arXiv subjects

Amr El-Keyi

Publications and source records attributed to Amr El-Keyi.

At least 19 recordsLinked to original sources

arXiv2025

Matrix Pencil-Based DoA Estimation for Hybrid Receivers in Snapshot-Limited Scenarios

The goal of this paper is to estimate the directions of arrival (DoAs) for hybrid analog/digital (HAD) receivers when the number of snapshots is too small for statistical averaging to be reliable. This goal is achieved in fully-digital receivers by employing the matrix pencil method (MPM). Unfortunately, the MPM cannot be directly applied in HAD receivers because of the entanglement induced by the underlying analog combiners on the output signals. Furthermore, these analog combiners project the received signal onto a low-dimensional space, jeopardizing the reception of signals arriving from particular DoA ranges. To circumvent these difficulties, we propose two approaches to enable the MPM to extract the DoAs in HAD receivers. The two approaches avoid severe attenuation induced by low-dimensional projection by cycling over an exhaustive set of analog combiners, collectively spanning the entire space. The first approach can be applied to both fully-connected (FC) and partially-connected (PC) HADs and relies on the availability of periodic, potentially unknown, signals to disentangle the output of the HAD receiver. The second approach applies to PC-HADs only, and eliminates contingency on periodic signals by exploiting the underlying block diagonal structure. The superiority of the proposed approaches is demonstrated via numerical simulations and comparisons with the Cram\'er-Rao lower bound.

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arXiv2025

Energy Efficient Wireless Communications by Harnessing Huygens' Metasurfaces

Ambitions for the next generation of wireless communication include high data rates, low latency, ubiquitous access, ensuring sustainability (in terms of consumption of energy and natural resources), all while maintaining a reasonable level of implementation complexity. Achieving these goals necessitates reforms in cellular networks, specifically in the physical layer and antenna design. The deployment of transmissive metasurfaces at basestations (BSs) presents an appealing solution, enabling beamforming in the radiated wave domain, minimizing the need for energy-hungry RF chains. Among various metasurface-based antenna designs, we propose using Huygens' metasurface-based antennas (HMAs) at BSs. Huygens' metasurfaces offer an attractive solution for antennas because, by utilizing Huygens' equivalence principle, they allow independent control over both the amplitude and phase of the transmitted electromagnetic wave. In this paper, we investigate the fundamental limits of HMAs in wireless networks by integrating electromagnetic theory and information theory within a unified analytical framework. Specifically, we model the unique electromagnetic characteristics of HMAs and incorporate them into an information-theoretic optimization framework to determine their maximum achievable sum rate. By formulating an optimization problem that captures the impact of HMA's hardware constraints and electromagnetic properties, we quantify the channel capacity of HMA-assisted systems. We then compare the performance of HMAs against phased arrays and other metasurface-based antennas in both rich scattering and realistic 3GPP channels, highlighting their potential in improving spectral and energy efficiency.

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arXiv2024

Hardware Limitations of Dynamic Metasurface Antennas in the Uplink: A Comparative Study

Dynamic Metasurface Antennas (DMAs) have emerged as promising candidates for basestation deployment in the next generation of wireless communications. While overlooking the practical and hardware limitations of DMA, previous studies have highlighted DMAs' potential to deliver high data rates while maintaining low power consumption. In this paper, we address this oversight by analyzing the impact of practical hardware limitations such as antenna efficiency, power consumed in required components, processing limitations, etc. Specifically, we investigate DMA-assisted wireless communications in the uplink and propose a model which accounts for these hardware limitations. To do so, we propose a concise model to characterize the power consumption of a DMA. For a fair assessment, we propose a wave-domain combiner, based on holography theory, to maximize the achievable sum rate of DMA-assisted antennas. We compare the achievable sum rate and energy efficiency of DMA antennas with that of a partially connected hybrid phased array. Our findings reveal the true potential of DMAs when accounting for the limitations of both designs.

