Polarization Channel Estimation for Circular and Non-Circular Signals in Massive MIMO Systems

Abstract

In this paper, an algorithm of multiple signal classification (MUSIC) is proposed for two-dimensional (2-D) directionof-arrival (DOA) and polarization estimation of non-circular signal in three-dimensional (3-D) millimeter wave polarized largescale/massive multiple-input-multiple-output (MIMO) systems. The traditional MUSIC-based algorithms can estimate either the DOA and polarization for circular signal or the DOA for non-circular signal by using spectrum search. By contrast, in the proposed algorithm only the DOA estimation needs spectrum search, and the polarization estimation has a closedform expression. First, a novel dimension-reduced MUSIC (DR-MUSIC) is proposed for DOA and polarization estimation of circular signal with low computational complexity. Next, based on the quaternion theory, a novel algorithm named quaternion non-circular MUSIC (QNC-MUSIC) is proposed for parameter estimation of non-circular signal with high estimation accuracy. Then based on the DOA estimation result using QNC-MUSIC, the polarization estimation of non-circular signal is acquired by using the closed-form expression of the polarization estimation in DR-MUSIC. In addition, the computational complexity analysis shows that compared with the conventional DOA and polarization estimation algorithms, our proposed QNC-MUSIC and DR-MUSIC have much lower computational complexity, especially when the source number is large. The stochastic Cramér-Rao Bound (CRB) for the estimation of the 2-D DOA and polarization parameters of the non-circular signals is derived as well. Finally, numerical examples are provided to demonstrate that the proposed algorithms can improve the parameter estimation performance when the large-scale/massive MIMO systems are employed.Index Terms-Direction-of-arrival (DOA) and polarization estimation, polarized large-scale/massive multiple-input-multipleoutput (LS-MIMO/massive MIMO), three-dimensional (3-D) millimeter wave communication, circular and non-circular signals, quaternion.

2D-DOD and 2D-DOA Estimation for a Mixture of Circular and Strictly Noncircular Sources Based on L-Shaped MIMO Radar

“…where b k,m denotes the mth element of the transmitter steering vector, s k (t) = α k (t)r k (t) is circular or strictly noncircular baseband signal, and w m (t) is the noise vector after matched filter. As for strictly noncircular baseband signal, the s k (t) can also be written as s k (t) = s n,k (t)e jϕ k /2 [19][20][21][22][23], where s n,k (t) is real-value and ϕ k /2 is arbitrary phase shifts that can be different for each signal but are constant with time.…”

“…However, the above-mentioned methods for MIMO radar failed to exploit some potential information of radar signals, such as noncircularity [19][20][21][22][23], which could lead to significant improvement in its performance. With the aid of noncircular (NC) property of the signals, a series of angle estimation methods [24][25][26] for bistatic MIMO radar were proposed, which can improve the accuracy of angle estimation and detect more signals.…”

Adaptive Spoofing Suppression Algorithm for GNSS Based on Multiple Antennas Array

“…Therefore, the traditional Direction of Arrival (DOA) estimation algorithm [27][28][29] can be used to measure the direction of arrival of the spoofing. In this paper, we use the multiple signal classification (MUSIC) algorithm [30] as an example to introduce the process of estimating the direction of arrival of spoofing.…”

An Array Switching Strategy for Direction of Arrival Estimation with Coprime Linear Array in the Presence of Mutual Coupling

“…As a fundamental part of array signal processing, direction of arrival (DOA) estimation plays a critical role in various fields, e.g., radar, acoustics, cognitive radio and wireless communication [1][2][3][4][5][6][7]. Numerous high-resolution DOA estimation algorithms are developed for uniform linear arrays (ULAs), such as MUSIC [8], ESPRIT [9] and the variants [10,11].…”