scholarly journals Low complexity channel estimation algorithm using paired spatial signatures for UAV 3D MIMO systems

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Peizhong Xie ◽  
Yingqing Wan ◽  
Ting Li ◽  
Renjie Ju
Keyword(s):  
Channel Estimation ◽  
Rotation Angle ◽  
Mimo Systems ◽  
Estimation Algorithm ◽  
Low Complexity ◽  
Three Dimension ◽  
Optimal Rotation ◽  
3D Mimo ◽  
Training Resources ◽  
Optimal Rotation Angle

AbstractThis paper proposes a low complexity channel estimation algorithm for unmanned aerial vehicle three dimension multi-user multiple-input-multiple-output (3D MIMO) systems with the uniform planar array (UPA) at base station using paired spatial signatures. With the aid of antenna array theory and array signal processing, 3D channel is firstly modeled based on the angles between the direction of arrival along x- and y-axis of the UPA. And 3D MIMO channels can be projected onto the x- and y-directions, respectively. Then, channel estimation for multi-user uplinks using small amount of training resources is divided into two phases. At the first uplink preamble phase, each user is assigned the orthogonal pilot, and the paired spatial signatures and optimal rotation angle of each user through the same pilot sequence are obtained. We also propose a user grouping strategy based on three-dimension angle-division multiple access (3D-ADMA) to ensure that the user's spatial signatures do not overlap. At the second phase during several coherence times, the same pilot sequence within a group and orthogonal pilot sequences between groups are assigned, then, the channel state information of the user's x- and y-directions are recovered by the paired space signatures and optimal rotation angle of each user obtained in the preamble phase, respectively. And dynamically updating the user's paired spatial signatures and optimal rotation angle utilizes the obtained channel parameter of x- and y-directions. Finally, the channel parameter of the x- and y-directions are reconstructed by the updated user's space signatures and the optimal rotation angle, and the 3D MIMO channel estimation is obtained through the Kronecker product. Compared with the conventional channel estimation method of the 3D MIMO system under UPA using a low-rank model, the proposed methods reduce the computational complexity without degrading the estimated performance to a large extent. Furthermore, it is carried out with limited training resources, and the pilot resource overhead of the system is greatly reduced by the 3D-ADMA packet and the two-stage pilot allocation. Simulation results verified that the proposed algorithm is effective and feasible.

Low Complexity Channel Estimation Algorithm Using Paired Spatial Signatures for UAV 3D MIMO Systems

2020 ◽  
Author(s):  
Peizhong Xie ◽  
Yingqing Wan ◽  
Ting Li ◽  
Renjie Ju
Keyword(s):  
Channel Estimation ◽  
Rotation Angle ◽  
Mimo Systems ◽  
Estimation Algorithm ◽  
Low Complexity ◽  
Three Dimension ◽  
Optimal Rotation ◽  
3D Mimo ◽  
Training Resources ◽  
Optimal Rotation Angle

Abstract This paper proposes a low complexity channel estimation algorithm for unmanned aerial vehicle (UAV) three dimension multi-user multiple-input-multiple-output (3D MIMO) systems with the uniform planar array (UPA) at base station (BS) using paired spatial signatures. With the aid of antenna array theory and array signal processing, 3D channel is firstly modeled based on the angles between the direction of arrival (DOA) along x- and y-axis of the UPA. And 3D MIMO channels can be projected onto the x- and y-directions, respectively. Then, channel estimation for multi-user uplinks using small amount of training resources is divided into two phases. At the first uplink preamble phase, each user is assigned the orthogonal pilot, and the paired spatial signatures and optimal rotation angle of each user through the same pilot sequence are obtained. We also propose a user grouping strategy based on three-dimension angle-division multiple access (3D-ADMA) to ensure that the user's spatial signatures do not overlap. At the second phase during several coherence times, the same pilot sequence within a group and orthogonal pilot sequences between groups are assigned, then, the channel state information of the user's x- and y-directions are recovered by the paired space signatures and optimal rotation angle of each user obtained in the preamble phase, respectively. And dynamically updating the user's paired spatial signatures and optimal rotation angle utilizes the obtained channel parameter of x- and y-directions. Finally, the channel parameter of the x- and y-directions are reconstructed by the updated user's space signatures and the optimal rotation angle, and the 3D MIMO channel estimation is obtained through the Kronecker product. Compared with the conventional channel estimation method of the 3D MIMO system under UPA using a low-rank model, the proposed methods reduce the computational complexity without degrading the estimated performance to a large extent. Furthermore, it is carried out with limited training resources, and the pilot resource overhead of the system is greatly reduced by the 3D-ADMA packet and the two-stage pilot allocation. Simulation results verified that the proposed algorithm is effective and feasible. Keywords 3D MIMO, 3D Channel Modeling, Unmanned Aerial Vehicle, Channel Estimation, Computational Complexity

Low Complexity Channel Estimation Algorithm Using Paired Spatial Signatures for UAV 3D MIMO Systems

2020 ◽  
Author(s):  
Yingqing Wan ◽  
Peizhong Xie ◽  
Ting Li ◽  
Renjie Ju
Keyword(s):  
Channel Estimation ◽  
Rotation Angle ◽  
Mimo Systems ◽  
Estimation Algorithm ◽  
Low Complexity ◽  
Three Dimension ◽  
Optimal Rotation ◽  
3D Mimo ◽  
Training Resources ◽  
Optimal Rotation Angle