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arXiv2024

Uplink Wave-Domain Combiner for Stacked Intelligent Metasurfaces Accounting for Hardware Limitations

Refractive metasurfaces (RMTSs) offer a promising solution to improve energy efficiency of wireless systems. To address the limitations of single-layer RMTS, stacked intelligent metasurfaces (SIMs), which form the desired precoder and combiner in the wave domain, have been proposed. However, previous analyses overlooked hardware non-idealities that significantly affect SIM performance. In this paper, we study the achievable sum-rate of SIM antennas in an uplink scenario, accounting for hardware constraints. We propose a system model that includes noise and hardware effects, formulate a non-convex sum-rate optimization problem, and solve it using gradient ascent and interior point methods. We compare SIMs and digital phased arrays (DPAs) under Rayleigh fading and 3GPP channels with two conditions: equal number of RF chains and equal physical aperture size. Our results show SIMs outperform DPAs under equal number of RF chains but underperform DPAs with equal aperture size.

eess.SP↗

arXiv2018

Spatial Configuration of Agile Wireless Networks with Drone-BSs and User-in-the-loop

Agile networking can reduce over-engineering, costs, and energy waste. Towards that end, it is vital to exploit all degrees of freedom of wireless networks efficiently, so that service quality is not sacrificed. In order to reap the benefits of flexible networking, we propose a spatial network configuration scheme (SNC), which can result in efficient networking; both from the perspective of network capacity, and profitability. First, SNC utilizes the drone-base-stations (drone-BSs) to configure access points. Drone-BSs are shifting paradigms of heterogeneous wireless networks by providing radically flexible deployment opportunities. On the other hand, their limited endurance and potential high cost increase the importance of utilizing drone-BSs efficiently. Therefore, secondly, user mobility is exploited via user-in-the-loop (UIL), which aims at influencing users' mobility by offering incentives. The proposed uncoordinated SNC is a computationally efficient method, yet, it may be insufficient to exploit the synergy between drone-BSs and UIL. Hence, we propose joint SNC, which increases the performance gain along with the computational cost. Finally, semi-joint SNC combines benefits of joint SNC, with computational efficiency. Numerical results show that semi-joint SNC is two orders of magnitude times faster than joint SNC, and more than 15 percent profit can be obtained compared to conventional systems.

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arXiv2017

Energy-Efficient Cooperative Cognitive Relaying Schemes for Cognitive Radio Networks

We investigate a cognitive radio network in which a primary user (PU) may cooperate with a cognitive radio user (i.e., a secondary user (SU)) for transmissions of its data packets. The PU is assumed to be a buffered node operating in a time-slotted fashion where the time is partitioned into equal-length slots. We develop two schemes which involve cooperation between primary and secondary users. To satisfy certain quality of service (QoS) requirements, users share time slot duration and channel frequency bandwidth. Moreover, the SU may leverage the primary feedback message to further increase both its data rate and satisfy the PU QoS requirements. The proposed cooperative schemes are designed such that the SU data rate is maximized under the constraint that the PU average queueing delay is maintained less than the average queueing delay in case of non-cooperative PU. In addition, the proposed schemes guarantee the stability of the PU queue and maintain the average energy emitted by the SU below a certain value. The proposed schemes also provide more robust and potentially continuous service for SUs compared to the conventional practice in cognitive networks where SUs transmit in the spectrum holes and silence sessions of the PUs. We include primary source burstiness, sensing errors, and feedback decoding errors to the analysis of our proposed cooperative schemes. The optimization problems are solved offline and require a simple 2-dimensional grid-based search over the optimization variables. Numerical results show the beneficial gains of the cooperative schemes in terms of SU data rate and PU throughput, average PU queueing delay, and average PU energy savings.

cs.NI↗

arXiv2017

3D Placement of an Unmanned Aerial Vehicle Base Station for Maximum Coverage of Users with Different QoS Requirements

The need for a rapid-to-deploy solution for providing wireless cellular services can be realized by unmanned aerial vehicle base stations (UAV-BSs). To the best of our knowledge, this letter is the first in literature that studies a novel 3D UAV-BS placement that maximizes the number of covered users with different Quality-of-Service requirements. We model the placement problem as a multiple circles placement problem and propose an optimal placement algorithm that utilizes an exhaustive search (ES) over a one-dimensional parameter in a closed region. We also propose a low-complexity algorithm, namely, maximal weighted area (MWA) algorithm to tackle the placement problem. Numerical simulations are presented showing that the MWA algorithm performs very close to the ES algorithm with a significant complexity reduction.

