A novel approach for Ultra-wideband MIMO channel modeling

Pistea, Ana-Maria; Palade, Tudor; Moldovan, Anca

doi:10.1109/iccomm.2010.5509014

Cited by 1 publication

(1 citation statement)

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“…The channel transfer function (CTF) (or impulse response) is obtained by fitting a certain parametric function. [24][25][26] In this paper, the signal from first antennas in transmitting antenna array can be expressed as ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi…”

Section: Mimo Channel Transfer Function Concerned Time-varying Movementioning

confidence: 99%

Modeling and simulating the time‐varying movement in MIMO downlink by integrating ADS with Matlab

Gui

Chen

2019

Int J Communication

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Communication systems and radar systems generally face problems caused by time-varying motion, especially in the case of complex radio wave propagation in cities. Therefore, it is necessary to establish a suitable channel model to simulate the system to deal with these problems. This paper refers to the MIMO space-time channel model in the 3rd Generation Partnership Project (3GPP) technical standard and proposes a method for modeling and simulating time-varying motion in a MIMO downlink system according to the characteristics of the wireless channel and the transmission mode. The transmission function in MIMO downlink is derived to calculate the different Doppler frequency shift in the model based on 3GPP. By integrating ADS with Matlab software, environmental parameters and correlation coefficients can be manually set to simulate the downlink. During the simulation process, different modulation model bandwidths and channel conditions are set, and the configuration of the antenna parameters changes accordingly. Finally, the differences of simulation results are analyzed. K E Y W O R D Sbite error rate, MIMO, time-varying movement, wireless channel | INTRODUCTIONMultiple-input multiple-output (MIMO) systems have become a key technology used in mobile communication systems. 1,2 It uses multiple antennas to achieve spatial multiplexing and spatial diversity. As the core of "4G" technology, this technology is a major breakthrough in the field of smart antennas for wireless mobile communication. 3,4 It can increase the capacity of the communication system without increasing the bandwidth. According to the number of transmitting antennas and receiving antennas, MIMO includes SIMO (single-input multiple-output) system and MISO (multiple-input single-output) system. 5,6 The modeling, analysis, and simulation of MIMO communication systems based on fading channels have attracted more and more researchers. [7][8][9] In the process of communication and detection, the quality of communication is often degraded due to the frequent occurrence of time-varying motion. 10,11 Especially in the complex environment of the city, the MIMO array and the complex buildings around the city are seriously disturbed, and it is difficult to model and simulate. This problem is exacerbated when the number of transmitting antennas becomes larger. 12 Today, there are many research results today that address these issues, such as a statistical simulation modeling with 3D, 13,14 a geometrical three-ring-based model built for the fading channels in cooperative networks, 15 and a Ricean fading channel model that includes a fixed (line of sight, LoS) part and a scattering

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Section: Mimo Channel Transfer Function Concerned Time-varying Movementioning

confidence: 99%