arXiv subjects

Tamer Khattab

Publications and source records attributed to Tamer Khattab.

At least 37 records · Page 2Linked to original sources

arXiv2021

Deep Reinforcement Learning Powered IRS-Assisted Downlink NOMA

In this work, we examine an intelligent reflecting surface (IRS) assisted downlink non-orthogonal multiple access (NOMA) scenario with the aim of maximizing the sum rate of users. The optimization problem at the IRS is quite complicated, and non-convex, since it requires the tuning of the phase shift reflection matrix. Driven by the rising deployment of deep reinforcement learning (DRL) techniques that are capable of coping with solving non-convex optimization problems, we employ DRL to predict and optimally tune the IRS phase shift matrices. Simulation results reveal that IRS assisted NOMA based on our utilized DRL scheme achieves high sum rate compared to OMA based one, and as the transmit power increases, the capability of serving more users increases. Furthermore, results show that imperfect successive interference cancellation (SIC) has a deleterious impact on the data rate of users performing SIC. As the imperfection increases by ten times, the rate decreases by more than 10%.

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arXiv2020

On Optimizing the Secrecy Performance of RIS-Assisted Cooperative Networks

Employing reconfigurable intelligent surfaces (RIS) is emerging as a game-changer candidate, thanks to their unique capabilities in improving the power efficiency and supporting the ubiquity of future wireless communication systems. Conventionally, a wireless network design has been limited to the communicating end points, i.e., the transmitter and the receiver. In general, we take advantage of the imposed channel state knowledge to manipulate the transmitted signal and to improve the detection quality at the receiver. With the aid of RISs, and to some extent, the propagation channel has become a part of the design problem. In this paper, we consider a single-input single-output cooperative network and investigate the effect of using RISs in enhancing the physical layer security of the system. Specifically, we formulate an optimization problem to study the effectiveness of the RIS in improving the system secrecy by introducing a weighted variant of the secrecy capacity definition. Numerical simulations are provided to show the design trade-offs and to present the superiority of RIS-assisted networks over the conventional ones in terms of the system's secrecy performance.

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arXiv2020

Smart and Secure Wireless Communications via Reflecting Intelligent Surfaces: A Short Survey

With the emergence of the internet of things (IoT) technology, wireless connectivity should be more ubiquitous than ever. In fact, the availability of wireless connection everywhere comes with security threats that, unfortunately, cannot be handled by conventional cryptographic solutions alone, especially in heterogeneous and decentralized future wireless networks. In general, physical layer security (PLS) helps in bridging this gap by taking advantage of the fading propagation channel. Moreover, the adoption of reconfigurable intelligent surfaces (RIS) in wireless networks makes the PLS techniques more efficient by involving the channel into the design loop. In this paper, we conduct a comprehensive literature review on the RIS-assisted PLS for future wireless communications. We start by introducing the basic concepts of RISs and their different applications in wireless communication networks and the most common PLS performance metrics. Then, we focus on the review and classification of RIS-assisted PLS applications, exhibiting multiple scenarios, system models, objectives, and methodologies. In fact, most of the works in this field formulate an optimization problem to maximize the secrecy rate (SR) or secrecy capacity (SC) at a legitimate user by jointly optimizing the beamformer at the transmitter and the RIS's coefficients, while the differences are in the adopted methodology to optimally/sub-optimally approach the solution. We finalize this survey by presenting some insightful recommendations and suggesting open problems for future research extensions.

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arXiv2020

On the Performance of Quickest Detection Spectrum Sensing: The Case of Cumulative Sum

Quickest change detection (QCD) is a fundamental problem in many applications. Given a sequence of measurements that exhibits two different distributions around a certain flipping point, the goal is to detect the change in distribution around the flipping point as quickly as possible. The QCD problem appears in many practical applications, e.g., quality control, power system line outage detection, spectrum reuse, and resource allocation and scheduling. In this paper, we focus on spectrum sensing as our application since it is a critical process for proper functionality of cognitive radio networks. Relying on the cumulative sum (CUSUM), we derive the probability of detection and the probability of false alarm of CUSUM based spectrum sensing. We show the correctness of our derivations using numerical simulations.

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arXiv2018

Design Challenges of Multi-UAV Systems in Cyber-Physical Applications: A Comprehensive Survey, and Future Directions

Unmanned Aerial Vehicles (UAVs) have recently rapidly grown to facilitate a wide range of innovative applications that can fundamentally change the way cyber-physical systems (CPSs) are designed. CPSs are a modern generation of systems with synergic cooperation between computational and physical potentials that can interact with humans through several new mechanisms. The main advantages of using UAVs in CPS application is their exceptional features, including their mobility, dynamism, effortless deployment, adaptive altitude, agility, adjustability, and effective appraisal of real-world functions anytime and anywhere. Furthermore, from the technology perspective, UAVs are predicted to be a vital element of the development of advanced CPSs. Therefore, in this survey, we aim to pinpoint the most fundamental and important design challenges of multi-UAV systems for CPS applications. We highlight key and versatile aspects that span the coverage and tracking of targets and infrastructure objects, energy-efficient navigation, and image analysis using machine learning for fine-grained CPS applications. Key prototypes and testbeds are also investigated to show how these practical technologies can facilitate CPS applications. We present and propose state-of-the-art algorithms to address design challenges with both quantitative and qualitative methods and map these challenges with important CPS applications to draw insightful conclusions on the challenges of each application. Finally, we summarize potential new directions and ideas that could shape future research in these areas.

