Energy-Efficient Backscatter Aided Uplink NOMA Roadside Sensor Communications under Channel Estimation Errors

[en] This work presents non-orthogonal multiple access (NOMA) enabled energy-efficient alternating optimization framework for backscatter aided wireless powered uplink sensors communications for beyond 5G intelligent transportation system (ITS). Specifically, the transmit power of carrier emitter (CE) and reflection coefficients of backscatter aided roadside sensors are optimized with channel uncertainties for the maximization of the energy efficiency (EE) of the network. The formulated problem is tackled by the proposed two-stage alternating optimization algorithm named AOBWS (alternating optimization for backscatter aided wireless powered sensors). In the first stage, AOBWS employs an iterative algorithm to obtain optimal CE transmit power through simplified closed-form computed through Cardano’s formulae. In the second stage, AOBWS uses a noniterative algorithm that provides a closed-form expression for the computation of optimal reflection coefficient for roadside sensors under their quality of service (QoS) and a circuit power constraint. The global optimal exhaustive search (ES) algorithm is used as a benchmark. Simulation results demonstrate that the AOBWS algorithm can achieve near-optimal performance with very low complexity, which makes it suitable for practical implementations.

Disciplines :

Ingénierie électrique & électronique

Auteur, co-auteur :

Ihsan, Asim

Chen, Wen

KHAN, Wali Ullah ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom

Wu, Qingqing

Wang, Kunlun

Co-auteurs externes :

yes

Langue du document :

Anglais

Titre :

Energy-Efficient Backscatter Aided Uplink NOMA Roadside Sensor Communications under Channel Estimation Errors

Titre traduit :

[en] Energy-Efficient Backscatter Aided Uplink NOMA Roadside Sensor Communications under Channel Estimation Errors

Date de publication/diffusion :

février 2023

Titre du périodique :

IEEE Transactions on Intelligent Transportation Systems

ISSN :

1524-9050

eISSN :

1558-0016

Maison d'édition :

Institute of Electrical and Electronics Engineers, New-York, Etats-Unis - New York

Peer reviewed :

Peer reviewed vérifié par ORBi

Disponible sur ORBilu :

depuis le 25 janvier 2023

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