UAV-Assisted Superposition Coded Cooperation: Hybrid Relaying and Nakagami-m Channel for UL/DL

Pankaj Kumar, Nikita Goel*, Manoj Tolani*, Santhosh Kamath

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    Abstract

    In future wireless communication systems reliability and throughput are the major concern for the users in an infrastructure less scenarios. These requirements are fulfill by the unmanned aerial vehicle (UAV)-assisted superposition coded cooperation (UA-SP-CC) system. However, the traditional relaying scheme (amplify-and-forward (AF)/decode-and-forward (DF)) used at the UAV is no longer sufficient in practical scenarios because it applies the received signal without comparing the received instantaneous signal-to-noise ratio (SNR) with the predefined threshold value. The other important issue in UA-SP-CC system is the same channel (Rayleigh or Rician) consideration for the whole network. However, in practical circumstances, the channel gain varies with UAV height. Taking these concerns into account, we consider a hybrid relaying at UAV and Nakagami-m channel whose gain is a function of UAV heights while deciding the channel between uplink (UL)/downlink (DL) in a UA-SP-CC scenario. The height-dependent path loss exponent is also consider for modeling the large scale fading between UL/DL. Taking urban scenarios into account, this paper considers non-line-of-sight (NLoS) paths among the ground users, and Rayleigh fading utilize for implementing these NLoS components. The expressions for the superposition coded noise (SPCN) and the variance of SPCN are developed for UA-NC-CC system using the proposal. The expressions of spectral efficiency, probability of outage, time complexity analysis, and throughput are developed for the proposal. Algorithm 1 is developed for evaluating the performance metrics (spectral efficiency and probability of outage) of our proposed work and compared the results with the existing state-of-the-art (Rician and Rayleigh fading channel model).

    Original languageEnglish
    JournalIEEE Access
    DOIs
    Publication statusAccepted/In press - 2025

    All Science Journal Classification (ASJC) codes

    • General Computer Science
    • General Materials Science
    • General Engineering

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