Trajectory Design and Power Allocation for Drone-Assisted NR-V2X Network with Dynamic NOMA/OMA

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Abbasi O., Yanikomeroglu H., EBRAHIMI A., Yamchi N. M.

IEEE Transactions on Wireless Communications, cilt.19, sa.11, ss.7153-7168, 2020 (SCI-Expanded, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 19 Sayı: 11
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1109/twc.2020.3008568
  • Dergi Adı: IEEE Transactions on Wireless Communications
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.7153-7168
  • Anahtar Kelimeler: NOMA, Relays, Trajectory, Resource management, Optimization, Wireless communication, Vehicle dynamics, Non-orthogonal multiple access, aerial relaying, dynamic multiple access, trajectory design, power allocation, V2X
  • Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
  • Atatürk Üniversitesi Adresli: Hayır

Özet

In this paper, we find trajectory planning and power allocation for a vehicular network in which an unmanned-aerial-vehicle (UAV) is considered as a relay to extend coverage for two disconnected far vehicles. We show that in a two-user network with an amplify-and-forward (AF) relay, non-orthogonal-multiple-access (NOMA) always has better or equal sum-rate in comparison to orthogonal-multiple-access (OMA) at high signal-to-noise-ratio (SNR) regime. However, for the cases where i) base station (BS)-to-relay link is weak, or ii) two users have similar links, or iii) BS-to-relay link is similar to relay-to-weak user link, applying NOMA has negligible sum-rate gain. Hence, due to the complexity of successive-interference-cancellation (SIC) decoding in NOMA, we propose a dynamic NOMA/OMA scheme in which OMA mode is selected for transmission when applying NOMA has only negligible gain. Also, we show that OMA always has better min-rate than NOMA at high SNR regime. Further, we formulate two optimization problems which maximize the sum-rate and min-rate of the two vehicles. These problems are non-convex, and hence we propose an iterative algorithm based on alternating-optimization (AO) method which solves trajectory and power allocation sub-problems by successive-convex-approximation (SCA) and difference-of-convex (DC) methods, respectively. Finally, the above-mentioned performance is confirmed by simulations.