Short-range Multiple-input Multiple-output Research Articles

Optimization of Mismatched Filters With Asymmetric Side-Lobe Shape for Short-Range MIMO Radars

This paper presents the design of signal compression and separation filters with asymmetric responses for multiple-input multiple-output (MIMO) radars that use pulses longer than the maximum return time of the reflected signal. Such radars suffer from direct penetration of the transmitted signal to the receiver, appearing as a very strong stationary reflection in the zero range. After pulse compression, the far-side lobes of this crosstalk may compete with the reflections of distant weak targets and limit the maximum radar range. Hence, in addition to the maximum suppression of the direct transmitted signal penetration to the receiver, the far-side lobe reduction of this crosstalk with positive time lags is desirable. Asymmetric response filters allow optimization to be focused on the region where the maximum suppression of crosstalk between the transmitted signal and the receiver is desired. Extreme suppression was achieved by applying lower demand in other areas and other parameters. In this paper, the problem is described in more detail along with the mathematical apparatus by which asymmetric filter outputs can be achieved.

Spatial frequency-based angular behavior of a short-range flicker-free MIMO-OCC link.

In this paper, we provide a solution based on spatial frequency fsf to study the angular behavior of a flicker-free, short-range indoor multiple-input multiple-output (MIMO) optical camera communications (OCC) link. We focus on the experimental investigation of OCC's performance for the transmitters (Txs) [i.e., light-emitting diode (LED) based arrays] located at the same and different distances from the receiver (Rx) with the off-axis rotation angle θ. We have used two 8×8 distributed LED arrays and a commercial low-cost complementary metal-oxide-semiconductor (CMOS) Raspberry Pi camera with the rolling-shutter capturing mode as the Tx and Rx, respectively. The image and the respective communications link quality metrics are measured in terms of the peak signal-to-noise ratio (PSNR) and the rate of successfully received bits with respect to fsf for different camera shutter speeds (SS). A CMOS image sensor noise characterization is carried in terms of the signal-to-noise ratio (SNR) and PSNR. The proposed study provides a 100% success rate in data reception at the optimum θ of 50° at lower captured values of fsf, which is projected onto the image sensor in the form of pixels. Moreover, the effect of channel saturation over fsf is studied with respect to θ and SS and we show that, for θ exceeding the optimum value along transmission range, the fsf area of the Txs reduces to less than ∼50% of the captured Tx units at θ of 0°, where no data can be fully recovered.

Complex ResNet Aided DoA Estimation for Near-Field MIMO Systems

The near-field effect of short-range multiple-input multiple-output (MIMO) systems imposes many challenges on direction-of-arrival (DoA) estimation. Most conventional scenarios assume that the far-field planar wavefronts hold. In this paper, we investigate the DoA estimation problem in short-range MIMO communications, where the effect of near-field spherical wave is non-negligible. By converting it into a regression task, a novel DoA estimation framework based on complex-valued deep learning (CVDL) is proposed for the near-field region in short-range MIMO communication systems. Under the assumption of a spherical wave model, the array steering vector is determined by both the distance and the direction. However, solving this regression task containing a massive number of variables is challenging, since datasets need to capture numerous complicated feature representations. To overcome this, a virtual covariance matrix (VCM) based on received signals is constructed, and thus such features extracted from the VCM can deal with the complicated coupling relationship between the direction and the distance. Although the emergence of wireless big data driven by future communication networks promotes deep learning-based wireless signal processing, the learning algorithms of complex-valued signals are still ongoing. This paper proposes a one-dimensional (1-D) residual network that can directly tackle complex-valued features due to the inherent 1-D structure of signal subspace vectors. In addition, we put forth a cropped VCM based policy which can be applied to different antenna sizes. The proposed method is able to fully exploit the complex-valued information. Our simulation results demonstrate the superiority of the proposed CVDL approach over the baseline schemes in terms of the accuracy of DoA estimation.