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arXiv2017

3D Placement of an Unmanned Aerial Vehicle Base Station (UAV-BS) for Energy-Efficient Maximal Coverage

Unmanned Aerial Vehicle mounted base stations (UAV-BSs) can provide wireless services in a variety of scenarios. In this letter, we propose an optimal placement algorithm for UAV-BSs that maximizes the number of covered users using the minimum transmit power. We decouple the UAV-BS deployment problem in the vertical and horizontal dimensions without any loss of optimality. Furthermore, we model the UAV-BS deployment in the horizontal dimension as a circle placement problem and a smallest enclosing circle problem. Simulations are conducted to evaluate the performance of the proposed method for different spatial distributions of the users.

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arXiv2017

Degrees of Freedom in Cached MIMO Relay Networks With Multiple Base Stations

The ability of physical layer relay caching to increase the degrees of freedom (DoF) of a single cell was recently illustrated. In this paper, we extend this result to the case of multiple cells in which a caching relay is shared among multiple non-cooperative base stations (BSs). In particular, we show that a large DoF gain can be achieved by exploiting the benefits of having a shared relay that cooperates with the BSs. We first propose a cache-assisted relaying protocol that improves the cooperation opportunity between the BSs and the relay. Next, we consider the cache content placement problem that aims to design the cache content at the relay such that the DoF gain is maximized. We propose an optimal algorithm and a near-optimal low-complexity algorithm for the cache content placement problem. Simulation results show significant improvement in the DoF gain using the proposed relay-caching protocol.

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arXiv2016

Optimal Beamforming for MIMO Shared Relaying in Downlink Cellular Networks with ARQ

In this paper, we study the performance of the downlink of a cellular network with automatic repeat-request (ARQ) and a half duplex decode-and-forward shared relay. In this system, two multiple-input-multiple-output (MIMO) base stations serve two single antenna users. A MIMO shared relay retransmits the lost packets to the target users. First, we study the system with direct retransmission from the base station and derive a closed form expression for the outage probability of the system.We show that the direct retransmission can overcome the fading, however, it cannot overcome the interference. After that, we invoke the shared relay and design the relay beamforming matrices such that the signal-to-interference-and-noise ratio (SINR) is improved at the users subject to power constraints on the relay. In the case when the transmission of only one user fails, we derive a closed form solution for the relay beamformers. On the other hand when both transmissions fail, we pose the beamforming problem as a sequence of non-convex feasibility problems. We use semidefinite relaxation (SDR) to convert each feasibility problem into a convex optimization problem. We ensure a rank one solution, and hence, there is no loss of optimality in SDR. Simulation results are presented showing the superior performance of the proposed relay beamforming strategy compared to direct ARQ system in terms of the outage probability.

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arXiv2016

Optimal Energy Allocation For Delay-Constrained Traffic Over Fading Multiple Access Channels

In this paper, we consider a multiple-access fading channel where $N$ users transmit to a single base station (BS) within a limited number of time slots. We assume that each user has a fixed amount of energy available to be consumed over the transmission window. We derive the optimal energy allocation policy for each user that maximizes the total system throughput under two different assumptions on the channel state information. First, we consider the offline allocation problem where the channel states are known a priori before transmission. We solve a convex optimization problem to maximize the sum-throughput under energy and delay constraints. Next, we consider the online allocation problem, where the channels are causally known to the BS and obtain the optimal energy allocation via dynamic programming when the number of users is small. We also develop a suboptimal resource allocation algorithm whose performance is close to the optimal one. Numerical results are presented showing the superiority of the proposed algorithms over baseline algorithms in various scenarios.

