In this paper, we study an energy efficient multi-antenna unmanned aerial vehicle(UAV)-enabled half-duplex mobile relaying system under Rician fading channels. By assuming that the UAV follows a circular trajectory at...In this paper, we study an energy efficient multi-antenna unmanned aerial vehicle(UAV)-enabled half-duplex mobile relaying system under Rician fading channels. By assuming that the UAV follows a circular trajectory at fixed altitude and applying the decode-and-forward relaying strategy, we maximize the energy efficiency by jointly designing beamforming, power allocation, circular radius and flight speed, subject to the sum transmit power constraint on source node and UAV relay node. First, we maximize the end-to-end signal-to-noise ratio by jointly designing beamforming and statistical power allocation. Based on the obtained beamforming and power allocation results, we then obtain a semi closed-form expression of energy efficiency, and finally maximize energy efficiency by optimizing flight speed and circular radius, allowing optimal circular radius to be obtained via numerical computation. Numerical results demonstrate that the proposed scheme can effectively enhance the system energy efficiency.展开更多
Low-resolution analog-to-digital converter(ADC)is a promising solution to reduce hardware cost and power consumption in generalized frequency division multiplexing(GFDM)systems.The severe nonlinear distortion of ADCs ...Low-resolution analog-to-digital converter(ADC)is a promising solution to reduce hardware cost and power consumption in generalized frequency division multiplexing(GFDM)systems.The severe nonlinear distortion of ADCs and the non-orthogonality of GFDM make receiver design a great challenge.In this paper,we propose a novel model-driven receiver architecture for GFDM with low-resolution ADCs.Orthogonal approximate message passing(OAMP)framework is combined with the classical linear estimator in this work to create a robust iterative receiver for GFDM systems with low-precision ADCs.The corresponding model-driven network is organized based on the proposed novel iterative algorithm according to the procedures of the receiver.The network of OAMP can reduce the gap between the approximate algorithm and the Bayesian optimal result due to the information loss of ADCs.The signal flow of the neural network is designed by unfolding the iterative algorithms for channel estimation and data detection.Numerical results are provided to show that the proposed OAMP-based receiver algorithm outperforms traditional receivers and the model-driven network can further improve the system performance on the basis of the corresponding novel algorithm.展开更多
基金supported in part by the National Science Foundation (NSFC) for Distinguished Young Scholars of China with Grant 61625106the National Natural Science Foundation of China under Grant 61531011
文摘In this paper, we study an energy efficient multi-antenna unmanned aerial vehicle(UAV)-enabled half-duplex mobile relaying system under Rician fading channels. By assuming that the UAV follows a circular trajectory at fixed altitude and applying the decode-and-forward relaying strategy, we maximize the energy efficiency by jointly designing beamforming, power allocation, circular radius and flight speed, subject to the sum transmit power constraint on source node and UAV relay node. First, we maximize the end-to-end signal-to-noise ratio by jointly designing beamforming and statistical power allocation. Based on the obtained beamforming and power allocation results, we then obtain a semi closed-form expression of energy efficiency, and finally maximize energy efficiency by optimizing flight speed and circular radius, allowing optimal circular radius to be obtained via numerical computation. Numerical results demonstrate that the proposed scheme can effectively enhance the system energy efficiency.
基金This work was supported in part by the National Key Research and Development Program(2018YFA0701602)the National Natural Science Foundation of China for Distinguished Young Scholars of China(Nos.61625106,61531011)+1 种基金The work of C.K.Wen was supported in part by the Ministry of Science and Technology of Taiwan(MOST 106-2221-E-110-019)the ITRI in Hsinchu,Taiwan,China。
文摘Low-resolution analog-to-digital converter(ADC)is a promising solution to reduce hardware cost and power consumption in generalized frequency division multiplexing(GFDM)systems.The severe nonlinear distortion of ADCs and the non-orthogonality of GFDM make receiver design a great challenge.In this paper,we propose a novel model-driven receiver architecture for GFDM with low-resolution ADCs.Orthogonal approximate message passing(OAMP)framework is combined with the classical linear estimator in this work to create a robust iterative receiver for GFDM systems with low-precision ADCs.The corresponding model-driven network is organized based on the proposed novel iterative algorithm according to the procedures of the receiver.The network of OAMP can reduce the gap between the approximate algorithm and the Bayesian optimal result due to the information loss of ADCs.The signal flow of the neural network is designed by unfolding the iterative algorithms for channel estimation and data detection.Numerical results are provided to show that the proposed OAMP-based receiver algorithm outperforms traditional receivers and the model-driven network can further improve the system performance on the basis of the corresponding novel algorithm.