxed passive lossless IRSs, which are able to scale the received signal by a number between $1-\varepsilon$ and $1$ in addition to adding a phase shift. We derive inner and outer bounds for the DoF region and lower and upper bounds for the sum DoF of the $K$-user interference channel in the presence of an active IRS and prove that the maximum value $K$ for the sum DoF can be achieved if the number of IRS elements exceeds a certain finite value. Then, we introduce probabilistic inner and outer bounds for the DoF region and probabilistic lower and upper bounds for the sum DoF of the $K$-user interference channel in the presence of a passive IRS and prove that the lower bound for the sum DoF asymptotically approaches $K$ as the number of IRS elements grows large. For the DoF analysis of passive lossless IRSs, first, we approximate it by the $\varepsilon$-relaxed passive lossless IRS and introduce a probabilistic lower bound for the corresponding sum DoF. We prove that this bound asymptotically tends to $K$. In addition, we define a relaxed type of DoF called $ρ$-limited DoF. We introduce a lower bound for the $ρ$-limited sum DoF of the passive lossless IRS-assisted $K$-user interference channel and prove that this lower bound asymptotically also tends to $K$.

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arXiv2021

Modeling and Design of IRS-Assisted Multi-Link FSO Systems

In this paper, we investigate the modeling and design of intelligent reflecting surface (IRS)-assisted optical communication systems which are deployed to relax the line-of-sight (LOS) requirement in multi-link free space optical (FSO) systems. The FSO laser beams incident on the optical IRSs have a Gaussian power intensity profile and a nonlinear phase profile, whereas the plane waves in radio frequency (RF) systems have a uniform power intensity profile and a linear phase profile. Given these substantial differences, the results available for IRS-assisted RF systems are not applicable to IRS-assisted FSO systems. Therefore, we develop a new analytical channel model for point-to-point IRS-assisted FSO systems based on the Huygens-Fresnel principle. Our analytical model captures the impact of the size, position, and orientation of the IRS as well as its phase shift profile on the end-to-end channel. To allow the sharing of the optical IRS by multiple FSO links, we propose three different protocols, namely the time division (TD), IRS-division (IRSD), and IRS homogenization (IRSH) protocols. The proposed protocols address the specific characteristics of FSO systems including the non-uniformity and possible misalignment of the laser beams. Furthermore, to compare the proposed IRS sharing protocols, we analyze the bit error rate (BER) and the outage probability of IRS-assisted multi-link FSO systems in the presence of inter-link interference. Our simulation results validate the accuracy of the proposed analytical channel model for IRS-assisted FSO systems and confirm that this model is applicable for both large and intermediate IRS-receiver lens distances. Moreover, in the absence of misalignment errors, the IRSD protocol outperforms the other protocols, whereas in the presence of misalignment errors, the IRSH protocol performs significantly better than the IRSD protocol.

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arXiv2021

Intelligent Surface-Aided Transmitter Architectures for Millimeter Wave Ultra Massive MIMO Systems

In this paper, we study two novel massive multiple-input multiple-output (MIMO) transmitter architectures for millimeter wave (mmWave) communications which comprise few active antennas, each equipped with a dedicated radio frequency (RF) chain, that illuminate a nearby large intelligent reflecting/transmitting surface (IRS/ITS). The IRS (ITS) consists of a large number of low-cost and energy-efficient passive antenna elements which are able to reflect (transmit) a phase-shifted version of the incident electromagnetic field. Similar to lens array (LA) antennas, IRS/ITS-aided antenna architectures are energy efficient due to the almost lossless over-the-air connection between the active antennas and the intelligent surface. However, unlike for LA antennas, for which the number of active antennas has to linearly grow with the number of passive elements (i.e., the lens aperture) due to the non-reconfigurablility (i.e., non-intelligence) of the lens, for IRS/ITS-aided antennas, the reconfigurablility of the IRS/ITS facilitates scaling up the number of radiating passive elements without increasing the number of costly and bulky active antennas. We show that the constraints that the precoders for IRS/ITS-aided antennas have to meet differ from those of conventional MIMO architectures. Taking these constraints into account and exploiting the sparsity of mmWave channels, we design two efficient precoders; one based on maximizing the mutual information and one based on approximating the optimal unconstrained fully digital (FD) precoder via the orthogonal matching pursuit algorithm. Furthermore, we develop a power consumption model for IRS/ITS-aided antennas that takes into account the impacts of the IRS/ITS imperfections, namely the spillover loss, taper loss, aperture loss, and phase shifter loss.

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arXiv2021

Intelligent Reflecting Surface-assisted Free-space Optical Communications

Free-space optical (FSO) systems are able to offer the high data-rate, secure, and cost-efficient communication links required for applications such as wireless front- and backhauling for 5G and 6G communication networks. Despite the substantial advancement of FSO systems over the past decades, the requirement of a line-of-sight connection between transmitter and receiver remains a key limiting factor for their deployment. In this paper, we discuss the potential role of intelligent reflecting surfaces (IRSs) as a solution to relax this requirement. We present an overview of existing optical IRS technologies; compare optical IRSs with radio-frequency IRSs and optical relays; and identify various open problems for future research on IRS-assisted FSO communications.

