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An Intelligence-Based Recurrent Learning Scheme for Optimal Channel Allocation and Selection in Device-to-Device Communications

Published: 01 February 2020 Publication History

Abstract

Decentralized mobile user communications rely on sensing and signal processing that are aided by fusion centers. Device-to-device (D2D) communications form the backend network for facilitating mobile user communication through the appropriate signal sensing and channel selection. The sensing and processing of tightly coupled channels ensure seamless uninterrupted communications with fewer outages. An imbalance in channel allocation and selection increases the gap between communication networks and signal processing systems. Unattended channel allocation and selection result in delayed communications and additional power exploitation with less reliability. This paper introduces an intelligence-based recurrent learning (IRL) scheme for optimal channel allocation and selection for mobile users’ D2D communication. The objective of this paper is to select a delay-controlled channel satisfying both the data rate and power control requirements in the channel allocation. The allocated channel is analyzed through a responsive linear system transformation for its power, data rate, and time constraints in a recurrent manner. The intelligent learning technique evaluates the consistency of the channel based on a recurrent analysis. The outcome of the analysis is the selection of an optimal channel from the allocated channels that satisfies the objective and channel policies. Synchronized channel allocation achieves power-controlled communications in a cooperative manner under controlled interference. The proposed IRL minimizes D2D communication delay, transmits the power requirement and outage, and improves throughput with better reliability.

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Cited By

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  • (2021)Hybrid Secure Equivalent Computing Model for Distributed Computing ApplicationsWireless Personal Communications: An International Journal10.1007/s11277-021-08265-x127:1(319-339)Online publication date: 19-Feb-2021
  • (2020)Distributed and scalable computing framework for improving request processing of wearable IoT assisted medical sensors on pervasive computing systemComputer Communications10.1016/j.comcom.2020.01.020151:C(257-265)Online publication date: 1-Feb-2020
  • (2019)A primer on design aspects, recent advances, and challenges in cellular device-to-device communicationAd Hoc Networks10.1016/j.adhoc.2019.10193894:COnline publication date: 1-Nov-2019

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            Published In

            cover image Circuits, Systems, and Signal Processing
            Circuits, Systems, and Signal Processing  Volume 39, Issue 2
            Feb 2020
            667 pages

            Publisher

            Birkhauser Boston Inc.

            United States

            Publication History

            Published: 01 February 2020
            Accepted: 06 February 2019
            Revision received: 03 February 2019
            Received: 11 December 2018

            Author Tags

            1. Channel allocation and sharing
            2. D2D communications
            3. Linear systems
            4. Recurrent learning
            5. Signal processing

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            View all
            • (2021)Hybrid Secure Equivalent Computing Model for Distributed Computing ApplicationsWireless Personal Communications: An International Journal10.1007/s11277-021-08265-x127:1(319-339)Online publication date: 19-Feb-2021
            • (2020)Distributed and scalable computing framework for improving request processing of wearable IoT assisted medical sensors on pervasive computing systemComputer Communications10.1016/j.comcom.2020.01.020151:C(257-265)Online publication date: 1-Feb-2020
            • (2019)A primer on design aspects, recent advances, and challenges in cellular device-to-device communicationAd Hoc Networks10.1016/j.adhoc.2019.10193894:COnline publication date: 1-Nov-2019

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