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arXiv2016

Asymmetric Degrees of Freedom of the Full-Duplex MIMO 3-Way Channel with Unicast and Broadcast Messages

In this paper, we characterize the asymmetric total degrees of freedom (DoF) of a multiple-input multiple-output (MIMO) 3-way channel. Each node has a separate-antenna full-duplex MIMO transceiver with a different number of antennas, where each antenna can be configured for either signal transmission or reception. We study this system under two message configurations; the first configuration is when each node has two unicast messages to be delivered to the two other nodes, while the second configuration is when each node has two unicast messages as well as one broadcast message to be delivered to the two other nodes. For each configuration, we first derive upper bounds on the total DoF of the system. Cut-set bounds in conjunction with genie-aided bounds are derived to characterize the achievable total DoF. Afterwards, we analytically derive the optimal number of transmit and receive antennas at each node to maximize the total DoF of the system, subject to the total number of antennas at each node. Finally, the achievable schemes for each configuration are constructed. The proposed schemes are mainly based on zero-forcing and null-space transmit beamforming.

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arXiv2016

Proactive Location-Based Scheduling of Delay-Constrained Traffic Over Fading Channels

In this paper, proactive resource allocation based on user location for point-to-point communication over fading channels is introduced, whereby the source must transmit a packet when the user requests it within a deadline of a single time slot. We introduce a prediction model in which the source predicts the request arrival $T_p$ slots ahead, where $T_p$ denotes the prediction window (PW) size. The source allocates energy to transmit some bits proactively for each time slot of the PW with the objective of reducing the transmission energy over the non-predictive case. The requests are predicted based on the user location utilizing the prior statistics about the user requests at each location. We also assume that the prediction is not perfect. We propose proactive scheduling policies to minimize the expected energy consumption required to transmit the requested packets under two different assumptions on the channel state information at the source. In the first scenario, offline scheduling, we assume the channel states are known a-priori at the source at the beginning of the PW. In the second scenario, online scheduling, it is assumed that the source has causal knowledge of the channel state. Numerical results are presented showing the gains achieved by using proactive scheduling policies compared with classical (reactive) networks. Simulation results also show that increasing the PW size leads to a significant reduction in the consumed transmission energy even with imperfect prediction.

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arXiv2016

On the Degrees of Freedom of SISO X-networks with Synergistic Alternating Channel State Information at transmitters

In this paper, we consider the two-user single-input single-output (SISO) X-channel and $K$-user SISO X-network in fast fading environment. It is assumed that the transmitters have access to synergistic alternating channel state information (CSI). Specifically, the CSIT alternates between three states, namely, perfect, delayed and no-CSIT, in a certain manner to enable these states to work together cooperatively. These states are associated with fractions of time denoted by $λ_P$, $λ_D$ \text{and} $λ_N$, respectively. For the two-user $X$-channel, simple upper bound is developed to prove the tightness of the achievability result of $4/3$ DoF under a certain distribution of the availability of three CSIT states for $Λ(λ_P=1/3, λ_D= 1/3, λ_N=1/3)$. For the $K$-user $X$-network, it is shown that the sum Degrees of freedom (DoF) is at least $2K/(K + 1)$, using two-phase transmission schemes over finite symbols channel extension and under the same distribution of the availability of $Λ(λ_P=1/3, λ_D= 1/3, λ_N=1/3)$.This achievability result, can be considered as a tight lower bound, coincides with the best lower bound known for the same network but with partial output feedback in stead of alternating CSIT. Hence, we show that the role of synergistic alternating CSIT with distribution $Λ(1/3,1/3,1/3)$ is equivalent to the partial output feedback. Also, this lower bound is strictly better than the best lower bound known for the case of delayed CSI assumption for all values of $K$. All the proposed transmission schemes are based on two phases transmission strategy, namely, interference creation and interference resurrection, which exploit the synergy of instantaneous CSI and delay CSIT to retrospectively align interference in the subsequent channel uses.

