arXiv subjects

Saad Al-Ahmadi

Publications and source records attributed to Saad Al-Ahmadi.

11 recordsLinked to original sources

arXiv2026

Parametric Channel Estimation and Design for Active-RIS-Assisted Communications

Reconfigurable Intelligent Surface (RIS) technology has emerged as a key enabler for future wireless communications. However, its potential is constrained by the difficulty of acquiring accurate user-to-RIS channel state information (CSI), due to the cascaded channel structure and the high pilot overhead of non-parametric methods. Unlike a passive RIS, where the reflected signal suffers from multiplicative path loss, an active RIS amplifies the signal, improving its practicality in real deployments. In this letter, we propose a parametric channel estimation method tailored for active RISs. The proposed approach integrates an active RIS model with an adaptive Maximum Likelihood Estimator (MLE) to recover the main channel parameters using a minimal number of pilots. To further enhance performance, an adaptive active RIS configuration strategy is employed, which refines the beam direction based on an initial user location estimate. Moreover, an orthogonal angle-pair codebook is used instead of the conventional Discrete Fourier Transform (DFT) codebook, significantly reducing the codebook size and ensuring reliable operation for both far-field and near-field users. Extensive simulations demonstrate that the proposed method achieves near-optimal performance with very few pilots compared to non-parametric approaches. Its performance is also benchmarked against that of a traditional passive RIS under the same total power budget to ensure fairness. Results show that active RIS yields higher spectral efficiency (SE) by eliminating the multiplicative fading inherent in passive RISs and allocating more resources to data transmission

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arXiv2026

AI-Native Open RAN for Non-Terrestrial Networks: An Overview

Non-terrestrial network (NTN) is envisioned as a critical component of Sixth Generation (6G) networks by enabling ubiquitous services and enhancing network resilience. However, the inherent mobility and high-altitude operation of NTN pose significant challenges throughout the development and operations (DevOps) lifecycle. To address these challenges, integrating NTNs with the Open Radio Access Network (ORAN) is a promising approach, since ORAN can offer disaggregation, openness, virtualization, and embedded intelligence. Despite extensive literature on ORAN and NTN, a holistic view of ORAN-based NTN frameworks is still lacking, particularly regarding how ORAN can effectively address the existing challenges of NTN. Furthermore, although artificial intelligence native (AI-Native) capabilities have the potential to enhance intelligence network control and optimization, their practical realization in NTNs has not yet been sufficiently investigated. Therefore, in this paper, we provide a comprehensive and structured overview of AI-Native ORAN for NTN. This paper commences with an in-depth review of the existing literature and subsequently introduces the necessary background about ORAN, NTN, and AI-Native for communication. After analyzing the DevOps challenges for NTN, we propose the orchestrated AI-Native ORAN-based NTN framework and discuss its key technological enablers. Finally, we present the representative use cases and outline the prospective future research directions of this study.

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arXiv2023

Energy-Efficient Optimization of Multi-User NOMA-Assisted Cooperative THz-SIMO MEC Systems

The various requirements in terms of data rates and latency in beyond 5G and 6G networks have motivated the integration of a variety of communications schemes and technologies to meet these requirements in such networks. Among these schemes are Terahertz (THz) communications, cooperative non-orthogonal multiple-access (NOMA)-enabled schemes, and mobile edge computing (MEC). THz communications offer abundant bandwidth for high-data-rate short-distance applications and NOMA-enabled schemes are promising schemes to realize the target spectral efficiencies and low latency requirements in future networks, while MEC would allow distributed processing and data offloading for the emerging applications in these networks. In this paper, an energy-efficient scheme of multi-user NOMA-assisted cooperative THz single-input multiple-output (SIMO) MEC systems is proposed to allow the uplink transmission of offloaded data from the far cell-edge users to the more computing resources in the base station (BS) through the cell-center users. To reinforce the performance of the proposed scheme, two optimization problems are formulated and solved, namely, the first problem minimizes the total users' energy consumption while the second problem maximizes the total users' computation energy efficiency (CEE) for the proposed scheme. In both problems, the NOMA user pairing, the BS receive beamforming, the transmission time allocation, and the NOMA transmission power allocation coefficients are optimized, while taking into account the full-offloading requirements of each user as well as the predefined latency constraint of the system. The obtained results reveal new insights into the performance and design of multi-user NOMA-assisted cooperative THz-SIMO MEC systems.

