arXiv subjects

Jalal Jalali

Publications and source records attributed to Jalal Jalali.

8 recordsLinked to original sources

arXiv2026

Shape Adaptive Reconfigurable Holographic Surfaces

The evolution of wireless networks toward sixth-generation (6G) is driving demand for intelligent, flexible, and energy-efficient propagation control. Reconfigurable holographic surfaces (RHSs) enable fine-grained wavefront manipulation through densely packed programmable elements. This paper introduces shape-adaptive RHSs, which dynamically change surface geometry to provide extra spatial degrees of freedom. The adaptive design responds to environmental dynamics, mitigates blockages, and improves performance across urban communications, aerial coverage, and joint sensing and communication scenarios. We propose a network architecture that jointly designs the surface shape at the RHS and optimizes transmission. Simulation results show that the proposed shape-adaptive RHSs significantly increase data rates. These findings establish shape-adaptive RHS as a foundational technology for intelligent, context-aware wireless environments in 6G and beyond wireless networks.

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arXiv2026

RHOSI: Efficient Anti-Jamming Resource Allocation with Holographic Surfaces in UAV-enabled ISAC

This paper investigates the susceptibility of Integrated Sensing and Communication (ISAC) systems to hostile jamming, focusing on an aerial Reconfigurable Holographic Surface (RHS)-aided unmanned aerial vehicle (UAV). The proposed framework, termed RHOSI, enhances ISAC's resilience by dynamically shaping the wireless propagation environment. Specifically, RHOSI introduces a strategy to improve jamming resistance by jointly optimizing transmit beamforming at the hybrid base station, RHS phase shift configuration, and UAV spatial deployment, while ensuring the required echo signal-to-interference-plus-noise ratios for reliable sensing. The resulting non-linear optimization problem features highly coupled variables, which are decomposed into sub-problems and solved using an alternating optimization (AO) approach. Simulation results confirm the practicality and effectiveness of RHOSI in significantly improving the throughput and robustness of ISAC under adversarial jamming.

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arXiv2025

Miniature UAV-Aided Cooperative THz Networks with Reconfigurable Energy Harvesting Holographic Surfaces

This paper focuses on enhancing the energy efficiency (EE) of a cooperative network that features a miniature unmanned aerial vehicle (UAV) operating at terahertz (THz) frequencies and equipped with holographic surfaces to improve network performance. Unlike traditional reconfigurable intelligent surfaces (RIS), which serve as passive relays for signal reflection, this work introduces a novel concept: energy harvesting (EH) using reconfigurable holographic surfaces (RHS). These surfaces provide more powerful and focused energy delivery during wireless power transfer than RIS and are mounted on the miniature UAV. In this system, a source node enables the UAV to simultaneously receive both information and energy signals, with the harvested energy powering data transmission to a specific destination. The EE optimization problem involves adjusting non-orthogonal multiple access (NOMA) power coefficients and the UAV's flight path while accounting for the unique characteristics of the THz channel. The problem is solved in two stages to maximize EE and meet a target transmission rate. The UAV trajectory is optimized using a successive convex approximation (SCA) method, followed by the adjustment of NOMA power coefficients through a quadratic transform technique. Simulation results demonstrate the effectiveness of the proposed algorithm, showing significant improvements over baseline methods.

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arXiv2025

Shape Adaptive Reconfigurable Holographic Surfaces

Reconfigurable Intelligent Surfaces (RIS) have emerged as a key solution to dynamically adjust wireless propagation by tuning the reflection coefficients of large arrays of passive elements. Reconfigurable Holographic Surfaces (RHS) build on the same foundation as RIS but extend it by employing holographic principles for finer-grained wave manipulation | that is, applying higher spatial control over the reflected signals for more precise beam steering. In this paper, we investigate shape-adaptive RHS deployments in a multi-user network. Rather than treating each RHS as a uniform reflecting surface, we propose a selective element activation strategy that dynamically adapts the spatial arrangement of deployed RHS regions to a subset of predefined shapes. In particular, we formulate a system throughput maximization problem that optimizes the shape of the selected RHS elements, active beamforming at the access point (AP), and passive beamforming at the RHS to enhance coverage and mitigate signal blockage. The resulting problem is non-convex and becomes even more challenging to solve as the number of RHS and users increases; to tackle this, we introduce an alternating optimization (AO) approach that efficiently finds near-optimal solutions irrespective of the number or spatial configuration of RHS. Numerical results demonstrate that shape adaptation enables more efficient resource distribution, enhancing the effectiveness of multi-RHS deployments as the network scales.