Analog Eigenmode Transmission for Short-Range MIMO Based on Orbital Angular Momentum

This paper proposes an analog eigenmode transmission technique suitable for a short-range multiple-input multiple-output (SR-MIMO) system consisting of arbitrary power-of-two number of antennas utilizing the idea of orbital angular momentum. In the proposed technique, uniform circular arrays that are coaxially arranged are used at both the transmitting (Tx) and receiving (Rx) sides. With this array configuration, the channel matrix is always a circulant matrix regardless of antenna type, array radius, Tx–Rx distance, and rotation about the coaxis. Due to the characteristics of a circulant matrix, the channel matrix can be diagonalized independently of the above-mentioned factors by fixed-weight beamforming based on a discrete Fourier transform (DFT) matrix uniquely determined by just the number of antennas. In this paper, the operating principle of the proposed technique is discussed from the viewpoints of linear algebra, and some example network configurations are presented with the determination of the DFT-matrix weight. Numerical analyses confirm the two important features of the proposed technique: 1) support of more than $4\times 4$ SR-MIMO and 2) independence with regard to rotation about the coaxis. Furthermore, an experiment on a fabricated DFT circuit confirmed the feasibility of the proposed technique in realizing practical short-range communication.

Transmit Design for Short-Range MIMO Channels With the Spherical-Wave Model

In this letter, we investigate the transmit design for short-range multiple-input multiple-output (MIMO) channels with the spherical-wave model (SWM) in three-dimensional (3D) space. We first establish the antenna array with arbitrary orientations in 3D space. On this basis, we propose a practical and low-complexity transmit scheme with the SWM in short-range MIMO channels. The analytical expressions for the transmit directions and the power allocation of the proposed transmit scheme is also derived. Both the analytical and simulation results show that the proposed scheme can obtain performance improvement compared with the equal power transmission.

Analog Eigenmode Transmission for Short-Range MIMO

This paper proposes a method of implementing analog eigenmode transmission for a short-range multiple-input–multiple-output (SR-MIMO) system that uses only 180° hybrid couplers. If the short-range MIMO system places transmitting and receiving arrays in line-of-sight (LOS) and symmetrically with respect to specific reference planes, the channel matrix in the system also becomes symmetrical. This allows the channel matrix to be diagonalized by connecting 180° hybrid couplers to both ports at the transmitter and receiver sides, i.e., eigenmode transmission can be realized. In this paper, first, the theory of the proposed technique is explained by taking a 2 x 2 MIMO as an example, based on the characteristics of 180° hybrid coupler and the theory of the cascade-connected network. Moreover, an extension to the method that offers 4 x 4 MIMO is also proposed. This paper clarifies that this proposed technique can diagonalize the channel matrix, regardless of array configuration, such as type of antennas and antenna spacing, as long as the symmetry of the system configuration is assured. Furthermore, numerical results verify that the distance between the transmitter and the receiver has no effect on channel orthogonality. As a result, this technique partially avoids the performance degradation caused by array displacement, which is a major disadvantage of the conventional analog-beamforming-based decoding technique for short-range MIMO systems. Thus, the superiority of the proposed technique is clear.

A Novel ZF-Based Fast Beamforming Method for Short-Range MIMO Transmission

Millimeter-wave short-range multiple-input multiple-output (SR-MIMO) transmission employing zero-forcing beamforming (ZF-BF) at the information kiosk side can improve transmission rate without increasing mobile terminal power consumption for MIMO signal processing. However, processing delay for ZF weight generation is large, so the effects of time-varying channels due to the user's hand jiggling, which cause performance degradation, cannot be ignored. In this letter, a novel fast beamforming method is described with which ZF-based weight can be generated with low delay by utilizing the relationship of channel variation and ZF weight variation. Simulation results show that the method can achieve better performance than ZF-BF.

Spherical-wave model for short-range MIMO

The plane-wave assumption has been used extensively in array signal processing, parameter estimation, and wireless channel modeling to simplify analysis. It is suitable for single-input single-output and single-input multiple-output systems, because the rank of the channel matrix is one. However, for short-range multiple-input multiple-output (MIMO) channels with a line-of-sight (LOS) component, the plane-wave assumption affects the rank and singular value distribution of the MIMO channel matrix, and results in the underestimation of the channel capacity, especially for element spacings exceeding half a wavelength. The short-range geometry could apply to many indoor wireless local area network applications. To avoid this underestimation problem, the received signal phases must depend precisely on the distances between transmit and receive antenna elements. With this correction, the capacity of short-range LOS MIMO channels grows steadily as the element spacing exceeds half a wavelength, as confirmed by measurements at 5.8 GHz. In contrast, the capacity growth with element spacing diminishes significantly under the plane-wave assumption. Using empirical fitting, we provide a threshold distance below which the spherical-wave model is required for accurate performance estimation in ray tracing.