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Irfan Azam

Publications and source records attributed to Irfan Azam.

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RIS-Assisted Joint Resource Allocation for 6G FR3 IoT Networks

In sixth-generation (6G) networks, the deployment of large numbers of Internet of Things (IoT) users (IU) necessitates efficient resource utilization and reliable connectivity, making resource allocation a critical factor. Specifically, the upper mid-band (FR3) spectrum has emerged as a promising candidate for 6G systems due to its favorable balance between bandwidth availability and coverage. However, translating these spectral advantages into performance gains in dense IoT environments requires intelligent management of interference and propagation impairments. In this paper, we propose a reconfigurable intelligent surface (RIS)-assisted IoT network operating in the FR3 band to enhance coverage and improve signal quality. Furthermore, we formulate a joint power allocation and IU-RIS association problem to maximize the achievable sum rate under practical channel conditions and power constraints. The resulting problem is nonconvex and combinatorial due to interference coupling and binary association variables. To address this challenge, we develop a multiphase resource allocation framework that integrates a successive convex approximation (SCA)-based power allocation scheme combined with a matching-theory-based user association algorithm. Simulation results demonstrate that the proposed scheme significantly outperforms conventional greedy and random search schemes in terms of sum-rate enhancement.

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Tensor-based Space Debris Detection for Satellite Mega-constellations

Thousands of satellites, asteroids, and rocket bodies break, collide, or degrade, resulting in large amounts of space debris in low Earth orbit. The presence of space debris poses a serious threat to satellite mega-constellations and to future space missions. Debris can be avoided if detected within the safety range of a satellite. In this paper, an integrated sensing and communication technique is proposed to detect space debris for satellite mega-constellations. The canonical polyadic (CP) tensor decomposition method is used to estimate the rank of the tensor that denotes the number of paths including line-of-sight and non-line-of-sight by exploiting the sparsity of THz channel with limited scattering. The analysis reveals that the reflected signals of the THz can be utilized for the detection of space debris. The CP decomposition is cast as an optimization problem and solved using the alternating least square (ALS) algorithm. Simulation results show that the probability of detection of the proposed tensor-based scheme is higher than the conventional energy-based detection scheme for the space debris detection.

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Mitigation of Misalignment Errors Over Inter-Satellite FSO Energy Harvesting

In this paper, the impact of the acquisition, tracking, and pointing (ATP) module utilization on inter-satellite energy harvesting is investigated for 1U (0.1$\times$0.1$\times$0.1 m) and 12U (0.2$\times$0.2$\times$0.3 m) satellites for adaptive beam divergence and the corresponding distances while maintaining the spot diameters. Random elevation and azimuth misalignment error angles at both the transmitter and the receiver are modeled with Gaussian distribution hence the radial pointing error angle is modeled with Rayleigh distribution. The Monte Carlo approach is used to determine mean radial error angles for both transmitter and receiver in the non-ATP and ATP cases. The average harvested powers are analyzed as a function of the transmit powers and inter-satellite distances for both 1U and 12U satellites while considering the minimum power requirements. Our simulation results show that in the non-ATP case, the minimum required average harvested power cannot be achieved beyond 680 and 1360 km distances for 1U and 12U satellites, respectively, with a maximum transmit power of 1 kW. However, 2 W of average harvested power can be achieved at around 750 and 1500 km for 1U and 12U satellites, respectively, with a transmit power of 27 W in the presence of an ATP mechanism.

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Energy Efficient Pairing and Power Optimization for NOMA UAV Network under QoS Constraints

Due to an increasing number of unmanned aerial vehicles (UAVs) with generally limited battery power, energy efficient data transmission schemes with massive connectivity capabilities are required for future wireless networks. Non-orthogonal multiple access (NOMA) is one of the promising techniques that provide such massive connectivity by allowing superposed data transmission of multiple users over the same resource block. Unlike existing literature, this paper presents a user pairing and power allocation technique for energy efficient and quality of service (QoS) aware NOMA transmission for cellular-connected mobile UAVs. The aim is to minimize the power consumption of the mobile UAVs during uplink data transmission and guarantee their required transmission rate by jointly optimizing the UAV pairing and power allocation. Furthermore, the performance and pairing complexity for mobile UAVs is analyzed to show that the proposed pairing technique efficiently fulfills their QoS requirements. Numerical and simulation results show the performance gain of the proposed technique compared to the conventional NOMA techniques.

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Role Switching and Power Allocation Technique for Mobile Users in NOMA

In this letter, role switching and power allocation schemes are proposed to tackle user mobility in non-orthogonal multiple access (NOMA) systems. When cell center user (CCU) and cell edge user (CEU) come very close or even cross each other in NOMA pairing, channel gains of paired users violate the basic NOMA conditions. This article refers to such condition as NOMA principle violation problem (NPVP). To solve this NPVP, optimized power role switching-NOMA (OPRS-NOMA) technique is proposed. Role switching technique is used where roles of mobile users are switched on the basis of their channel gains. Furthermore, a power allocation scheme based on bisection search power optimization is presented to maximize the average sum capacity of mobile NOMA users. Random way point mobility model is considered for user mobility. Individual and sum capacity are used for performance evaluation. Simulation results show that OPRS-NOMA outperforms the conventional NOMA and orthogonal multiple access (OMA).

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