Hadi Ghauch

• PhD
• Professor (Assistant) at Télécom Paris

This paper proposes methods for Machine Learning (ML)-based Beam Alignment (BA), using low-complexity ML models, and achieves a small pilot overhead. We assume a single-user massive mmWave MIMO, Uplink, using a fully analog architecture. Assuming large-dimension codebooks of possible beam patterns at UE and BS, this data-driven and model-based appr...

This paper proposes a new approach for partial and blind Machine Learning (ML)-based Beam Alignment (BA) for massive mm Wave MIMO. It models an uplink scenario using one-bit quantization through a low complexity fully-analog system architecture. The proposed BA is based on sub-sampled codebooks holding possible beam patterns at UE and BS. We propos...

The growing number of Internet of Thing (IoT) and Ultra-Reliable Low Latency Communications (URLCC) use cases in next generation communication networks calls for the development of efficient Forward Error Correction (FEC) mechanisms. These use cases usually imply using short to mid-sized information blocks and requires low-complexity and/or fast de...

Due to the rising number of sophisticated customer functionalities, electronic control units (ECUs) are increasingly integrated into modern automotive systems. However, the high connectivity between the in-vehicle and the external networks paves the way for hackers who could exploit in-vehicle network protocols' vulnerabilities. Among these protoco...

Network Intrusion Detection Systems (NIDSs) are widely regarded as efficient tools for securing in-vehicle networks against diverse cyberattacks. However, since cyberattacks are always evolving, signature-based intrusion detection systems are no longer adopted. An alternative solution can be the deployment of deep learning based intrusion detection...

This paper proposes a new approach for Machine Learning (ML)-based beam alignment, for a single radio-frequency chain millimeter-wave (mmW) MIMO transmitter (Tx) and receiver (Rx), with massive antennas. Assuming (massive) codebooks of possible beams at Tx and Rx, we propose to sound a very small subset of beams from the Tx/Rx codebooks. We then us...

Network Intrusion Detection Systems are well considered as efficient tools for securing in-vehicle networks against diverse cyberattacks. However, since cyberattack are always evolving, signature-based intrusion detection systems are no longer adopted. An alternative solution can be the deployment of deep learning based intrusion detection system (...

The present invention relates to a method for finding an accurate beam alignment between beams radiated by transmitter antennas and receiver antennas in a Millimeter-Wave Multiple-Input Multiple Output (MIMO) system using Machine Learning methods. Millimeter-Wave MIMO systems are widely used in 5G and are bound to be implemented even more massively...

Data representation techniques have made a substantial contribution to advancing data processing and machine learning (ML). Improving predictive power was the focus of previous representation techniques, which unfortunately perform rather poorly on the interpretability in terms of extracting underlying insights of the data. Recently, the Kolmogorov...

A data representation technique dubbed Kolmogorov model (KM), has been applied to the beam alignment problem in large-dimensional antenna systems. The previous learning-based beam alignment solely focused on utilizing the predictive power of KM, i.e., the capability of predicting the outcome of random variables that are outside the training set, to...

Intrusion Detection Systems are widely used to detect cyberattacks, especially on protocols vulnerable to hacking attacks such as SOME/IP. In this paper, we present a deep learning-based sequential model for offline intrusion detection on SOME/IP application layer protocol. To assess our intrusion detection system, we have generated and labeled a d...

Data representation techniques have made a substantial contribution to advancing data processing and machine learning (ML). Improving predictive power was the focus of previous representation techniques, which unfortunately perform rather poorly on the interpretability in terms of extracting underlying insights of the data. Recently, Kolmogorov mod...

Full-duplex communications have the potential to almost double the spectral efficiency. To realize such a potentiality, the signal separation at base station’s antennas plays an essential role. This paper addresses the fundamentals of such separation by proposing a new smart antenna architecture that allows every antenna to be either shared or sepa...

We present an enhancement to the problem of beam alignment in millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems, based on a modification of the machine learning-based criterion, called Kolmogorov model (KM), previously applied to the beam alignment problem. Unlike the previous KM, whose computational complexity is not scalable...

Inter-operator spectrum sharing in millimeter-wave bands has the potential of substantially increasing the spectrum utilization and providing a larger bandwidth to individual user equipment at the expense of increasing inter-operator interference. Unfortunately, traditional model-based spectrum sharing schemes make idealistic assumptions about inte...

Inter-operator spectrum sharing in millimeter-wave bands has the potential of substantially increasing the spectrum utilization and providing a larger bandwidth to individual user equipment at the expense of increasing inter-operator interference. Unfortunately, traditional model-based spectrum sharing schemes make idealistic assumptions about inte...

In this paper, we study optimization of multi-tone signals for wireless power transfer (WPT) systems. We investigate different non-linear energy harvesting models. Two of them are adopted to optimize the multi-tone signal according to the channel state information available at the transmitter. We show that a second-order polynomial curve-fitting mo...

