DOA Estimation for Coherently Distributed Sources Considering Circular and Noncircular Signals in Massive MIMO Systems

Wan, Liangtian; Han, Guangjie; Jiang, Jinfang; Rodrigues, Joel J. P. C.; Feng, Naixing; Zhu, Tong

doi:10.1109/jsyst.2015.2445052

Cited by 93 publications

(57 citation statements)

References 23 publications

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“…Step 5: according to (32), convert 1D PSS to polynomial root finding process and obtain the K roots of u (k) i . Similarly, we can achieve v (k) i and w (k) i .…”

Section: Detailedmentioning

confidence: 99%

“…In this paper, on the basis of the 1D CLA and 2D CPA, we construct a three-dimensional (3D) array geometry called coprime cubic array (CCA). In the context of massive MIMO systems [31,32], MC effects become important which have a vital influence on DOA estimation accuracy. e geometry of CCA possesses the extended array aperture and can effectively reduce MC effects.…”

Section: Introductionmentioning

confidence: 99%

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Three-Dimensional Coprime Array for Massive MIMO: Array Configuration Design and 2D DOA Estimation

Gong

Ahmed

2020

Wireless Communications and Mobile Computing

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In massive multiple-input multiple-output (MIMO) systems, it is critical to obtain the accurate direction of arrival (DOA) estimation. Conventional three-dimensional array mainly focuses on the uniform array. Due to the dense arrangement of the sensors, the array aperture is limited and severe mutual coupling effects arise. In this paper, a coprime cubic array (CCA) configuration design is presented, which is composed of two uniform cubic subarrays and can extend the interelement spacing with a selection of three pairs of coprime integers. Compared with uniform cubic array (UCA), CCA achieves the larger array aperture and less MC effects. And the analytical expression of Cramer–Rao Bound (CRB) for CCA is derived which verifies that the proposed CCA geometry outperforms the conventional UCA in two-dimensional (2D) DOA estimation performance in massive MIMO systems. Meanwhile, we propose a computationally efficient 2D DOA estimation algorithm with high accuracy for CCA. Specifically, we utilize array mapping to extract two uniform arrays from the nonuniform array by exploiting the relation derived from the signal subspace and the two directional matrices. Then, we operate a reduced dimension process on the uniform arrays and convert the 2D spectrum peak searching (SPS) problem into one-dimensional (1D) one, which significantly reduces the computational complexity. In addition, we employ the polynomial root finding technique with a lower complexity instead of 1D SPS to further relieve the computational complexity. Simultaneously, with coprime property, the phase ambiguity problem is solved, which results from the large interelement spacing. Numerical simulation results demonstrate that the proposed algorithm is very computationally efficient without degradation of DOA estimation performance.

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“…Step 5: according to (32), convert 1D PSS to polynomial root finding process and obtain the K roots of u (k) i . Similarly, we can achieve v (k) i and w (k) i .…”

Section: Detailedmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Coprime Array for Massive MIMO: Array Configuration Design and 2D DOA Estimation

Gong

Ahmed

2020

Wireless Communications and Mobile Computing

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“…According to the analysis in [13], the spectrum estimation function of the maximal non-circularity rated signals can be expressed as…”

Section: Doa Estimation For Maximal Non-circularity Rated Signalsmentioning

confidence: 99%

An improved DOA estimation algorithm for circular and non-circular signals with high resolution

Wan

Xie

2016

2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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In this paper, an improved direction-of-arrival (DOA) estimation algorithm for circular and non-circular signals is proposed. Most stateof-the-art algorithms only deal with the DOA estimation problem for the maximal non-circularity rated and circular signals. However, common non-circularity rated signals are not taken into consideration. The proposed algorithm can estimates not only the maximal non-circularity rated and circular signals, but also the common noncircularity rated signals. Based on the property of the non-circularity phase and rate, the incident signals can be divided into three types as mentioned above, which can be estimated separately. The interrelationship among these signals can be reduced significantly, which means the resolution performance among different types of signals is improved. Simulation results illustrate the effectiveness of the proposed method.

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“…Thus, Yang proposed a method for CD noncircular signals based on sparse representation, which exhibits a good performance under the condition of small snapshots with low SNR [16]. Wan put forward a DSPE algorithm based on the combination of circular and noncircular signals in a large MIMO system, which improves the parameter estimation precision [17]. To reduce computation cost, Yang combined the characteristics of noncircular signals 2 Wireless Communications and Mobile Computing with the ESPRIT algorithm to avoid complex parameter search and obtain high-accuracy results [18].…”

Section: Introductionmentioning

confidence: 99%

Direct Position Determination of Coherently Distributed Noncircular Sources

Wang

et al. 2018

Wireless Communications and Mobile Computing

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The existing localization algorithms for coherently distributed (CD) sources fail to achieve the best localization performance because of position information loss and error accumulation. To solve this problem, this study proposed a novel direct position determination (DPD) algorithm that profits from the characteristics of noncircular signals. Based on the parameterization assumption of CD sources, the DPD localization model is initially constructed and an extended subspace data fusion-based DPD algorithm is subsequently proposed by decomposing the extended covariance matrices, which are constructed by combining the characteristics of noncircular sources. The algorithm achieves a low complexity and a high efficiency by avoiding the calculation of the intermediate variables. Specifically, the closed-form expression of the Cramer-Rao lower bound for CD noncircular sources is also derived. Simulation results show that, compared with existing DPD algorithms, the proposed algorithm improves the multitarget localization capability and achieves high-accuracy results.

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DOA Estimation for Coherently Distributed Sources Considering Circular and Noncircular Signals in Massive MIMO Systems

Cited by 93 publications

References 23 publications

Three-Dimensional Coprime Array for Massive MIMO: Array Configuration Design and 2D DOA Estimation

Three-Dimensional Coprime Array for Massive MIMO: Array Configuration Design and 2D DOA Estimation

An improved DOA estimation algorithm for circular and non-circular signals with high resolution

Direct Position Determination of Coherently Distributed Noncircular Sources

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