Device-to-device (D2D) communications can be adopted as a promising solution to attain high quality of service (QoS) for a network. However, D2D communications generates harmful interference when available resources are shared with traditional cellular users (CUs). In this paper, network architecture for the uplink resource management issue for D2D communications underlaying uplink cellular networks is proposed. We develop a fractional frequency reuse (FFR) technique to mitigate interference induced by D2D pairs (DPs) to CUs and mutual interference among DPs in a cell. Then, we formulate a sum throughput optimization problem to achieve the QoS requirements of the system. However, the computational complexity of the optimization problem is very high due to the exhaustive search for a global optimal solution. In order to reduce the complexity, we propose a greedy heuristic search algorithm for D2D communications so as to find a sub-optimal solution. Moreover, a binary power control scheme is proposed to enhance the system throughput by reducing overall interference. The performance of our proposed scheme is analyzed through extensive numerical analysis using Monte Carlo simulation. The results demonstrate that our proposed scheme provides significant improvement in system throughput with the lowest computational complexity.
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http://dx.doi.org/10.3390/s19020251 | DOI Listing |
Oncol Lett
February 2025
Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, P.R. China.
Paracancerous tissues actively communicate with the tumor and undergo molecular alterations associated with tumorigenesis. Apparent diffusion coefficient (ADC) can help distinguish between rectal adenocarcinoma (RA), tumor-adjacent and tumor-distant tissues. Preoperative determining optimal distal resection margin (DRM) is crucial for formulating surgical options.
View Article and Find Full Text PDFPeerJ Comput Sci
October 2024
Changchun Children's Library, Changchun, Jilin, China.
PLoS One
October 2024
College of Engineering, Basic and Applied Science, Arab Academy for Science, Technology and Maritime Transport, Alexandria, Egypt.
Egypt faces extreme traffic congestion in its cities, which results in long travel times, large lines of parked cars, and increased safety hazards. Our study suggests a multi-modal approach that combines critical infrastructure improvements with cutting-edge technologies to address the ubiquitous problem of traffic congestion. Assuring vehicles owners of their timely arrival, cutting down on fuel usage, and improving communication using deep learning approach and optimization algorithm within the potential of IoT enabled 5G framework are the main goals.
View Article and Find Full Text PDFSci Rep
October 2024
Huawei, Nanjing, 210096, Jiangsu, China.
With the rapid development of Internet of Things (IoT) services, technologies that leverage multimedia computer communication for information sharing in embedded systems have become a research focus. To address the challenges of low spectral efficiency and poor network flexibility in multimedia computer communications, this paper proposes a resource allocation scheme based on parallel Convolutional Neural Network (CNN). The scheme optimizes the base station beamforming vector and the Reconfigurable Intelligent Surface (RIS) phase shifts to maximize the secure transmission rate for cellular users (CUs), while ensuring normal and secure communication for device-to-device (D2D) users.
View Article and Find Full Text PDFSensors (Basel)
September 2024
Electrical, Mechanical and Computer (EMC) School of Engineering, Federal University of Goias (UFG), Goiânia 74605010, GO, Brazil.
Next-generation mobile networks, such as those beyond the 5th generation (B5G) and 6th generation (6G), have diverse network resource demands. Network slicing (NS) and device-to-device (D2D) communication have emerged as promising solutions for network operators. NS is a candidate technology for this scenario, where a single network infrastructure is divided into multiple (virtual) slices to meet different service requirements.
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