Automotive antennas are gaining importance due to their increasingly important role for autonomous driving with the development of the Internet of Vehicles. However, over‐the‐air testing on ...automotive antennas is difficult owing to its large volume and complex body structure. Plane wave generators can approximate uniform plane waves in the near field of the device under test, which can greatly reduce the measurement distance and thereby decreasing the cost compared with direct far‐field solutions. This letter designs three plane wave generators for three quiet zone sizes selected according to the vehicle structure at 5.9 GHz, achieving quiet zone sizes of 1.45 m ×0.23$\times 0.23$ m, 2.9m ×0.56$\times 0.56$ m, and 3.9 m ×1.27$\times 1.27$ m, respectively. Within the three quiet zones, amplitude deviations of 0.82, 0.34, and 0.34 dB and phase deviations of 9.4∘${9.4^\circ }$, 6.72∘${6.72^\circ }$ and 1.42∘${1.42^\circ }$ are realized, respectively, according to the numerical simulations. Uncertainty analysis is further implemented to investigate the robustness of the designed PWGs proposed in this letter.
This letter designs three plane wave generators for three quiet zone sizes selected according to the vehicle structure at sub‐6 GHz, achieving amplitude deviations of 0.82, 0.34, and 0.34 dB and phase deviations of 9.4∘$9.4^{\circ }$, 6.72∘$6.72^{\circ }$, and 1.42∘$1.42^{\circ }$, respectively, according to the numerical simulations. Uncertainty analysis is further implemented to investigate the robustness of the designed PWGs proposed in this letter.
In this paper, an effective method for developing a multi-feed multiple-input multiple-output (MIMO) antenna system using the metal rims of a mobile phone without any structural interruption on the ...long edge frames is proposed. Instead of traditionally designing MIMO antennas with multiple similar antenna structures on the mobile phone frame or its ground plane, the MIMO antennas in this work are realized by reasonably constructing feeding points and grounding points on the entire edge frame. The MIMO antenna system established by such multi-feed technique is capable to achieve much simpler structural configuration, excellent isolation and matching performance while multiple antennas are connected. A planar eight-port MIMO antenna system operating in the 5G frequency band of 3.4~3.6 GHz is investigated initially, and subsequently applied to the curved metal-rims which comply with the industry design of a modern flagship mobile phone. The prototypes are fabricated and measured, evaluation results show that isolations among all ports are better than 15 dB with reflection coefficients below −10 dB within the band of 3.4~3.7 GHz and −6 dB within the band of 3.3~3.8 GHz. In addition, more than 57% total efficiency and envelope correlation coefficient (ECC) of less than 0.3 are obtained. The satisfactory performance reveals the proposed design of multi-feed MIMO antennas can be a promising candidate for 5G metal-rimmed mobile phone applications.
A distributed interference coordination scheme is proposed to alleviate cross-tier and inner-tier interference in heterogeneous network (HetNet), consisting of a power control strategy based on game ...theory to acquire both Nash equilibrium among femtocells and Stackelberg equilibrium between femtocells and macrocells. Component carrier assignment is the other interference coordination dimension for HetNet with carrier aggregation. The proposed method is a two-dimensional interference coordination scheme combining power control and component carrier assignment. The simulation results demonstrate the effectiveness and improvement of the proposed scheme.
In orthogonal frequency-division multiplexing systems, the temporal channel gains to estimate are much more than the observable data over highly mobile channels. The basis expansion model (BEM) has ...been employed to reduce the number of these channel parameters. In the absence of channel statistics, generalized complex-exponential BEM (GCE-BEM) is popular for its fast algebra operation and easy generation of basis matrix. However, there is still much potential for performance improvement by modeling error reduction. In this paper, the factors affecting the modeling error are analyzed and an iterative decomposed estimation algorithm is proposed to improve the modeling accuracy. The proposed algorithm decomposes each tap into the linear part and the non-linear part. The linear part with two parameters (the middle value and the slope) is initialized by estimation in linearly time-varying channel models. And the non-linear part is addressed by the conventional least-squares (LS) method based on GCE-BEM and then the slopes of the linear part are updated for the next iteration by two distinct slope update methods. The simulations show that the proposed algorithm outperforms the conventional estimation methods with significantly reduced modeling error under both high signal to noise ratio and Doppler shift conditions.
