Effective power allocation and distribution for 6 g – network in a box enabled peer to peer wireless communication networks

Gnanavel, V. K.; Srinivasan, Anand

doi:10.1007/s12083-020-00942-1

Cited by 1 publication

(1 citation statement)

References 24 publications

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“…Research on 6G wireless networks and the associated technical advances has lately received significant attention from both academia and industry, helping the advancement of the IoT and beyond [22][23][24]. Because of its improved features over the prior network decades, like ultra-low latency communication, ultrahigh throughput, satellite-based client services and massive and automatic networks, 6G is anticipated to offer a completely new service quality and improve users' experiences in current IoT systems [25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Sustainable Power Consumption for Variance-Based Integration Model in Cellular 6G-IoT System

Ramamoorthy,

Sanober,

Di Nunzio

et al. 2023

Sustainability

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With the emergence of the 5G network, the count of analysis papers associated with the 6G Internet of Things (IoT) has rapidly increased due to the rising attention of researchers in next-generation technology, 6G networks and IoT techniques. Owing to this, grasping the overall research topics and directions is a complex task. To mutually address the significant issues of 6G cellular IoT, i.e., information transmission, data aggregation and power supply, we proposed a variance-based integrating model for the 6G-IoT approach that considers energy, communication and computation (ECC). Initially, the base station (BS) charges huge IoT devices concurrently utilizing WPT in the downlink. After that, IoT devices gather the energy to perform the communication task and the computation task in the uplink in a similar spectrum. Also, the model integrates the optimization of transmit beams via the Improved Ant Colony Optimization (IACO) model to balance the system performance, power consumption and computational complexity. Further, this study exploited activated Remote Radio Units (RRUs) to improve the network performance and energy efficiency in the downlink model. The simulation outcomes evaluate the performance of the proposed work over the conventional models concerning error analysis. From the results, the MSE value in the IACO work is much lower, around 0.011, while the compared schemes achieved comparatively higher MSE values.

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