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arXiv2022

Vision-Assisted User Clustering for Robust mmWave-NOMA Systems

When operated in the mmWave band, user channels get highly correlated which can be exploited in mmWave-NOMA systems to cluster a set of "correlated" users together. Identifying the set of users to cluster greatly affects the viability of NOMA systems. Typically, only channel state information (CSI) is used to make these clustering decisions. When any problem arises in accessing up-to-date and accurate CSI, user clustering will not properly function due to its hard-dependency on CSI, and obviously, this will negatively affect the robustness of the NOMA systems. To improve the robustness of the NOMA systems, we propose to utilize emerging trends such as location-aware and camera-equipped base stations (CBSs) which do not require any extra radio frequency resource consumption. Specifically, we explore three different dimensions of feedback that a CBS can benefit from to solve the user clustering problem, namely CSI-based feedback and non-CSI-based feedback, comprised of user equipment (UE) location and the CBS camera feed. We first investigate how the vision assistance of a CBS can be used in conjunction with other dimensions of feedback to make clustering decisions in various scenarios. Later, we provide a simple user case study to illustrate how to implement vision-assisted user clustering in mmWave-NOMA systems to improve robustness, in which a deep learning (DL) beam selection algorithm is trained on the images captured by the CBS to perform NOMA clustering. We demonstrate that user clustering without CSI can achieve comparable performance to accurate CSI-based solutions, and user clustering can continue to function without much performance loss even in the scenarios where CSI is severely outdated or not available at all.

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arXiv2021

Energy-Efficient Coverage Enhancement of Indoor THz-MISO Systems: An FD-NOMA Approach

Terahertz (THz) communication is gaining more interest as one of the envisioned enablers of high-data-rate short-distance indoor applications in beyond 5G networks. Moreover, non-orthogonal multiple-access (NOMA)-enabled schemes are promising schemes to realize the target spectral efficiency, low latency, and user fairness requirements in future networks. In this paper, an energy-efficient cooperative NOMA (CNOMA) scheme that guarantees the minimum required rate for the cell-edge users in an indoor THz-MISO communications network is proposed. The proposed cooperative scheme consists of three stages: (i) beamforming stage that allocates base-station (BS) beams to THz cooperating cell-center users using analog beamforming with the aid of the cosine similarity metric, (ii) user pairing stage that is tackled using the Hungarian algorithm, and (iii) power allocation stage for both the BS THz-NOMA transmit power and the cooperation power of the cooperating cell-center users, which are optimized sequentially. The obtained results quantify the energy efficiency (EE) of the proposed scheme and shed new light on the performance of multi-user THz-NOMA-enabled networks.

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arXiv2021

On the Achievable Max-Min User Rates in Multi-Carrier Centralized NOMA-VLC Networks

Visible light communications (VLC) is gaining interest as one of the enablers of short-distance, high-data-rate applications, in future beyond 5G networks. Moreover, non-orthogonal multiple-access (NOMA)-enabled schemes have recently emerged as a promising multiple-access scheme for these networks that would allow realization of the target spectral efficiency and user fairness requirements. The integration of NOMA in the widely adopted orthogonal frequency-division multiplexing (OFDM)-based VLC networks would require an optimal resource allocation for the pair or the cluster of users sharing the same subcarrier(s). In this paper, the max-min rate of a multi-cell indoor centralized VLC network is maximized through optimizing user pairing, subcarrier allocation, and power allocation. The joint complex optimization problem is tackled using a low-complexity solution. At first, the user pairing is assumed to follow the divide-and-next-largest-difference user-pairing algorithm (D-NLUPA) that can ensure fairness among the different clusters. Then, subcarrier allocation and power allocation are solved iteratively through both the Simulated Annealing (SA) meta-heuristic algorithm and the bisection method. The obtained results quantify the achievable max-min user rates for the different relevant variants of NOMA-enabled schemes and shed new light on both the performance and design of multi-user multi-carrier NOMA-enabled centralized VLC networks.

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arXiv2021

Performance Evaluation of Machine Learning Techniques for DoS Detection in Wireless Sensor Network

The nature of Wireless Sensor Networks (WSN) and the widespread of using WSN introduce many security threats and attacks. An effective Intrusion Detection System (IDS) should be used to detect attacks. Detecting such an attack is challenging, especially the detection of Denial of Service (DoS) attacks. Machine learning classification techniques have been used as an approach for DoS detection. This paper conducted an experiment using Waikato Environment for Knowledge Analysis (WEKA)to evaluate the efficiency of five machine learning algorithms for detecting flooding, grayhole, blackhole, and scheduling at DoS attacks in WSNs. The evaluation is based on a dataset, called WSN-DS. The results showed that the random forest classifier outperforms the other classifiers with an accuracy of 99.72%.

