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Interference Aware Resource Control for 6G-Enabled Expanded IoT Networks.
Taneja, Ashu; Alqahtani, Nayef; Alqahtani, Ali.
Afiliação
  • Taneja A; Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, Punjab, India.
  • Alqahtani N; Department of Electrical Engineering, College of Engineering, King Faisal University, Al-Hofuf, Al-Ahsa 31982, Saudi Arabia.
  • Alqahtani A; Department of Networks and Communications Engineering, College of Computer Science and Information Systems, Najran University, Najran 61441, Saudi Arabia.
Sensors (Basel) ; 23(12)2023 Jun 16.
Article em En | MEDLINE | ID: mdl-37420816
ABSTRACT
Emerging consumer devices rely on the next generation IoT for connected support to undergo the much-needed digital transformation. The main challenge for next-generation IoT is to fulfil the requirements of robust connectivity, uniform coverage and scalability to reap the benefits of automation, integration and personalization. Next generation mobile networks, including beyond 5G and 6G technology, play an important role in delivering intelligent coordination and functionality among the consumer nodes. This paper presents a 6G-enabled scalable cell-free IoT network that guarantees uniform quality-of-service (QoS) to the proliferating wireless nodes or consumer devices. By enabling the optimal association of nodes with the APs, it offers efficient resource management. A scheduling algorithm is proposed for the cell-free model such that the interference caused by the neighbouring nodes and neighbouring APs is minimised. The mathematical formulations are obtained to carry out the performance analysis with different precoding schemes. Further, the allocation of pilots for obtaining the association with minimum interference is managed using different pilot lengths. It is observed that the proposed algorithm offers an improvement of 18.9% in achieved spectral efficiency using partial regularized zero-forcing (PRZF) precoding scheme at pilot length τp=10. In the end, the performance comparison with two other models incorporating random scheduling and no scheduling at all is carried out. As compared to random scheduling, the proposed scheduling shows improvement of 10.9% in obtained spectral efficiency by 95% of the user nodes.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Conscientização / Algoritmos Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Conscientização / Algoritmos Idioma: En Ano de publicação: 2023 Tipo de documento: Article