arXiv subjects

Ziaul Haq Abbas

Publications and source records attributed to Ziaul Haq Abbas.

3 recordsLinked to original sources

arXiv2026

Controlled Out-of-Band Device-to-Device Communication in Cellular Networks Using a Backup Channel in Television White Space

In this article, we address the problem of spectrum scarcity in cellular networks (CNs). We propose a backup channel (BuC) for cellular users (CUs) located in the same macro-cell under the control of a single macro base station (eNB). This BuC operates in television white space and is detected by the CUs through a cognitive radio energy-detection channel-sensing technique with a certain probability of success. When all regular channels with the cellular eNB are occupied, the CUs within the same coverage area of the macro eNB can utilize the sensed BuC to establish a controlled out-of-band device-to-device link for communication. The BuC bypasses the eNB for data communication and reduces the burden on the core of the CN. This leads to improved cellular eNB capacity. In the proposed system model, each CU and eNB is equipped with two antennas for communication in two separate bands, i.e., cellular and TV bands. Simulations show significant reductions in the blocking probability and probability of call delay.

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arXiv2025

Energy-Efficient and Reliable Data Collection in Receiver-Initiated Wake-up Radio Enabled IoT Networks

In unmanned aerial vehicle (UAV)-assisted wake-up radio (WuR)-enabled internet of things (IoT) networks, UAVs can instantly activate the main radios (MRs) of the sensor nodes (SNs) with a wake-up call (WuC) for efficient data collection in mission-driven data collection scenarios. However, the spontaneous response of numerous SNs to the UAV's WuC can lead to significant packet loss and collisions, as WuR does not exhibit its superiority for high-traffic loads. To address this challenge, we propose an innovative receiver-initiated WuR UAV-assisted clustering (RI-WuR-UAC) medium access control (MAC) protocol to achieve low latency and high reliability in ultra-low power consumption applications. We model the proposed protocol using the $M/G/1/2$ queuing framework and derive expressions for key performance metrics, i.e., channel busyness probability, probability of successful clustering, average SN energy consumption, and average transmission delay. The RI-WuR-UAC protocol employs three distinct data flow models, tailored to different network traffic conditions, which perform three MAC mechanisms: channel assessment (CCA) clustering for light traffic loads, backoff plus CCA clustering for dense and heavy traffic, and adaptive clustering for variable traffic loads. Simulation results demonstrate that the RI-WuR-UAC protocol significantly outperforms the benchmark sub-carrier modulation clustering protocol. By varying the network load, we capture the trade-offs among the performance metrics, showcasing the superior efficiency and reliability of the RI-WuR-UAC protocol.

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arXiv2024

Energy Efficiency Maximization in IRS-enabled Phase Cooperative PS-SWIPT based Self-sustainable IoT Network

Power splitting based simultaneous wireless information and power transfer (PS-SWIPT) appears to be a promising solution to support future self-sustainable Internet of Things (SS-IoT) networks. However, the performance of these networks is constrained by radio frequency signal strength and channel impairments. To address this challenge, intelligent reflecting surfaces (IRSs) are introduced in PS-SWIPT based SS-IoT networks to improve network efficiency by controlling signal reflections. In this article, an IRS-enabled phase cooperative framework is proposed to improve energy efficiency (EE) of the IoT network $({\mathtt {I}}^{net})$ using phase shifts of the user network $({\mathtt {U}^{net})}$, without constraining hardware resources at ${\mathtt {U}^{net}}$. We exploit transmit beamforming (BF) at access points (APs) and phase shifts optimization at the IRS end with phase effective cooperation between APs to enhance ${\mathtt {I}}^{net}$ EE performance. The maximization problem turns out to be NP-hard, so first, an alternating optimization (AO) is solved for the ${\mathtt {U}^{net}}$ using low computational complexity heuristic BF approaches, namely, transmit minimum-mean-square-error and zero-forcing BF, and phase optimization is performed using semidefinite relaxation (SDR) approach. To combat the computational complexity of AO, we also propose an alternative solution by exploiting heuristic BF schemes and an iterative algorithm, i.e., the element-wise block-coordinate descent method for phase shifts optimization. Next, EE maximization is solved for the ${\mathtt {I}^{net}}$ by optimizing the PS ratio and active BF vectors by exploiting optimal phase shifts of the ${\mathtt {U}}^{net}$. Simulation results confirm that employing IRS phase cooperation in PS-SWIPT based SS-IoT networks can significantly improve EE performance of ${\mathtt {I}^{net}}$ without constraining resources.

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