cs.LG↗

arXiv2020

User Clustering in mmWave-NOMA Systems with User Decoding Capability Constraints for B5G Networks

This paper proposes a millimeter wave-NOMA (mmWave-NOMA) system that takes into account the end-user signal processing capabilities, an important practical consideration. The implementation of NOMA in the downlink (DL) direction requires successive interference cancellation (SIC) to be performed at the user terminals, which comes at the cost of additional complexity. In NOMA, the weakest user only has to decode its own signal, while the strongest user has to decode the signals of all other users in the SIC procedure. Hence, the additional implementation complexity required of the user to perform SIC for DL NOMA depends on its position in the SIC decoding order. Beyond fifth-generation (B5G) communication systems are expected to support a wide variety of end-user devices, each with their own processing capabilities. We envision a system where users report their SIC decoding capability to the base station (BS), i.e., the number of other users signals a user is capable of decoding in the SIC procedure. We investigate the rate maximization problem in such a system, by breaking it down into a user clustering and ordering problem (UCOP), followed by a power allocation problem. We propose a NOMA minimum exact cover (NOMA-MEC) heuristic algorithm that converts the UCOP into a cluster minimization problem from a derived set of valid cluster combinations after factoring in the SIC decoding capability. The complexity of NOMA-MEC is analyzed for various algorithm and system parameters. For a homogeneous system of users that all have the same decoding capabilities, we show that this equates to a simple maximum number of users per cluster constraint and propose a lower complexity NOMA-best beam (NOMA-BB) algorithm. Simulation results demonstrate the performance superiority in terms of sum rate compared to orthogonal multiple access (OMA) and traditional NOMA

cs.IT↗

arXiv2020

A Survey of Rate-optimal Power Domain NOMA with Enabling Technologies of Future Wireless Networks

The ambitious high data-rate applications in the envisioned future B5G networks require new solutions, including the advent of more advanced architectures than the ones already used in 5G networks, and the coalition of different communications schemes and technologies to enable these applications requirements. Among the candidate schemes for future wireless networks are NOMA schemes that allow serving more than one user in the same resource block by multiplexing users in other domains than frequency or time. In this way, NOMA schemes tend to offer several advantages over OMA schemes such as improved user fairness and spectral efficiency, higher cell-edge throughput, massive connectivity support, and low transmission latency. With these merits, NOMA-enabled transmission schemes are being increasingly looked at as promising multiple access schemes for future wireless networks. When the power domain is used to multiplex the users, it is referred to as PD-NOMA. In this paper, we survey the integration of PD-NOMA with the enabling communications schemes and technologies that are expected to meet the various requirements of B5G networks. In particular, this paper surveys the different rate optimization scenarios studied in the literature when PD-NOMA is combined with one or more of the candidate schemes and technologies for B5G networks including MISO, MIMO, mMIMO, advanced antenna architectures, mmWave and THz, CoMP, cooperative communications, cognitive radio, VLC, UAV and others. The considered system models, the optimization methods utilized to maximize the achievable rates, and the main lessons learnt on the optimization and the performance of these NOMA-enabled schemes and technologies are discussed in detail along with the future research directions for these combined schemes. Moreover, the role of machine learning in optimizing these NOMA-enabled technologies is addressed.

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arXiv2018

Multi-User Visible Light Communications: State-of-the-Art and Future Directions

Visible light communication (VLC) builds upon the dual use of existing lighting infrastructure for wireless data transmission. VLC has recently gained interest as cost-effective, secure, and energy-efficient wireless access technology particularly for indoor user-dense environments. While initial studies in this area are mainly limited to single-user point-to-point links, more recent efforts have focused on multi-user VLC systems in an effort to transform VLC into a scalable and fully networked wireless technology. In this paper, we provide a comprehensive overview of multi-user VLC systems discussing the recent advances on multi-user precoding, multiple access, resource allocation, and mobility management. We further provide possible directions of future research in this emerging topic.

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arXiv2010

A New Formula for the BER of Binary Modulations with Dual-Branch Selection over Generalized-K Composite Fading Channels

Error performance is one of the main performance measures and derivation of its closed-form expression has proved to be quite involved for certain systems. In this letter, a unified closed-form expression, applicable to different binary modulation schemes, for the bit error rate of dual-branch selection diversity based systems undergoing independent but not necessarily identically distributed generalized-K fading is derived in terms of the extended generalized bivariate Meijer G-function.

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