scholarly journals Statistical Characteristics of Measured 3-Dimensional MIMO Channel for Outdoor-to-Indoor Scenario in China and New Zealand

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Yawei Yu ◽  
Jianhua Zhang ◽  
Mansoor Shafi ◽  
Min Zhang ◽  
Jawad Mirza
Keyword(s):  
New Zealand ◽  
Channel Model ◽  
Elevation Angle ◽  
Statistical Characteristics ◽  
Mimo Channel ◽  
Delay Spread ◽  
Angle Of Arrival ◽  
Power Delay Profile ◽  
3 Dimensional ◽  
Rms Delay Spread

The 3-dimensional (3D) channel model gives a better understanding of statistical characteristics for practical channels than the 2-dimensional (2D) channel model, by taking the elevation domain into consideration. As different organizations and researchers have agreed to a standard 3D channel model, we attempt to measure the 3D channel and determine the parameters of the standard model. In this paper, we present the statistical propagation results of the 3D multiple-input and multiple-output (MIMO) channel measurement campaign performed in China and New Zealand (NZ). The measurements are done for an outdoor-to-indoor (O2I) urban scenario. The dense indoor terminals at different floors in a building form a typical 3D propagation environment. The key parameters of the channel are estimated from the measured channel impulse response (CIR) using the spatial-alternating generalized expectation-maximization (SAGE) algorithm. Till now there is abundant research performed on the azimuth domain; this paper mainly considers the statistical characteristics of the elevation domain. A statistical analysis of 3D MIMO channel results for both China and NZ measurements is presented for the following parameters: power delay profile (PDP), root mean square (rms), delay spread (DS), elevation angle-of-arrival (EAoA) distribution, elevation angle-of-departure (EAoD) distribution, elevation angular spread (AS), and cross-polarization discrimination (XPD).

scholarly journals The Impact of Antenna Height on 3D-MIMO Channel: a Ray Launching Based Analysis

2017 ◽  
Author(s):  
Qi Hong ◽  
Jiliang Zhang ◽  
Hui Zheng ◽  
Hao Li ◽  
Haonan Hu ◽  
...  
Keyword(s):  
Channel Model ◽  
Elevation Angle ◽  
Base Station ◽  
Mimo Channel ◽  
Delay Spread ◽  
Three Dimension ◽  
Angle Of Arrival ◽  
3D Mimo ◽  
The Impact ◽  
Ray Launching

Three dimension (3D) Multi-input-multi-output (MIMO) scheme, which exploits another dimension of the spatial resource, is one of the enabling technologies for the next generation mobile communication. As the elevation angle in 3D-MIMO channel model might varies against the height of the base station transmit antenna, it has to be taken into account carefully. In this paper, the impact of antenna height on the channel characteristics of 3D MIMO channel is investigated by using the intelligent ray launching algorithm (IRLA). Three typical street scenarios, i.e., the straight street, the fork road and the cross road, are selected as benchmarks. On the basis of simulations, joint and marginal probability density functions (PDFs) of both the elevation angle of departure (EAoD) and the elevation angle of arrival (EAoA) are obtained. The elevation angle spread (AS) and the delay spread (DS) under various antenna heights are also discussed. Simulation results indicate that the PDFs of EAoD and EAoA vary characteristics under different street scenarios. Moreover, the minimum value of the DS can be achieved when the antenna height is half of the building height.

scholarly journals Predicting Wireless MmWave Massive MIMO Channel Characteristics Using Machine Learning Algorithms

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Lu Bai ◽  
Cheng-Xiang Wang ◽  
Jie Huang ◽  
Qian Xu ◽  
Yuqian Yang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Elevation Angle ◽  
Azimuth Angle ◽  
Machine Learning Algorithms ◽  
Statistical Characteristics ◽  
Mimo Channel ◽  
Angle Of Arrival ◽  
Millimetre Wave ◽  
Channel Characteristics ◽  
Mean Square Errors

This paper proposes a procedure of predicting channel characteristics based on a well-known machine learning (ML) algorithm and convolutional neural network (CNN), for three-dimensional (3D) millimetre wave (mmWave) massive multiple-input multiple-output (MIMO) indoor channels. The channel parameters, such as amplitude, delay, azimuth angle of departure (AAoD), elevation angle of departure (EAoD), azimuth angle of arrival (AAoA), and elevation angle of arrival (EAoA), are generated by a ray tracing software. After the data preprocessing, we can obtain the channel statistical characteristics (including expectations and spreads of the above-mentioned parameters) to train the CNN. The channel statistical characteristics of any subchannels in a specified indoor scenario can be predicted when the location information of the transmitter (Tx) antenna and receiver (Rx) antenna is input into the CNN trained by limited data. The predicted channel statistical characteristics can well fit the real channel statistical characteristics. The probability density functions (PDFs) of error square and root mean square errors (RMSEs) of channel statistical characteristics are also analyzed.

