Loading [MathJax]/extensions/MathMenu.js
A Robust Tensor-Based Receiver for Joint Channel Estimation and Symbol Detection in UAV Assisted Communication Systems | IEEE Conference Publication | IEEE Xplore

A Robust Tensor-Based Receiver for Joint Channel Estimation and Symbol Detection in UAV Assisted Communication Systems


Abstract:

In this paper, for unmanned aerial vehicle (UAV) assisted communication systems, we propose a robust tensor-based receiver for joint channel estimation and symbol detecti...Show More

Abstract:

In this paper, for unmanned aerial vehicle (UAV) assisted communication systems, we propose a robust tensor-based receiver for joint channel estimation and symbol detection. Firstly, at the source node (SN), the proposed receiver adopts a superposition transmitting scheme for information symbol and pilot signal. Then, the UAV amplifies and forwards the received signals to the destination node (DN), and the signals received at DN are constructed to a fourth-order tensor model. Finally, a robust algorithm is developed to fitting the constructed tensor model for joint channel estimation and symbol detection. The proposed receiver can effectively estimate channels and detect symbols. Compared with the existing receivers, our receiver has better performance of channel estimation and symbol detection.
Date of Conference: 13-16 October 2021
Date Added to IEEE Xplore: 04 January 2022
ISBN Information:

ISSN Information:

Conference Location: Tianjin, China
References is not available for this document.

I. Introduction

Recently, unmanned aerial vehicle (UAV) has been widely used in various fields with their high flexibility and reliability [1]. For example, in the case of reconstruction services after natural disasters or traffic diversion in sudden traffic accidents on the ground, UAV can play a huge role as a space base station. Compared with traditional terrestrial communication systems, UAV assisted communication system can achieve orders of magnitude performance improvement [2]. On the other hand, the UAV relay can be placed at any position and height as needed [3], [4], and the performance index of the UAV relay can be dynamically deployed according to demand [5]. In conclusion, MIMO relay node based on UAV can provide network operators with greater flexibility.

Select All
1.
L Zhang, H Zhao, S Hou et al., "A Survey on 5G Millimeter Wave Communications for UAV- Assisted Wireless Networks[J]", IEEE Access, vol. PP, no. 99, pp. 1-1, 2019.
2.
M Gapeyenko, V Petrov, D Moltchanov et al., "Comparing Capacity Gains of Static and UAV- Based Millimeter-Wave Relays in Clustered Deployments[C]// 2020 IEEE International Conference on Communications Workshops (ICC Workshops)", IEEE, 2020.
3.
Che Y L Wang, J Long et al., "Multiple Access MmWave Design for UAV-Aided 5G Communications[J]", IEEE Wireless Communications, vol. 26, no. 1, pp. 64-71, 2019.
4.
Z Xiao, H Dong, L Bai et al., "Unmanned Aerial Vehicle Base Station (UAV-BS) Deployment With Millimeter-Wave Beamforming[J]", IEEE Internet of Things Journal, vol. 7, no. 2, pp. 1336-1349, 2020.
5.
M Mozaffari, W Saad, M Bennis et al., "A Tutorial on UAVs for Wireless Networks: Applications Challenges and Open Problems[J]", IEEE Communications Surveys Tutorials, pp. 2334-2360, 2019.
6.
G Zhang, Q Wu, M Cui et al., "Securing UAV Communications via Joint Trajectory and Power Control[J]", IEEE Transactions on Wireless Communications, 2019.
7.
C You and R Zhang, "3D Trajectory Optimization in Rician Fading for UAV- Enabled Data Harvesting[J]", IEEE Transactions on Wireless Communications, pp. 1-1, 2019.
8.
J Zhao, J Liu, J Jiang et al., "Efficient Deployment With Geometric Analysis for mmWave UAV Communications[J]", IEEE Wireless Communications Letters, vol. 9, no. 7, pp. 1115-1119, 2020.
9.
J Du, M Han, L Jin et al., "Semi-Blind Receivers for Multi-User Massive MIMO Relay Systems Based on Tucker2-PARAFAC Tensor Model[J]", IEEE Access, vol. PP, no. 99, 2020.
10.
F Gao, Tao C and Nallanathan A, "On channel estimation and optimal training design for amplify and forward relay networks[J]", IEEE Transactions on Wireless Communications, vol. 7, no. 5, pp. 1907-1916, 2008.
11.
D Katselis, E Kofidis and S Theodoridis, "On Training Optimization for Estimation of Correlated MIMO Channels in the Presence of Multiuser Interference[J]", IEEE Transactions on Signal Processing, vol. 56, no. 10, pp. 4892-4904, 2008.
12.
G Geraci, A Garcia-Rodriguez, L Galati Giordano et al., "Understanding UAV Cellular Communications: From Existing Networks to Massive MIMO[J]", IEEE Access, vol. 6, pp. 67853-67865, 2018.
13.
C Pirak, Z J Wang, K Liu et al., "A Data-Bearing Approach for Pilot-Embedding Frameworks in Space-Time Coded MIMO Systems[J]", IEEE Transactions on Signal Processing, vol. 54, no. 10, pp. 3966-3979, 2006.
14.
S Gong, S Wang, C Xing et al., "Robust Superimposed Training Optimization for UAV Assisted Communication Systems[J]", IEEE Transactions on Wireless Communications, vol. 19, no. 3, pp. 1704-1721, 2020.
15.
H Xi, A Almeida, A Liu et al., "Semi-Blind Receiver for Two-Way MIMO Relaying Systems based on Joint Channel and Symbol Estimation[J]", IET Communications, vol. 13, no. 8, pp. 1090-1094, 2019.
16.
N. D. Sidiropoulos and R. S. Budampati, "Khatri-Rao space-time codes", Signal Processing IEEE Transactions on 50, vol. 10, pp. 2396-2407, 2015.
17.
R A Harshman, "Foundations of the parafac procedure: Models and conditions for an “explanatory” multimodal factor analysis[J]", Ucla Working Papers in Phonetics, vol. 16, 1970.
18.
J Du, C Yuan and J Zhang, "Semi-blind parallel factor based receiver for joint symbol and channel estimation in amplify-and-forward multiple-input multiple-output relay systems[J]", IET Communications, vol. 9, no. 6, pp. 737-744, 2015.
19.
A L F De Almeida, G Favier and L R Ximenes, "Space-time-frequency (STF) MIMO communication systems with blind receiver based on a generalized PARATUCK2 model[J]", IEEE Transactions on Signal Processing, vol. 61, no. 8, pp. 1895-1909, 2013.
20.
H Lin, C Yuan, J Du et al., "Tensor-Based Joint Channel Estimation and Symbol Detection for AF MIMO Relay Networks[J]", Journal of Shanghai Jiaotong University (Science), vol. 25, no. 1, pp. 88-96, 2020.
21.
K Madsen, H B Nielsen and O Tingleff, Methods for non-linear least squares problems [M], Copenhagen, Denmark:Technical University of Denmark, 2004.

Contact IEEE to Subscribe

References

References is not available for this document.