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arXiv2016

Achievable Degrees of Freedom of the K-user MISO Broadcast Channel with Alternating CSIT via Interference Creation-Resurrection

Channel state information at the transmitter affects the degrees of freedom of the wireless networks. In this paper, we analyze the DoF for the K-user multiple-input single-output (MISO) broadcast channel (BC) with synergistic alternating channel state information at the transmitter (CSIT). Specifically, the CSIT of each user alternates between three states, namely, perfect CSIT (P), delayed CSIT (D) and no CSIT (N) among different time slots. For the K-user MISO BC, we show that the total achievable degrees of freedom (DoF) are given by $\frac{K^{2}}{2K-1}$ through utilizing the synergistic benefits of CSIT patterns. We compare the achievable DoF with results reported previously in the literature in the case of delayed CSIT and hybrid CSIT models.

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arXiv2016

On Optimizing Cooperative Cognitive User Performance under Primary QoS Constraints

We study the problem of optimizing the performance of cognitive radio users with opportunistic real-time applications subject to primary users quality-of-service (QoS) constraints. Two constrained optimization problems are formulated; the first problem is maximizing the secondary user throughput while the second problem is minimizing the secondary user average delay, subject to a common constraint on the primary user average delay. In spite of the complexity of the optimization problems, due to their non-convexity, we transform the first problem into a set of linear programs and the second problem into a set of quasiconvex optimization problems. We prove that both problems are equivalent with identical feasible sets and optimal solutions. We show, through numerical results, that the proposed cooperation policy represents the best compromise between enhancing the secondary users QoS and satisfying the primary users QoS requirements.

cs.NI↗

arXiv2016

Efficient 3-D Placement of an Aerial Base Station in Next Generation Cellular Networks

Agility and resilience requirements of future cellular networks may not be fully satisfied by terrestrial base stations in cases of unexpected or temporary events. A promising solution is assisting the cellular network via low-altitude unmanned aerial vehicles equipped with base stations, i.e., drone-cells. Although drone-cells provide a quick deployment opportunity as aerial base stations, efficient placement becomes one of the key issues. In addition to mobility of the drone-cells in the vertical dimension as well as the horizontal dimension, the differences between the air-to-ground and terrestrial channels cause the placement of the drone-cells to diverge from placement of terrestrial base stations. In this paper, we first highlight the properties of the dronecell placement problem, and formulate it as a 3-D placement problem with the objective of maximizing the revenue of the network. After some mathematical manipulations, we formulate an equivalent quadratically-constrained mixed integer non-linear optimization problem and propose a computationally efficient numerical solution for this problem. We verify our analytical derivations with numerical simulations and enrich them with discussions which could serve as guidelines for researchers, mobile network operators, and policy makers.

math.OC↗

arXiv2016

Interactive Multiple Model Estimation of Doubly-Selective Channels for OFDM systems

In this paper, we propose an algorithm for channel estimation, acquisition and tracking, for orthogonal frequency division multiplexing (OFDM) systems. The proposed algorithm is suitable for vehicular communications that encounter very high mobility. A preamble sequence is used to derive an initial estimate of the channel using least squares (LS). The temporal variation of the channel within one OFDM symbol is approximated by two complex exponential basis expansion models (CE-BEM). One of the Fourier-based BEMs is intended to capture the low frequencies in the channel (slow variations corresponding to low Doppler), while the other is destined to capture high frequencies (fast variations corresponding to high Doppler). Kalman filtering is employed to track the BEM coefficients iteratively on an OFDM symbol-by-symbol basis. An interactive multiple model (IMM) estimator is implemented to dynamically mix the estimates obtained by the two Kalman filters, each of which matched to one of the BEMs. Extensive numerical simulations are conducted to signify the gain obtained by the proposed combining technique.

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