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arXiv2018

Estimating the Number of Sources: An Efficient Maximization Approach

Estimating the number of sources received by an antenna array have been well known and investigated since the starting of array signal processing. Accurate estimation of such parameter is critical in many applications that involve prior knowledge of the number of received signals. Information theo- retic approaches such as Akaikes information criterion (AIC) and minimum description length (MDL) have been used extensively even though they are complex and show bad performance at some stages. In this paper, a new algorithm for estimating the number of sources is presented. This algorithm exploits the estimated eigenvalues of the auto correlation coefficient matrix rather than the auto covariance matrix, which is conventionally used, to estimate the number of sources. We propose to use either of a two simply estimated decision statistics, which are the moving increment and moving standard deviation as metric to estimate the number of sources. Then process a simple calculation of the increment or standard deviation of eigenvalues to find the number of sources at the location of the maximum value. Results showed that our proposed algorithms have a better performance in comparison to the popular and more computationally expensive AIC and MDL at low SNR values and low number of collected samples.

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arXiv2018

Non-data-aided SNR Estimation for QPSK Modulation in AWGN Channel

Signal-to-noise ratio (SNR) estimation is an important parameter that is required in any receiver or communication systems. It can be computed either by a pilot signal data-aided approach in which the transmitted signal would be known to the receiver, or without any knowledge of the transmitted signal, which is a non-data-aided (NDA) estimation approach. In this paper, a NDA SNR estimation algorithm for QPSK signal is proposed. The proposed algorithm modifies the existing Signal- to-Variation Ratio (SVR) SNR estimation algorithm in the aim to reduce its bias and mean square error in case of negative SNR values at low number of samples of it. We first present the existing SVR algorithm and then show the mathematical derivation of the new NDA algorithm. In addition, we compare our algorithm to two baselines estimation methods, namely the M2M4 and SVR algorithms, using different test cases. Those test cases include low SNR values, extremely high SNR values and low number of samples. Results showed that our algorithm had a better performance compared to second and fourth moment estimation (M2M4) and original SVR algorithms in terms of normalized mean square error (NMSE) and bias estimation while keeping almost the same complexity as the original algorithms

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arXiv2018

Small Cell Association with Networked Flying Platforms: Novel Algorithms and Performance Bounds

Fifth generation (5G) and beyond-5G (B5G) systems expect coverage and capacity enhancements along with the consideration of limited power, cost and spectrum. Densification of small cells (SCs) is a promising approach to cater these demands of 5G and B5G systems. However, such an ultra dense network of SCs requires provision of smart backhaul and fronthaul networks. In this paper, we employ a scalable idea of using networked flying platforms (NFPs) as aerial hubs to provide fronthaul connectivity to the SCs. We consider the association problem of SCs and NFPs in a SC network and study the effect of practical constraints related to the system and NFPs. Mainly, we show that the association problem is related to the generalized assignment problem (GAP). Using this relation with the GAP, we show the NP-hard complexity of the association problem and further derive an upper bound for the maximum achievable sum data rate. Linear Programming relaxation of the problem is also studied to compare the results with the derived bounds. Finally, two efficient (less complex) greedy solutions of the association problem are presented, where one of them is a distributed solution and the other one is its centralized version. Numerical results show a favorable performance of the presented algorithms with respect to the exhaustive search and derived bounds. The computational complexity comparison of the algorithms with the exhaustive search is also presented to show that the presented algorithms can be practically implemented.

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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.

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arXiv2017

Thresholds Optimization for One-Bit Feedback Multi-User Scheduling

We propose a new one-bit feedback scheme with scheduling decision based on the maximum expected weighted rate. We show the concavity of the $2$-user case and provide the optimal solution which achieves the maximum weighted rate of the users. For the general asymmetric M-user case, we provide a heuristic method to achieve the maximum expected weighted rate. We show that the sum rate of our proposed scheme is very close to the sum rate of the full channel state information case, which is the upper bound performance.