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arXiv2025

Placement, Orientation, and Resource Allocation Optimization for Cell-Free OIRS-aided OWC Network

The emergence of optical intelligent reflecting surface (OIRS) technologies marks a milestone in optical wireless communication (OWC) systems, enabling enhanced control over light propagation in indoor environments. This capability allows for the customization of channel conditions to achieve specific performance goals. This paper presents an enhancement in downlink cell-free OWC networks through the integration of OIRS. The key focus is on fine-tuning crucial parameters, including transmit power, receiver orientations, OIRS elements allocation, and strategic placement. In particular, a multi-objective optimization problem (MOOP) aimed at simultaneously improving the network's spectral efficiency (SE) and energy efficiency (EE) while adhering to the network's quality of service (QoS) constraints is formulated. The problem is solved by employing the $ε$-constraint method to convert the MOOP into a single-objective optimization problem and solving it through successive convex approximation. Simulation results show the significant impact of OIRS on SE and EE, confirming its effectiveness in improving OWC network performance.

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arXiv2023

On the Energy Efficiency of THz-NOMA enhanced UAV Cooperative Network with SWIPT

This paper considers the energy efficiency (EE) maximization of a simultaneous wireless information and power transfer (SWIPT)-assisted unmanned aerial vehicles (UAV) cooperative network operating at TeraHertz (THz) frequencies. The source performs SWIPT enabling the UAV to receive both power and information while also transmitting the information to a designated destination node. Subsequently, the UAV utilizes the harvested energy to relay the data to the intended destination node effectively. Specifically, we maximize EE by optimizing the non-orthogonal multiple access (NOMA) power allocation coefficients, SWIPT power splitting (PS) ratio, and UAV trajectory. The main problem is broken down into a two-stage optimization problem and solved using an alternating optimization approach. In the first stage, optimization of the PS ratio and trajectory is performed by employing successive convex approximation using a lower bound on the exponential factor in the THz channel model. In the second phase, the NOMA power coefficients are optimized using a quadratic transform approach. Numerical results demonstrate the effectiveness of our proposed resource allocation algorithm compared to the baselines where there is no trajectory optimization or no NOMA power or PS optimization.

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arXiv2023

Toward Energy Efficient Multiuser IRS-Assisted URLLC Systems: A Novel Rank Relaxation Method

This paper proposes an energy efficient resource allocation design algorithm for an intelligent reflecting surface (IRS)-assisted downlink ultra-reliable low-latency communication (URLLC) network. This setup features a multi-antenna base station (BS) transmitting data traffic to a group of URLLC users with short packet lengths. We maximize the total network's energy efficiency (EE) through the optimization of active beamformers at the BS and passive beamformers (a.k.a. phase shifts) at the IRS. The main non-convex problem is divided into two sub-problems. An alternating optimization (AO) approach is then used to solve the problem. Through the use of the successive convex approximation (SCA) with a novel iterative rank relaxation method, we construct a concave-convex objective function for each sub-problem. The first sub-problem is a fractional program that is solved using the Dinkelbach method and a penalty-based approach. The second sub-problem is then solved based on semi-definite programming (SDP) and the penalty-based approach. The iterative solution gradually approaches the rank-one for both the active beamforming and unit modulus IRS phase-shift sub-problems. Our results demonstrate the efficacy of the proposed solution compared to existing benchmarks.

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arXiv2020

Resource Allocation for SWIPT in Multi-Service Wireless Networks

The novel resource allocation for simultaneous wireless information and power transfer (SWIPT) is presented as a means of not only helping to communicate and access information with increasing efficiency in the next generation of mobile data networks but also contributing to minimizing a network's overall power consumption by providing a green energy source. First, a unique architecture is proposed that harvests energy from an access point (AP) without the receiver needing a splitter. In the proposed system model, a portion of the spectrum is used for information decoding (ID) while the remaining portion is exploited for energy harvesting (EH) in an orthogonal frequency division multiple access (OFDMA) network. To investigate the performance gain, an optimization problem is formulated that maximizes the harvested energy of a multi-user single-cell OFDMA downlink (DL) network with SWIPT and also satisfies a minimum data-rate requirement for all users. A locally optimal solution for the underlying problem, which is essentially non-convex due to the coupling of the integer variable, is obtained by using optimization tools. Second, the proposed system model is improved in order to investigate the resource allocation problem of needing to maximize throughput based on the separated receiver architecture in an OFDMA multi-user multi-cell system that uses SWIPT. The resulting problem, which jointly optimizes the subcarrier assignment and power allocation, is a mixed-integer non-linear problem (MINLP) that is difficult to solve. Third, a state-of-the-art harvesting technique at the receiver that is based on receiver antenna selection with a co-located architecture is explored to optimize the energy efficiency (EE) of a SWIPT-enabled multi-cell multi-user OFDMA network. This is referred to as a Generalized Antenna-Switching Technique.

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