In this study, the authors propose a fast quadrilinear decomposition algorithm for estimation of the directions-of-arrival and polarisations of the incident sources via a uniform rectangular array of electromagnetic v...
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In this study, the authors propose a fast quadrilinear decomposition algorithm for estimation of the directions-of-arrival and polarisations of the incident sources via a uniform rectangular array of electromagnetic vector sensors (EMVSs). Conventional quadrilinear alternating least squares (QALS), involves computationally intensive Khatri-Rao products in each iteration, to update the parameter matrices (factors). Moreover, QALS is more likely to fall in a local minimum and tends to take more steps before an acceptable solution, which further slows down the convergence and often mis-converges, thereby yielding meaningless results. To preserve the quadrilinearity, they arrange the measurements as a four-dimensional (4D) data (fourth-order tensor), from which a third-order sub-tensor (3D slice) can be obtained by fixing one index along any dimension. These slices are used to create new cost functions that are alternately minimised while updating the factors until convergence. They show that the rows of parameter matrices form the diagonal elements of a tensor, which capture the internal quadrilinearity of data and significantly reduce the cost function in few iterations only. Simulation results verify that the authors' algorithm holds faster convergence, does not mis-converge, provides parameter estimation accuracy similarly to the QALS and superior of the Estimation of Signal Parameters via Rotational Invariance Technique and propagator method.
The concept of an intelligent reflecting surface (IRS) has recently emerged as a promising solution for improving the coverage and energy/spectral efficiency of future wireless communication systems. However, as the n...
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The concept of an intelligent reflecting surface (IRS) has recently emerged as a promising solution for improving the coverage and energy/spectral efficiency of future wireless communication systems. However, as the number of reflecting elements in an IRS increase, the beam training protocol in IRS-assisted millimeter-wave (mmWave) cellular systems requires a large beam training time because it needs to find the best beam pairs for the link between the base station (BS) and the IRS, as well as the link between the IRS and the mobile station (MS). In this paper, a fast beam training technique for IRS-assisted mmWave cellular systems with a uniform rectangular array is proposed for detecting the best beam pairs of BS-IRS and IRS-MS links simultaneously. Two different types of beam training signals (BTSs) are proposed to distinguish simultaneously transmitted beams from the BSs in multi-cell multi-beam environments: the Zadoff-Chu sequence based BTS (ZC-BTS) and m-sequence based BTS (m-BTS). The correlation properties of ZC-BTSs and m-BTSs are analyzed in multi-cell multi-beam environments. In addition, the effect of symbol time offset on the ZC-BTS and m-BTS is analyzed. Finally, simulation results reveal that the proposed technique can significantly reduce the beam training time for IRS-assisted mmWave cellular systems.
The polarimetric massive multiple-input multiple-output (MIMO) radio channel of an indoor line-of-sight scenario is investigated at 1.35 GHz using a real-time radio channel sounder. The 8 x 12 massive MIMO transmitter...
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The polarimetric massive multiple-input multiple-output (MIMO) radio channel of an indoor line-of-sight scenario is investigated at 1.35 GHz using a real-time radio channel sounder. The 8 x 12 massive MIMO transmitter is constructed using a hybrid architecture including a vertical uniform linear array translated at different horizontal positions forming a virtual, yet realistic, uniform rectangular array. The performance of the system is evaluated with six users distributed in the room for different polarisation schemes and receiver orientations using propagation channel-based metrics (such as receiver spatial correlation and Rician factor) and system-oriented metrics such as sum-rate capacity and signal to interference and noise ratio. The results show a clear dependence of the performance to the polarisation schemes and receiver orientation and showing that when facing the array, cross-polarisation can be very beneficial. Furthermore, it is concluded that the additional degree of freedom brought by the polarisation diversity can contribute to improve spectral efficiency (similar to 20% depending on the configuration), paving the way for further capacity enhancements in massive MIMO systems. It was also found that the receiver spatial correlation can be modelled using a Burr distribution.
The upcoming fifth-generation wireless mobile systems are projected to be commercialized in the year 2020 and are set to play the main role in massive multiple input-multiple output (mMIMO) integrated with the technol...
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The upcoming fifth-generation wireless mobile systems are projected to be commercialized in the year 2020 and are set to play the main role in massive multiple input-multiple output (mMIMO) integrated with the technologies of beamforming antenna arrays. However, the performance of mMIMO is constrained by inter-cell interference from adjacent cells triggered by the reused pilot, an issue termed pilot contamination. To address this issue, this paper focuses on mitigating pilot contamination by implementing a suboptimal spatial source detection method based on the beamforming approach using a two-dimension-unitary estimation of the signal parameters through rotational invariance techniques algorithm. We jointly used 2D-AOA information (azimuth and elevation angles) and statistical channel estimations at the BSs to identify the channels correlation condition and evaluate the sum rate performance of users based on AOA. The detected signals from the uniform rectangular array are used to segregate the required signal from the interfering signal without any change to the pilot construction of the training signals. The performance of the minimum mean squared error beamforming (MMSE-beamforming) technique in the multi-cell mMIMO system of the aforementioned method is numerically evaluated and then compared with conventional methods that depend only on pilot identity information. The simulation reveals that the achievable sum rate gains of 2D-AOA and the pilot identity information techniques (best case) with respect to deterministic MMSE are 96.3% and 85.4%, respectively, thus showing the prospect of eliminating the majority of pilot contamination using the 2D-AOA estimation.
In this paper, we address the problem of direction-of-arrival (DOA) estimation of multipath signals in the presence of gain-phase uncertainties using an auxiliary source (AS) with uniform rectangular array. Based on t...