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arXiv2017

Association of Networked Flying Platforms with Small Cells for Network Centric 5G+ C-RAN

5G+ systems expect enhancement in data rate and coverage area under limited power constraint. Such requirements can be fulfilled by the densification of small cells (SCs). However, a major challenge is the management of fronthaul links connected with an ultra dense network of SCs. A cost effective and scalable idea of using network flying platforms (NFPs) is employed here, where the NFPs are used as fronthaul hubs that connect the SCs to the core network. The association problem of NFPs and SCs is formulated considering a number of practical constraints such as backhaul data rate limit, maximum supported links and bandwidth by NFPs and quality of service requirement of the system. The network centric case of the system is considered that aims to maximize the number of associated SCs without any biasing, i.e., no preference for high priority SCs. Then, two new efficient greedy algorithms are designed to solve the presented association problem. Numerical results show a favorable performance of our proposed methods in comparison to exhaustive search.

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arXiv2017

A Distributed Approach for Networked Flying Platform Association with Small Cells in 5G+ Networks

The densification of small-cell base stations in a 5G architecture is a promising approach to enhance the coverage area and facilitate the ever increasing capacity demand of end users. However, the bottleneck is an intelligent management of a backhaul/fronthaul network for these small-cell base stations. This involves efficient association and placement of the backhaul hubs that connects these small-cells with the core network. Terrestrial hubs suffer from an inefficient non line of sight link limitations and unavailability of a proper infrastructure in an urban area. Seeing the popularity of flying platforms, we employ here an idea of using networked flying platform (NFP) such as unmanned aerial vehicles (UAVs), drones, unmanned balloons flying at different altitudes, as aerial backhaul hubs. The association problem of these NFP-hubs and small-cell base stations is formulated considering backhaul link and NFP related limitations such as maximum number of supported links and bandwidth. Then, this paper presents an efficient and distributed solution of the designed problem, which performs a greedy search in order to maximize the sum rate of the overall network. A favorable performance is observed via a numerical comparison of our proposed method with optimal exhaustive search algorithm in terms of sum rate and run-time speed.

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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

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

Secure Degrees of Freedom of the MIMO Multiple Access Channel with Multiple unknown Eavesdroppers

We investigate the secure degrees of freedom (SDoF) of a two-transmitter Gaussian multiple access channel with multiple antennas at the transmitters, the legitimate receiver with the existence of an unknown number of eavesdroppers each with a number of antennas less than or equal to a known value $N_E$. The channel matrices between the legitimate transmitters and the receiver are available everywhere, while the legitimate pair does not know the eavesdroppers' channels matrices. We provide the exact sum SDoF for the considered system. A new comprehensive upperbound is deduced and a new achievable scheme based on utilizing jamming is exploited. We prove that Cooperative Jamming is SDoF optimal even without the instantaneous eavesdropper CSI available at the transmitters.

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arXiv2016

Secure Degrees of Freedom of the Gaussian MIMO Wiretap and MIMO Broadcast Channels with Unknown Eavesdroppers

We investigate the secure degrees of freedom (SDoF) of the wiretap and the K user Gaussian broadcast channels with multiple antennas at the transmitter, the legitimate receivers and an unknown number of eavesdroppers each with a number of antennas less than or equal to a known value NE. The channel matrices between the legitimate transmitter and the receivers are available everywhere, while the legitimate pair have no information about the eavesdroppers' channels. We provide the exact sum SDoF for the considered system. A new comprehensive upperbound is deduced and a new achievable scheme based on utilizing jamming is exploited. We prove that cooperative jamming is SDoF optimal even without the eavesdropper CSI available at the transmitters.

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arXiv2016

On the Secure Degrees of Freedom of the K-user MAC and 2-user Interference Channels

We investigate the secure degrees of freedom (SDoF) of the K-user MIMO multiple access (MAC) and the two user MIMO interference channel. An unknown number of eavesdroppers are trying to decode the messages sent by the transmitters. Each eavesdropper is equipped with a number of antennas less than or equal to a known value NE. The legitimate transmitters and receivers are assumed to have global channel knowledge. We present the sum SDoF of the two user MIMO interference channel. We derive an upperbound on the sum SDoF of the K-user MAC channel and present an achievable scheme that partially meets the derived upperbound.

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arXiv2016

Self-Interference Cancellation Using Time-Domain Phase Noise Estimation in OFDM Full-Duplex Systems

In full-duplex systems, oscillator phase noise (PN) problem is considered the bottleneck challenge that may face the self-interference cancellation (SIC) stage especially when orthogonal frequency division multiplexing (OFDM) transmission scheme is deployed. Phase noise degrades the SIC performance significantly, if not mitigated before or during the SIC technique. The presence of the oscillator phase noise has different impacts on the transmitted data symbol like common phase error (CPE) and inter-carrier interference (ICI). However, phase noise can be estimated and mitigated digitally in either time or frequency domain. Through this work, we propose a novel and simple time domain self-interference (SI) phase noise estimation and mitigation technique. The proposed algorithm is inspired from Wiener filtering in time domain. Simulation results show that the proposed algorithm has a superior performance than the already-existing time-domain or frequency domain PN mitigation solutions with a noticeable reduction in the computational complexity.

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