Abstract This paper proposes a low complexity channel estimation algorithm for unmanned aerial vehicle (UAV) three dimension multi-user multiple-input-multiple-output (3D MIMO) systems with the uniform planar array (UPA) at base station (BS) using paired spatial signatures. With the aid of antenna array theory and array signal processing, firstly 3D channel modeling based on the angle between the direction of arrival (DOA) and the x- direction of the array antenna, and the angle between the DOA and the y- direction of the array antenna. And 3D MIMO channels can be projected onto the x- and y-directions, respectively. Then, channel estimation for multiuser uplinks using small amount of training resources, which is divided into two phases. The first phase is the uplink preamble phase, which assigns each user an orthogonal pilot, and obtains the paired spatial signatures and optimal rotation angle of each user through the same pilot sequence. We also propose a user grouping strategy based on three dimension angle-division multiple access (3D-ADMA) to ensure that the user's spatial signatures do not overlap. The second phase is much coherence times after the preamble phase, which assigns the same pilot sequence within a group and assigns orthogonal pilot sequences between groups, and the channel state information of the user's x- and y-directions is recovered by the paired space signatures and optimal rotation angle of each user obtained in the preamble phase, respectively. And dynamically updating the user's paired spatial signatures and optimal rotation angle utilizes the obtained channel components of x- and y-directions. Finally, the channel components of the x- and y-directions are reconstructed by the updated user's space signatures and the optimal rotation angle, and the 3D MIMO channel is generated by the Kronecker product. Compared with the conventional channel estimation method of a 3D MIMO system under UPA using a low rank model, the proposed methods greatly reduce the computational complexity without reducing the estimated performance, it is carried out with limited training resources, and the pilot resource overhead of the system is greatly reduced by the 3D-ADMA packet and the two-stage pilot allocation. Various numerical results are provided to corroborate the proposed studies.

scholarly journals Modulation Set Optimization for the Improved Complex Quadrature SM

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Asif Iqbal ◽  
Manar Mohaisen ◽  
Kyung Sup Kwak
Keyword(s):  
Euclidean Distance ◽  
Rotation Angle ◽  
Computational Cost ◽  
Low Complexity ◽  
Spatial Modulation ◽  
Optimal Rotation ◽  
Wide Range ◽  
Channel Realization ◽  
System Configurations ◽  
Optimal Rotation Angle

At each channel use, the complex quadrature spatial modulation (CQSM) transmits two signal symbols drawn from two disjoint modulation sets. The indices of the antennas from which symbols are transmitted also carry information. In the improved CQSM (ICQSM), an additional antenna is used to transmit the second signal symbol only when the indices of the antennas to be used for transmission are equal. Conventionally, the second modulation set is a rotated version of the first, where the rotation angle is optimized such that the average unconditional error probability (AUP) is reduced. In this paper, we propose a low-complexity method to design the PSK modulation sets based on reducing the AUP. After introducing min-BER and max-dmin, two exhaustive search methods, we analytically show that the AUP depends on Euclidean distance between transmitted vectors, which in turn depends on the power of signal symbols, the Euclidean distance between the symbols of each modulation set, and the Euclidean distance between the symbols of the two sets. The optimal rotation angle is analytically derived for any modulation order and the radii of the modulation sets are optimized such that AUP is reduced for a wide range of system configurations. The simulation results show that more than 3 dB of power gain is achieved in the case of 16PSK, where higher gains are achieved for higher modulation orders. These gains are achieved at no computational cost because the optimization does not depend on the channel realization.

scholarly journals Low-Complexity Joint Channel Estimation for Multi-User mmWave Massive MIMO Systems

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 301
Author(s):  
Jianhe Du ◽  
Jiaqi Li ◽  
Jing He ◽  
Yalin Guan ◽  
Heyun Lin
Keyword(s):  
Channel Estimation ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Estimation Algorithm ◽  
Step Length ◽  
Low Complexity ◽  
Base Station ◽  
Estimation Accuracy ◽  
Input Multiple Output

For multi-user millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems, the precise acquisition of channel state information (CSI) is a huge challenge. With the increase of the number of antennas at the base station (BS), the traditional channel estimation techniques encounter the problems of pilot training overhead and computational complexity increasing dramatically. In this paper, we develop a step-length optimization-based joint iterative scheme for multi-user mmWave massive MIMO systems to improve channel estimation performance. The proposed estimation algorithm provides the BS with full knowledge of all channel parameters involved in up- and down-links. Compared with existing algorithms, the proposed algorithm has higher channel estimation accuracy with low complexity. Moreover, the proposed scheme performs well even with a small number of training sequences and a large number of users. Simulation results are shown to demonstrate the performance of the proposed channel estimation algorithm.

scholarly journals Low-complexity beam-domain channel estimation and power allocation in hybrid architecture massive MIMO systems

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Xiao Chen ◽  
Zaichen Zhang ◽  
Liang Wu ◽  
Jian Dang
Keyword(s):  
Channel Estimation ◽  
Power Allocation ◽  
Spectral Efficiency ◽  
Communication Systems ◽  
Mimo Systems ◽  
Beam Steering ◽  
Estimation Method ◽  
Low Complexity ◽  
Estimation Accuracy ◽  
Hybrid Architecture

Abstract In this journal, we investigate the beam-domain channel estimation and power allocation in hybrid architecture massive multiple-input and multiple-output (MIMO) communication systems. First, we propose a low-complexity channel estimation method, which utilizes the beam steering vectors achieved from the direction-of-arrival (DOA) estimation and beam gains estimated by low-overhead pilots. Based on the estimated beam information, a purely analog precoding strategy is also designed. Then, the optimal power allocation among multiple beams is derived to maximize spectral efficiency. Finally, simulation results show that the proposed schemes can achieve high channel estimation accuracy and spectral efficiency.

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