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arXiv2021

IRS-Assisted Active Device Detection

This paper studies intelligent reflecting surface (IRS) assisted active device detection. Since the locations of the devices are a priori unknown, optimal IRS beam alignment is not possible and a worst-case design for a given coverage area is developed. To this end, we propose a generalized likelihood ratio test (GLRT) detection scheme and an IRS phase-shift design that minimizes the worst-case probability of misdetection. In addition to the proposed optimization-based phase-shift design, we consider two alternative suboptimal designs based on closed-form expressions for the IRS phase shifts. Our performance analysis establishes the superiority of the optimization-based design, especially for large coverage areas. Furthermore, we investigate the impact of scatterers on the proposed line-of-sight based design using simulations.

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arXiv2021

Area Rate Efficiency in Molecular Communications

We consider a multiuser diffusion-based molecular communication (MC) system where multiple spatially distributed transmitter (TX)-receiver (RX) pairs establish point-to-point communication links employing the same type of signaling molecules. To realize the full potential of such a system, an in-depth understanding of the interplay between the spatial user density and inter-user interference (IUI) and its impact on system performance in an asymptotic regime with large numbers of users is needed. In this paper, we adopt a three-dimensional (3-D) system model with multiple independent and spatially distributed point-to-point transmission links, where both the TXs and RXs are positioned according to a regular hexagonal grid, respectively. Based on this model, we first derive an expression for the channel impulse responses (CIRs) of all TX-RX links in the system. Then, we provide the maximum likelihood (ML) decision rule for the RXs and show that it reduces to a threshold-based detector. We derive an analytical expression for the corresponding detection threshold which depends on the statistics of the MC channel and the statistics of the IUI. Furthermore, we derive an analytical expression for the bit error rate (BER) and the achievable rate of a single transmission link. Finally, we propose a new performance metric, which we refer to as area rate efficiency (ARE), that captures the tradeoff between the user density and IUI. The ARE characterizes how efficiently given TX and RX areas are used for information transmission and is given in terms of bits per area unit. We show that there exists an optimal user density for maximization of the ARE. Results from particle-based and Monte Carlo simulations validate the accuracy of the expressions derived for the CIR, optimal detection threshold, BER, and ARE.

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arXiv2021

Optimal Resource Allocation Design for Large IRS-Assisted SWIPT Systems: A Scalable Optimization Framework

In this paper, we study the optimal resource allocation algorithm design for large intelligent reflecting surface (IRS)-assisted simultaneous wireless information and power transfer (SWIPT) systems. To facilitate efficient system design for large IRSs, instead of jointly optimizing all the IRS elements, we partition the IRS into several tiles and employ a scalable optimization framework comprising an offline design stage and an online optimization stage. In the offline stage, the IRS elements of each tile are jointly designed to support a set of different phase shift configurations, referred to as transmission modes, while the best transmission mode is selected from the set for each tile in the online stage. Given a transmission mode set, we aim to minimize the total base station (BS) transmit power by jointly optimizing the beamforming and the transmission mode selection policy taking into account the quality-of-service requirements of information decoding and non-linear energy harvesting receivers, respectively. Although the resource allocation algorithm design is formulated as a non-convex combinatorial optimization problem, we solve it optimally by applying the branch-and-bound (BnB) approach which entails a high computational complexity. To strike a balance between optimality and computational complexity, we also develop an efficient suboptimal algorithm capitalizing on the penalty method and successive convex approximation. Our simulation results show that the proposed designs enable considerable power savings compared to several baseline schemes. Moreover, our results reveal that by properly adjusting the numbers of tiles and transmission modes, the proposed scalable optimization framework indeed facilitates online design for large IRSs.

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arXiv2021

Smart and Reconfigurable Wireless Communications: From IRS Modeling to Algorithm Design

Intelligent reflecting surfaces (IRSs) have been introduced into wireless communications systems due to their great potential to smartly customize and reconfigure radio propagation environments in a cost-effective manner. Despite the promising advantages of IRSs, academic research on IRSs is still in its infancy. In particular, the design and analysis of IRS-assisted wireless communication systems critically depend on an accurate and tractable modeling of the IRS. In this article, we first present and compare three IRS models, namely the conventional independent diffusive scatterer-based model, physics-based model, and impedance network-based model, in terms of their accuracy, tractability, and hardware complexity. Besides, a new framework based on partitioning the IRS into tiles and employing codebooks of transmission modes is introduced to enable scalable IRS optimization. Then, we investigate the impact of the three considered IRS models on system design, where several crucial technical challenges for the efficient design of IRS-assisted wireless systems are identified and the corresponding solutions are unraveled. Furthermore, to illustrate the properties of the considered models and the efficiency of the proposed solution concepts, IRS-assisted secure wireless systems and simultaneous wireless information and power transfer (SWIPT) systems are studied in more detail. Finally, several promising future research directions for IRS-assisted wireless systems are highlighted.

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