scholarly journals Indoor Corridor Wideband Radio Propagation Measurements and Channel Models for 5G Millimeter Wave Wireless Communications at 19 GHz, 28 GHz, and 38 GHz Bands

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Ahmed M. Al-samman ◽  
Tharek Abd Rahman ◽  
Marwan Hadri Azmi
Keyword(s):  
Millimeter Wave ◽  
Free Space ◽  
Path Loss ◽  
Delay Spread ◽  
Angle Of Arrival ◽  
Microwave Band ◽  
Power Delay Profile ◽  
Rms Delay Spread ◽  
Path Loss Exponent ◽  
Line Slope

This paper presents millimeter wave (mmWave) measurements in an indoor environment. The high demands for the future applications in the 5G system require more capacity. In the microwave band below 6 GHz, most of the available bands are occupied; hence, the microwave band above 6 GHz and mmWave band can be used for the 5G system to cover the bandwidth required for all 5G applications. In this paper, the propagation characteristics at three different bands above 6 GHz (19, 28, and 38 GHz) are investigated in an indoor corridor environment for line of sight (LOS) and non-LOS (NLOS) scenarios. Five different path loss models are studied for this environment, namely, close-in (CI) free space path loss, floating-intercept (FI), frequency attenuation (FA) path loss, alpha-beta-gamma (ABG), and close-in free space reference distance with frequency weighting (CIF) models. Important statistical properties, such as power delay profile (PDP), root mean square (RMS) delay spread, and azimuth angle spread, are obtained and compared for different bands. The results for the path loss model found that the path loss exponent (PLE) and line slope values for all models are less than the free space path loss exponent of 2. The RMS delay spread for all bands is low for the LOS scenario, and only the directed path is contributed in some spatial locations. For the NLOS scenario, the angle of arrival (AOA) is extensively investigated, and the results indicated that the channel propagation for 5G using high directional antenna should be used in the beamforming technique to receive the signal and collect all multipath components from different angles in a particular mobile location.

scholarly journals Analysis of Non-Stationarity for 5.9 GHz Channel in Multiple Vehicle-to-Vehicle Scenarios

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3626
Author(s):  
Fang Li ◽  
Wei Chen ◽  
Yishui Shui
Keyword(s):  
Transmission Rate ◽  
Radio Channel ◽  
Vertical Direction ◽  
Statistical Characteristics ◽  
Small Scale ◽  
Delay Spread ◽  
Important Indicator ◽  
Power Delay Profile ◽  
Channel Characteristics ◽  
Vehicle To Vehicle

The vehicle-to-vehicle (V2V) radio channel is non-stationary due to the rapid movement of vehicles. However, the stationarity of the V2V channels is an important indicator of the V2V channel characteristics. Therefore, we analyzed the non-stationarity of V2V radio channels using the local region of stationarity (LRS). We selected seven scenarios, including three directions of travel, i.e., in the same, vertical, and opposite directions, and different speeds and environments in a similar driving direction. The power delay profile (PDP) and LRS were estimated from the measured channel impulse responses. The results show that the most important influences on the stationary times are the direction and the speed of the vehicles. The average stationary times for driving in the same direction range from 0.3207 to 1.9419 s, the average stationary times for driving in the vertical direction are 0.0359–0.1348 s, and those for driving in the opposite direction are 0.0041–0.0103 s. These results are meaningful for the analysis of the statistical characteristics of the V2V channel, such as the delay spread and Doppler spread. Small-scale fading based on the stationary times affects the quality of signals transmitted in the V2V channel, including the information transmission rate and the information error code rate.

scholarly journals PHY, MAC, and RLC Layer Based Estimation of Optimal Cyclic Prefix Length

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4796
Author(s):  
Adriana Lipovac ◽  
Vlatko Lipovac ◽  
Borivoj Modlic
Keyword(s):  
Error Recovery ◽  
Cyclic Prefix ◽  
Closed Form Expression ◽  
Delay Spread ◽  
Radio Link ◽  
Medium Access ◽  
Power Delay Profile ◽  
Rms Delay Spread ◽  
Industry Standard ◽  
New Radio

