channel matrix
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2022 ◽  
Vol 7 (1) ◽  
pp. 143-155
Author(s):  
Jin Cheng ◽  

<abstract><p>In this paper, global exponential outer synchronization of coupled nonlinear systems with general coupling matrices are investigated via pinning impulsive control. More realistic and more general partially coupled drive-response systems are established, where the completely communication channel matrix between coupled nodes may not be a permutation matrix. By using pinning impulsive strategy involving pinning ratio and our generalised lower average impulsive interval method, a number of novel and less restrictive synchronization criteria are proposed. In the end, a numerical example is constructed to indicate the effectiveness of our theoretical results.</p></abstract>


Symmetry ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2423
Author(s):  
Edgar Dmitriyev ◽  
Eugeniy Rogozhnikov ◽  
Natalia Duplishcheva ◽  
Serafim Novichkov

The growing demand for broadband Internet services is forcing scientists around the world to seek and develop new telecommunication technologies. With the transition from the fourth generation to the fifth generation wireless communication systems, one of these technologies is beamforming. The need for this technology was caused by the use of millimeter waves in data transmission. This frequency range is characterized by heavy path loss. The beamforming technology could compensate for this significant drawback. This paper discusses basic beamforming schemes and proposes a model implemented on the basis of QuaDRiGa. The model implements a MIMO channel using symmetrical antenna arrays. In addition, the methods for calculating the antenna weight coefficients based on the channel matrix are compared. The first well-known method is based on the addition of cluster responses to calculate the coefficients. The proposed one uses the singular value decomposition of the channel matrix into clusters to take into account the most correlated information between all clusters when calculating the antenna coefficients. According to the research results, the proposed method for calculating the antenna coefficients allows an increase in the SNR/SINR level by 8–10 dB on the receiving side in the case of analog beamforming with a known channel matrix.


2021 ◽  
Vol 2140 (1) ◽  
pp. 012013
Author(s):  
Mahmoud Eissa ◽  
D Sukhanov

Abstract This paper presents a technique for obtaining a well-conditioned channel matrix in a line of sight multiple input multiple output (MIMO) environment. The technique is based on the implementation of a back-to-back antenna system as a passive repeater to enhance performance in MIMO systems. The flexible configuration with no need for a phase controller allows to spread the proposed repeater in MIMO communications to ensure spatial multiplexing and enhance capacity. A condition number and matrix rank are proposed as metrics to demonstrate the validity of the proposed method.


2021 ◽  
Author(s):  
◽  
Callum Thomas Neil

<p>A novel technical solution, and paradigm shift, envisioned to achieve the significant spectral efficiency enhancements required for Fifth Generation (5G) wireless systems is massive multiple-input-multiple-output (MIMO). Massive MIMO systems scale up the number of transmit (TX) and receive (RX) antennas by at least an order of magnitude relative to conventional multi-user MIMO systems, which have been a key feature in current wireless standards, such as Long Term Evolution. Thus, massive MIMO leverages the spatial dimension by providing significant increases in all the virtues of conventional MIMO systems but on a much larger scale. Namely, data rate, link reliability, energy efficiency, and multiplexing gains can all be increased with massive MIMO systems, while simultaneously reducing inter-user interference through digital processing techniques. Further motivating the surge in research of massive MIMO systems are the additional channel properties which occur when operating with large dimensions. These properties arise as a result of random matrix theory asymptotics and under these conditions random variables become deterministic, simplifying analysis and allowing simple processing techniques to become (near) optimal. These idealistic properties, however, are based on the assumptions of an independent and identically distributed channel matrix with an infinite number of TX antennas.  Physical contraints typically prohibit the deployment of large numbers of TX antennas. It therefore seems natural to determine the number of TX antennas required for large MIMO systems to begin to exhibit these favourable asymptotic properties. Analytically deriving the first and second moments of the composite Wishart channel matrix and numerically defining three convergence metrics, the rate of channel convergence is examined. Limiting matched-filter (MF) and zero-forcing precoding signal-to-interference-plus-noise-ratio (SINR) performances are then analytically derived and rate of convergence shown. Coordinated distributed MIMO systems can mitigate the detrimental effects of spatial correlation relative to a colocated MIMO system. The instantaneous and limiting MF SINR performance of a distributed massive MIMO system is derived, allowing clear insights into the effects of imperfect channel state information, spatial correlation, link gains and number of antenna clusters. The wide bandwidths vacant at millimeter-wave (mmWave) frequency bands are suitable for 5G wireless systems since they occupy regions of uncongested spectrum which enable large contiguous bandwidth carriers. Spatial correlation of an arbitrary antenna array topology is analytically derived for a mmWave channel model. Numerically, the effects of mutual coupling amongst antenna elements is then shown on the effective spatial correlation, eigenvalue structure and user rate of different antenna topologies.   Channel models and measurements across a wide range of candidate bands for 5G wireless systems are then considered, motivated by the different propagation and spatial characteristics between different bands and different channel models within the same band. Key channel modelling and spatial parameter differences are identified and, in turn, their impact on various antenna topologies investigated, in terms of system sum rate, channel eigenvalue structure, effective degrees of freedom and massive MIMO convergence properties.</p>


Author(s):  
M.G. Bakulin ◽  
V.B. Kreyndelin ◽  
S.V. Melnik ◽  
V.A. Sudovtsev ◽  
D.A. Petrov
Keyword(s):  

2021 ◽  
Vol 18 (9) ◽  
pp. 130-147
Author(s):  
Yitian Chen ◽  
Shaoshuai Gao ◽  
Guofang Tu ◽  
Hao Qiu

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1246
Author(s):  
Md Khalid Hossain Jewel ◽  
Rabiu Sale Zakariyya ◽  
Fujiang Lin

Narrowband Internet of Things (NB-IoT) systems were specified by 3GPP in release 13 as a low power wide area network (LPWAN) technology to operate with a very narrow bandwidth of 180 kHz only. Due to fragile radio signal operating conditions (where a signal is weaker than noise), NB-IoT channel status becomes highly complex. Therefore, an effective and low complexity channel estimation will perform a significant role in the receiver operation. The linear minimum mean square error (LMMSE) scheme is very effective in estimating the channel but introduces massive complexity because of having complex matrix inversion. In this paper, we first derive the analytical model of the signal for long-term evolution (LTE)-based NB-IoT downlink systems and propose a reduced complexity LMMSE channel estimation for the downlink NB-IoT systems by applying singular value decomposition (SVD) technique along with partitioning the whole channel matrix into small submatrices. Furthermore, we apply the overlap banded technique to optimize the performance of the proposed channel estimator. As a result of exploiting several submatrices instead of a larger channel matrix, the operational complexity is significantly optimized. Lastly, we propose a polyphase filter structure for implementing the interpolation procedure instead of the conventional interpolation method to further optimize the performance and complexity of the proposed channel estimator further. The performance of the proposed technique has been justified by the mean square error (MSE), bit error rate (BER), and instantaneous throughput for the related signal-to-noise ratio (SNR). The system complexity is verified by the number of complex multiplications used. Simulation evaluations indicate that with the sacrifice of negligible performance, the proposed modified LMMSE technique along with the proposed interpolation possesses a good balance between the performance and the system complexity that could help the proposed techniques to be applied successfully in the low complexity NB-IoT systems.


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