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In this paper, we address the problem of direction-of-arrival (DOA) estimation of multipath signals in the presence of gain-phase uncertainties using an auxiliary source (AS) with uniform rectangular array. Based on the assumption that the waveform of the AS is a known prior, and the signal of the AS impinges on the array without multipath propagation, a two-step algorithm is proposed to estimate the DOAs along with the fading coefficients and gain-phase errors. First, a coarse estimation is obtained by extending the traditional spatial smoothing-based ESPRIT algorithm. Second, in order to overcome the performance deterioration due to a reduction of the effective array aperture, an alternate iterative algorithm is proposed. Meanwhile, the relevant stochastic Cramer-Rao bound (CRB) is also derived. Simulation results show that the proposed method is capable of approaching the stochastic CRB when the signal-noise ratio (SNR) of the AS is large enough and is greater than the SNR of the unknown source. (c) 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
For two-dimensional (2D) direction of arrival (DOA) estimation in a uniform rectangular array (URA), the conventional method converts the 2D problem into a one-dimensional (1D) problem;however, the computational compl...
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For two-dimensional (2D) direction of arrival (DOA) estimation in a uniform rectangular array (URA), the conventional method converts the 2D problem into a one-dimensional (1D) problem;however, the computational complexity is high, and the accuracy is limited by the grid interval. To address this issue, based on sparse representation theory and a separable observation model (SPM), this paper presents a novel off-grid-framework-based 2D DOA estimation approach by designing a modified 2D off-grid model and a solution for the multisnapshot case in the SPM. The proposed algorithm can be divided into two stages. In the first stage, we use a matching pursuit and focal underdetermined system solver (MFOCUSS) algorithm to quickly identify the candidate or potential areas where the true sources may exist. In the second stage, the candidate areas obtained in the first stage are regarded as the initialization. Then, for a specific source, we regard other sources as interference. By using an alternating descent method, we can obtain accurate DOAs. Moreover, based on the equivalence of time delay and spatial spacing, a 2D off-grid method for multisnapshot cases is proposed in this paper. Numerical simulations demonstrate the effectiveness and efficiency of the proposed algorithm.
This paper studies autocorrelation complementary matrices (ACM), a set of N matrices of size M x L whose two-dimensional autocorrelations add to a two-dimensional deltafunction, which we refer to as a set of (M;N;L)-A...
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ISBN:
(纸本)9781728143002
This paper studies autocorrelation complementary matrices (ACM), a set of N matrices of size M x L whose two-dimensional autocorrelations add to a two-dimensional deltafunction, which we refer to as a set of (M;N;L)-ACM. The ACM is an extension of the Golay complementary sequences to a matrix form. In addition to an existing approach in the literature to construct the ACM, we show that i) a set of (M;N;L)-complete complementary codes (CCC) is actually a set of (M;N;L)-ACM, and ii) from two pairs of complementary sequences of length M and L we can construct a set of (M;4;L)-ACM (i.e., N = 4). As an application of the ACM, we show how it can be applied to omnidirectional precoding for a multi-input multi-output (MIMO) communication system with a uniform rectangular array (URA).
In this paper, we investigate the downlink achievable ergodic spectral efficiency (SE) of a single-cell multi-user millimeter wave system, in which a uniform rectangular array is used at the base station (BS) to serve...
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In this paper, we investigate the downlink achievable ergodic spectral efficiency (SE) of a single-cell multi-user millimeter wave system, in which a uniform rectangular array is used at the base station (BS) to serve multiple single-antenna users. We adopt a three-dimensional channel model by considering both the azimuth and elevation dimensions under single-path propagation. We derive the achievable ergodic SE for this system in with maximum ratio transmission precoding. This analytical expression enables the accurate and quantitative evaluation of the effect of the number of BS antennas, signal-to-noise ratio (SNR), and the crosstalk (squared inner product between different steering vectors) which is a function of the angles of departure (AoD) of users and the inter-antenna spacing. Results show that the achievable ergodic SE logarithmically increases with the number of BS antennas and converges to a value in the high SNR regime. To improve the achievable ergodic SE, we also propose a user scheduling scheme based on feedback of users' AoD information and obtain the maximum achievable ergodic SE. Furthermore, we consider a dense user scenario where every user's AoD becomes nearly identical and then derive the system's minimum achievable SE.
In the field of direction of arrival (DOA) estimation, there exists no problem of angle merging and it has low sidelobe characteristics with the uniform rectangular array. But when sensors in the uniformrectangular a...
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ISBN:
(纸本)9781538669563
In the field of direction of arrival (DOA) estimation, there exists no problem of angle merging and it has low sidelobe characteristics with the uniform rectangular array. But when sensors in the uniform rectangular array are partially damaged, the two-dimensional DOA estimation performance of the original algorithms will seriously decline, and even have a performance failure in some cases. To solve the problem, we study the inexact augmented Lagrange multiplier method (IALM). Through utilizing features of low-rank matrix, obtained by the tensor unfolding in different modes, in the tensor model of the received signal, we propose the IALM-ESPRIT algorithm. Compared with the direct ESPRIT algorithm, the performance of two-dimensional DOA estimation is significantly improved when partial sensors damaged.
The performance of the conventional adaptive beamformer undergoes degradation in the presence of the mutual coupling between the neighbouring elements. To eliminate the sensitivity for the MC, the dummy elements are f...
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The performance of the conventional adaptive beamformer undergoes degradation in the presence of the mutual coupling between the neighbouring elements. To eliminate the sensitivity for the MC, the dummy elements are fixed around the array. Here, the authors demonstrate the optimal layers of auxiliary elements for uniform rectangular array (URA) in the case of the specific MC model and give the concrete theoretical proof. The corresponding derivation proves that only one layer of auxiliary elements is needed to tackle with the MC effect, and the output SINR and beampattern are improved by means of the proposed method for URA. Finally, the simulation results have shown the effectiveness of authors' method.
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