This chapter is devoted to the use of machine learning (ML) tools to address the spectrum‐sharing problem in cellular networks. The emphasis is on a hybrid approach that combines the traditional model‐based approach with a (ML) data‐driven approach. Taking millimeter‐wave cellular network as an application case, the theoretical analyses and experim...

In this paper, we study optimization of multi-tone signals for wireless power transfer (WPT) systems. We investigate different non-linear energy harvesting models. Two of them are adopted to optimize the multi-tone signal according to the channel state information available at the transmitter. We show that a second-order polynomial curve-fitting mo...

This paper considers a millimeter-wave communication system and proposes an efficient channel estimation scheme with a minimum number of pilots. We model the dynamics of the channel's second-order statistics by a Markov process and develop a learning framework to obtain these dynamics from an unlabeled set of measured angles of arrival and departur...

Next generation 5G cellular networks are envisioned to accommodate an unprecedented massive amount of Internet of things (IoT) and user devices while providing high aggregate multi-user sum rates and low latencies. To this end, cloud radio access networks (CRAN), which operate at short radio frames and coordinate dense sets of spatially distributed...

We summarize our recent findings, where we proposed a framework for learning a Kolmogorov model, for a collection of binary random variables. More specifically, we derive conditions that link outcomes of specific random variables, and extract valuable relations from the data. We also propose an algorithm for computing the model and show its first-o...

The lack of mathematical tractability of Deep Neural Networks (DNNs) has hindered progress towards having a unified convergence analysis of training algorithms, in the general setting. We propose a unified optimization framework for training different types of DNNs, and establish its convergence for arbitrary loss, activation, and regularization fu...

In this work, we investigate the problem of mitigating interference between so-called antenna domains of a cloud radio access network (C-RAN). In contrast to previous work, we turn to an approach utilizing primarily the optimal assignment of users to central processors in a C-RAN deployment. We formulate this user assignment problem as an integer o...

In this work, we investigate the problem of mitigating interference between so-called antenna domains of a cloud radio access network (C-RAN). In contrast to previous work, we turn to an approach utilizing primarily the optimal assignment of users to central processors in a C-RAN deployment. We formulate this user assignment problem as an integer o...

In this paper, we present some contributions from our recent investigation. We address the open issue of interference coordination for sub-28 GHz millimeter-wave communication, by proposing fast-converging coordination algorithms, for dense multi-user multi-cell networks. We propose to optimize a lower bound on the network sum-rate, after investiga...

Next generation cellular networks are expected to improve aggregate multi-user sum rates by a thousand-fold, implying the deployment of cloud radio access networks (CRANs) that consist of a dense set of radio heads. Such a densification of the network inevitably results in high interference coordination complexity and is associated with significant...

Coordinated multipoint (CoMP) transmission and reception has been considered in cellular networks for enabling larger coverage, improved rates and interference mitigation. To harness the gains of coordinated beamforming, fast information exchange over a backhaul connecting the cooperating base stations (BSs) is required. In practice, the bandwidth...

Coordinated multipoint (CoMP) transmission and reception have been considered in cellular networks for enabling larger coverage, improved rates, and interference mitigation. To harness the gains of coordinated beamforming, fast information exchange over a backhaul connecting the cooperating base stations (BSs) is required. In practice, the bandwidt...

To further improve the potential of full-duplex communications, networks may employ multiple antennas at the base station or user equipment. To this end, networks that employ current radios usually deal with self-interference and multi-user interference by beamforming techniques. Although previous works investigated beamforming design to improve sp...

To further improve the potential of full-duplex communications, networks may employ multiple antennas at the base station or user equipment. To this end, networks that employ current radios usually deal with self-interference and multi-user interference by beamforming techniques. Although previous works investigated beamforming design to improve sp...

In this paper, we extend our previous work on user assignment in Cloud-RAN, where we proposed an algorithm for user assignment (UA). We motivate the inherent fairness issue that is present in the latter UA scheme, since some users in the system will never get served. To improve the fairness, we propose that the UA scheme is preceded by a user sched...

MIMO systems in the lower part of the millimetrewave spectrum band (i.e., below 28 GHz) do not exhibit enough directivity and selectively, as their counterparts in higher bands of the spectrum (i.e., above 60 GHz), and thus still suffer from the detrimental effect of interference, on the system sumrate. As such systems exhibit large numbers of ante...

Next generation cellular networks will have to leverage large cell densifications to accomplish the ambitious goals for aggregate multi-user sum rates, for which CRAN architecture is a favored network design. This shifts the attention back to applicable resource allocation (RA), which need to be applicable for very short radio frames, large and den...

There has been growing interest in millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems, which would likely employ hybrid analog-digital precoding with large-scale analog arrays deployed at wide bandwidths. Primary challenges here are how to efficiently estimate the large-dimensional frequency-selective channels and customize the...

