Abstract
This 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.
Highlights
During recent years, the research on 5th-generation (5G) technology has developed at the speed of blowout
Sudheesh et al [9] considered the application of IA in a high altitude platform (HAP) to ground station (GS) communication, and the application of IA is proposed for a generalized channel in a HAP-to-GS communication link that takes into account angle-ofdeparture and angle-of-arrival at the transmitter and at the receiver, respectively
5 Numerical results and discussions we demonstrate the effectiveness of the proposed method through numerical example. we consider a multi-user 3D MIMO system with Base station (BS) configuration uniform planar array (UPA), and system parameters are chosen as M = 100 and N = 100, which are number of antennas in the x- and y-directions of the UPA, respectively, antenna spacing d = λ/2
Summary
The research on 5th-generation (5G) technology has developed at the speed of blowout. The CSI acquisition has been recognized as very challenging task for 3D MIMO systems, due to the high dimensionality of channel matrices as well as the resultant uplink pilot contamination, prohibitive computational complexity and so on [10] To solve these problems, some researchers have used the sparsity of the Massive MIMO channel to estimate the channel with a small number of observations, thereby reducing computational complexity and pilot overhead [11,12,13,14]. Author in [22] proposed a channel estimation algorithm based on 2D discrete Fourier transform (2D-DFT) for indoor 60 GHz massive MIMO systems via array signal processing. −→ new definition; (A) denotes the vectorization of A ; [h]B, indicates the sub-vector of h by keeping the elements indexed by B ; [H ]B, stands for the sub-matrix of H by collecting the rows indexed by B ; [H ]B denotes the sub-matrix of H by collecting the columns indexed B
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