Abstract
As the key to wireless communication, channel estimation has become a hot research topic in recent years. In this paper, we propose a deep learning method based on the channel estimation of ...inverse convolutional network and expanded convolutional network to address the problems that the performance of traditional channel estimation algorithms in orthogonal frequency division multiplexing (OFDM) systems can hardly meet the communication requirements of complex scenarios and are greatly affected by noise. The method constructs a lightweight deconvolutional network using the correlation of channels, and achieves channel interpolation and estimation step by step with a few layers of deconvolutional operations, which achieves channel estimation with low complexity. To improve the estimation performance, an expanded convolutional network is further constructed to suppress the channel noise and improve the accuracy of channel estimation. The simulation results show that the channel estimation can be performed at different signal levels. The simulation results show that the proposed deep learning method based on deconvolution and dilation convolution has lower estimation error and lower complexity than the traditional methods under different signal-to-noise ratios (SNR).
Abstract
The 5G AGPS positioning technology has been widely used in wireless devices. The principle, test method and test system of the 5G AGPS positioning technology are presented in this paper. ...This method can evaluate positioning antenna performance in simulated environment that is close to real use. The test results show that the system can reflect the positioning antenna performance of EUT very well and provide the test guarantee for user experience.
The real-time kinematic technology has been widely used in positioning terminals. The principle, test method of the real-time kinematic technology and its application in terminal positioning test are ...presented in this paper. A virtual drive test system is developed by using the real-time kinematic technology, and the positioning performance of the terminal is tested under different road sections. The test results show that the system can evaluate the terminals performance under the real application scenarios very well.
Time-varying channel gains are approximated by basis expansion model (BEM) to make the tremendous unknowns estimation feasible in orthogonal frequency division multiplexing (OFDM) systems. However, ...sparse dispersive channel requires overloaded subcarriers for pilot-aided estimation in the framework of BEM. This paper proposes a channel estimation scheme over time-varying and sparse dispersive channel with circular grouped pilot pattern, which occupies much less subcarriers. In this scheme, the sparse tap delays are detected with the interpolated channel frequency response and the modified BEM based estimation deals with only the detected taps, eliminating the noise interference from the null taps. The proposed estimator outperforms the existing methods applied to sparse dispersive channel with higher spectral efficiency. Our claims are verified by simulation results, which are obtained in COST207 typical urban channel model.
Fifth-generation (5G) wireless communication technologies play a crucial role in supporting the pervasive implementation of the Campus Internet of Things (IoT). The application of 5G wireless ...communication in Campus IoT will introduce unique channel characteristics that need to be fully explored through channel measurement and channel modeling in various campus scenarios. In this article, a channel sounding system based on the universal software-defined radio peripheral (USRP) is designed, which can efficiently collect channel measuring data in diverse settings. Based on this system, channel measurements with omnidirectional and directional antennas at the 4.9, 5.2, and 5.8-GHz bands for multicase are conducted. The measurement cases include the path loss (PL) measurements for both outdoor and indoor scenarios, the penetration loss measurements for indoor and outdoor materials, the outdoor to indoor (O2I) measurements, and the blockage effect measurements. The channel characteristics, involving PL, shadow fading, penetration loss, and blockage effect, are extracted and analyzed. The PL models, penetration loss models, O2I PL models, and models for blockage effects at measured frequency bands are proposed to predict and validate channel characteristics. The channel measurement and modeling results not only demonstrate the practicality of the proposed sounding system but also provide realistic channel characteristics for the research on 5G wireless communication systems in Campus IoT scenarios.
This paper proposes a novel recursive approach for orthogonal frequency division multiplexing (OFDM) channel estimation over highly mobile channels without any priori channel statistics. The key idea ...is to decompose each objective channel into the known component and the rest for estimation. The known component is the output of the prior iteration except that the first one is attained in linear time-varying (LTV) model. In each iteration, the rest channel component, obtained by subtracting the known channel component from the original channel, is estimated in generalized complex exponential basis expansion model (GCEBEM). Since the rest component varies much milder than the original channel, both modeling error and inter-carrier interference (ICI) are significantly reduced in GCEBEM-based estimation. Monte Carlo simulations demonstrate the superiority of the proposed approach with a few iterations over the conventional methods under highly mobile conditions.
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