Explosive growth in the use of smart wireless devices has necessitated the provision of higher data rates and always-on connectivity, which are the main motivators for designing the fifth generation (5G) systems. To achieve higher system efficiency, massive antenna deployment with tight coordination is one potential strategy for designing 5G system...

In this work, we address the problem of channel estimation and precoding / combining for the so-called hybrid millimeter wave (mmWave) MIMO architecture. Our proposed channel estimation scheme exploits channel reciprocity in TDD MIMO systems, by using echoing, thereby allowing us to implement Krylov subspace methods in a fully distributed way. The...

We study here the problem of Antenna Domain Formation (ADF) in cloud RAN systems, whereby multiple remote radio-heads (RRHs) are each to be assigned to a set of antenna domains (ADs), such that the total interference between the ADs is minimized. We formulate the corresponding optimization problem, by introducing the concept of \emph{interference c...

In this work we highlight the inherent connection between sum-rate maximization problems and separability metrics (arising in the context of linear discriminant analysis), by establishing that maximizing the separability between the signal and interference-plus-noise subspaces, results in optimizing a lower bound on the sum-rate of the network. We...

In this work, we investigate the so-called antenna domain formation problem, as the optimal assignment of users to antenna domains, in cloud radio access networks. We focus on theoretical aspects of the problem, namely, the finding of lower bounds, on the interference leakage in the network. We formulate the antenna domain formation problem as an i...

We study here the problem of Antenna Domain Formation (ADF) in cloud RAN systems, whereby multiple remote radio-heads (RRHs) are each to be assigned to a set of antenna domains (ADs), such that the total interference between the ADs is minimized. We formulate the corresponding optimization problem, by introducing the concept of interference couplin...

Email Print Request Permissions In this work we shed light on the problem of precoding and user selection in MIMO networks. We formulate the problem using the framework of stable matching, whereby a set of users wish to be matched to a set of serving base stations, such as to maximize the sum-rate performance of the system. Though the problem is NP...

In this work, we consider cloud RAN architecture and focus on the downlink of an antenna domain (AD) exposed to external interference from neighboring ADs. With system sum-rate as performance metric, and assuming that perfect channel state information is available at the aggregation node (AN), we implement i) a greedy user association algorithm, an...

Channel estimation and precoding in hybrid analog-digital millimeter-wave (mmWave) MIMO systems is a fundamental problem that has yet to be addressed, before any of the promised gains can be harnessed. For that matter, we propose a method (based on the well-known Arnoldi iteration) exploiting channel reciprocity in TDD systems and the sparsity of t...

In this work, we address the problem of channel estimation and precoding / combining for the so-called hybrid millimeter wave (mmWave) MIMO architecture. Our proposed channel estimation scheme exploits channel reciprocity in TDD MIMO systems, by using echoing, thereby allowing us to implement Krylov subspace methods in a fully distributed way. The...

We consider downlink transmission in multi-cell wireless networks where in each cell one base station is serving multiple mobile terminals. There is no a priori channel state information (CSI) available at base stations and mobile terminals. We propose a low-complexity pilot-assisted opportunistic user scheduling (PAOUS) scheme. The proposed scheme...

In this work, we address the problem of channel estimation and precoding / combining for the so-called hybrid millimeter wave (mmWave) MIMO architecture. Our proposed channel estimation scheme exploits channel reciprocity in TDD MIMO systems, by using echoing, thereby allowing us to implement Krylov subspace methods in a fully distributed way. The...

We consider a MIMO interference channel in which the transmitters and receivers operate in frequency-division duplex mode. In this setting, interference management through coordinated transceiver design necessitates channel state information at the transmitters (CSI-T). The acquisition of CSI-T is done through feedback from the receivers, which ent...

Our aim in this paper is to propose fully distributed schemes for transmit and receive filter optimization. The novelty of the proposed schemes is that they only require a few forward-backward iterations, thus causing minimal communication overhead. For that purpose, we relax the well-known leakage minimization problem, and then propose two differe...

We consider channel/subspace tracking systems for temporally correlated millimeter wave (e.g., E-band) multiple-input multiple-output (MIMO) channels. Our focus is given to the tracking algorithm in the non-line-of-sight (NLoS) environment, where the transmitter and the receiver are equipped with hybrid analog/digital precoder and combiner, respect...

In this work, we study the so-called leakage minimization problem, within the context of interference alignment (IA). For that purpose, we propose a novel approach based on controlled perturbations of the leakage function, and show how the latter can be used as a mechanism to control the algorithm's convergence (and thus tradeoff convergence speed...

Interference Alignment (IA) is the process of designing signals in such a way that they cast overlapping shadows at their unintended receivers, while remaining distinguishable at the intended ones. Our goal in this paper is to come up with an algorithm for IA that runs at the transmitters only (and is transparent to the receivers), that doesn't req...