arXiv subjects

Ali Olfat

Publications and source records attributed to Ali Olfat.

5 recordsLinked to original sources

arXiv2026

Comprehensive Review of Advances and Challenges in Next Generation Wireless Networks: From Novel Hardware Technologies to Learning Based Resource Allocation in 6G

In modern wireless communication systems, there is a rapidly increasing demand for connectivity to wireless networks. Devices such as internet of things (IoT) devices, connected vehicles, smartphones, surveillance systems, and various other applications contribute significantly to this demand. Consequently, next-generation wireless systems must be capable of handling this enormous volume of devices and traffic. In recent years, several technologies have been introduced to address these challenges, including reconfigurable intelligent surfaces (RIS), integrated sensing and communication (ISAC), advanced antenna and intelligent surface technologies, and novel multiple access (MA) techniques. Furthermore, due to the limited resources available in communication systems, efficient resource allocation strategies are essential to support complex and high-dimensional optimization problems. In addition, modern communication systems are required to optimize resources within strict time constraints. Therefore, resource allocation solutions must be intelligent and computationally efficient. Conventional optimization techniques, such as convex optimization, are often inadequate for addressing these requirements. To overcome these limitations, novel resource allocation algorithms based on learning methods have been developed. In this paper, we comprehensively investigate advanced communication technologies alongside modern resource allocation optimization methods and algorithms based on machine learning techniques. Subsequently, current challenges of wireless networks are analyzed. Finally, open research challenges are identified.

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arXiv2025

Spectrum Sharing in STAR-RIS-assisted UAV with NOMA for Cognitive Radio Networks

As an emerging technology, the simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) can improve the spectrum efficiency (SE) of primary users (PUs) and secondary users (SUs) in cognitive radio (CR) networks by mitigating the interference of the incident signals. The STAR-RIS-assisted unmanned aerial vehicle (UAV) can fully cover the dynamic environment through high mobility and fast deployment. According to the dynamic air-to-ground channels, the STAR-RIS-assisted UAV may face a challenge configuring their elements' coefficients (i.e., reflecting and transmitting the amplitude and phases). Hence, to meet the requirements of dynamic channel determination with the SE approach, this paper proposes the sum rate maximization of both PUs and SUs through non-orthogonal multiple access in CR network to jointly optimize the trajectory and transmission-reflection beamforming design of the STAR-RIS-assisted UAV, and power allocation. Since the non-convex joint optimization problem includes coupled optimization variables, we develop an alternative optimization algorithm. Simulation results study the impact of: 1) the significant parameters, 2) the performance of different intelligence surface modes and STAR-RIS operating protocols, 3) the joint trajectory and beamforming design with fixed and mobile users, and 4) STAR-RIS capabilities such as mitigating the interference, and how variations in the roles of elements dynamically.

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arXiv2025

Decode and Forward Relaying for SC-FDE Systems with a Multi-Antenna Relay

In this paper, a cooperative relay network consisting of a single-antenna source, a multi-antenna relay, and a multi-antenna destination is considered. The relay operates in decode-and-forward (DF) mode under frequency-selective fading. To combat intersymbol interference (ISI), single-carrier frequency-domain equalization (SC-FDE) with or without decision feedback is deployed at the relay and the destination. The equalization coefficients are obtained using minimum mean squared error (MMSE) criterion. Both equal and optimum power allocations for a constant total transmit power at the relay are considered. While, the optimum power allocation is a non-convex problem, the solution is obtained using strong duality.

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arXiv2020

Wideband Modal Orthogonality: A New Approach for Broadband DOA Estimation

Wideband direction of arrival (DOA) estimation techniques for sensors array have been studied extensively in the literature. Nevertheless, needing prior information on the number and directions of sources or demanding heavy computational load makes most of these techniques less useful in practice. In this paper, a low complexity subspace-based framework for DOA estimation of broadband signals, named as wideband modal orthogonality (WIMO), is proposed and accordingly two DOA estimators are developed. First, a closed-form approximation of spatial-temporal covariance matrix (STCM) in the uniform spectrum case is presented. The eigenvectors of STCM associated with non-zero eigenvalues are modal components of the wideband source in a given bandwidth and direction. WIMO idea is to extract these eigenvectors at desired DOAs from the approximated STCM and test their orthogonality to estimated noise subspace. In the non-uniform spectrum case, WIMO idea can be applied by approximating STCM through numerical integration. Fortunately, STCM approximation and modal extraction can be performed offline. WIMO provides DOA estimation without the conventional prerequisites, such as spectral decomposition, focusing procedure and, a priori information on the number of sources and their DOAs. Several numerical examples are conducted to compare the WIMO performance with the state-of-the-art methods. Simulations demonstrate that the two proposed DOA estimators achieve superior performance in terms of probability of resolution and estimation error along with orders of magnitude runtime speedup.

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arXiv2019

Single Stage DOA-Frequency Representation of the Array Data with Source Reconstruction Capability

In this paper, a new signal processing framework is proposed, in which the array time samples are represented in DOA-frequency domain through a single stage problem. It is shown that concatenated array data is well represented in a $\mathbf{G}$ dictionary atoms space, where $\mathbf{G}$ columns correspond to pixels in the DOA-frequency image. We present two approaches for the $\mathbf{G}$ formation and compare the benefits and disadvantages of them. A mutual coherence guaranteed $\mathbf{G}$ manipulation technique is also proposed. Furthermore, unlike most of the existing methods, the proposed problem is reversible into the time domain, therefore, source recovery from the resulted DOA-frequency image is possible. The proposed representation in DOA-frequency domain can be simply transformed into a group sparse problem, in the case of non-multitone sources in a given bandwidth. Therefore, it can also be utilized as an effective wideband DOA estimator. In the simulation part, two scenarios of multitone sources with unknown frequency and DOA locations and non-multitone wideband sources with assumed frequency region are examined. In multitone scenario, sparse solvers yield more accurate DOA-frequency representation compared to some noncoherent approaches. At the latter scenario, the proposed method with group sparse solver outperforms some existing wideband DOA estimators in low SNR regime. In addition, sources' recovery simultaneous with DOA estimation shows significant improvement compared to the conventional delay and sum beamformer and without prerequisites required in sophisticated wideband beamformers.

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