This work is motivated by growing evidence that the standard Cyclic Prefix (CP) length, adopted in the Long Term Evolution (LTE) physical layer (PHY) specifications, is oversized in propagation environments ranging from indoor to typical urban. Although this ostensibly seems to be addressed by 5G New Radio (NR) numerology, its scalable CP length reduction is proportionally tracked by the OFDM symbol length, which preserves the relative CP overhead of LTE. Furthermore, some simple means to optimize fixed or introduce adaptive CP length arose from either simulations or models taking into account only the bit-oriented PHY transmission performance. On the contrary, in the novel crosslayer analytical model proposed here, the closed-form expression for the optimal CP length is derived such as to minimize the effective average codeblock length, by also considering the error recovery retransmissions through the layers above PHY—the Medium Access Control (MAC) and the Radio Link Control (RLC), in particular. It turns out that, for given protective coding, the optimal CP length is determined by the appropriate rms delay spread of the channel power delay profile part remaining outside the CP span. The optimal CP length values are found to be significantly lower than the corresponding industry-standard ones, which unveils the potential for improving the net throughput.

Research on Improvement of the Next Generation IEEE802.11ac Channel Model

2013 ◽  
Vol 712-715 ◽  
pp. 1741-1745
Author(s):  
Hao Cai ◽  
Dan Ao Han
Keyword(s):  
Wireless Local Area Network ◽  
Channel Model ◽  
Local Area Network ◽  
Local Area ◽  
Task Group ◽  
Mimo Channel ◽  
Area Network ◽  
Power Delay Profile ◽  
Ieee 802.11Ac ◽  
Set Up

Based on the special correlation of antennas and the power delay profile (PDP) of the cluster model, six models of A-F have been established by the TGn task-group in total. On the basis of the new broadband wireless local area network (WLAN) standard--IEEE 802.11ac with larger bandwidth and multi-user requirements drawn up by the TGac task-group, in this paper, the IEEE 802.11ac channel model is set up by means of improving and simulating the indoor MIMO channel.

scholarly journals A Flexible FPGA-Based Channel Emulator for Non-Stationary MIMO Fading Channels

2020 ◽  
Vol 10 (12) ◽  
pp. 4161
Author(s):  
Qiuming Zhu ◽  
Wei Huang ◽  
Kai Mao ◽  
Weizhi Zhong ◽  
Boyu Hua ◽  
...  
Keyword(s):  
Fading Channels ◽  
Channel Model ◽  
Multiple Input Multiple Output ◽  
Mimo Channel ◽  
Channel Fading ◽  
Power Delay Profile ◽  
Channel Emulator ◽  
Field Programmable ◽  
Fpga Chip ◽  
Doppler Power

In this paper, a discrete non-stationary multiple-input multiple-output (MIMO) channel model suitable for the fixed-point realization on the field-programmable gate array (FPGA) hardware platform is proposed. On this basis, we develop a flexible hardware architecture with configurable channel parameters and implement it on a non-stationary MIMO channel emulator in a single FPGA chip. In addition, an improved non-stationary channel emulation method is employed to guarantee accurate channel fading and phase, and the schemes of other key modules are also illustrated and implemented in a single FPGA chip. Hardware tests demonstrate that the output statistical properties of proposed channel emulator, i.e., the probability density function (PDF), cross-correlation function (CCF), Doppler power spectrum density (DPSD), and the power delay profile (PDP) agree well with the corresponding theoretical ones.

scholarly journals Statistical Analysis of 5G Channel Propagation using MIMO and Massive MIMO Technologies

2021 ◽  
Vol 11 (4) ◽  
pp. 7417-7423
Author(s):  
Z. A. Shamsan
Keyword(s):  
Antenna Arrays ◽  
Massive Mimo ◽  
Multiple Input Multiple Output ◽  
Small Scale ◽  
Delay Spread ◽  
Band Frequency ◽  
Power Delay Profile ◽  
Mimo Antenna ◽  
Rms Delay Spread ◽  
Path Lengths

Multiple Input Multiple Output (MIMO) and massive MIMO technologies play a significant role in mitigating five generation (5G) channel propagation impairments. These impairments increase as frequency increases, and they become worse at millimeter-waves (mmWaves). They include difficulties of material penetration, Line-of-Sight (LoS) inflexibility, small cell coverage, weather circumstances, etc. This paper simulates the 5G channel at the E-band frequency using the Monte Carlo approach-based NYUSIM tool. The urban microcell (UMi) is the communication environment of this simulation. Both MIMO and massive MIMO use uniformly spaced rectangular antenna arrays (URA). This study investigates the effects of MIMO and massive MIMO on LOS and Non-LOS (NLOS) environments. The simulations considered directional and omnidirectional antennas, the Power Delay Profile (PDP), Root Mean Square (RMS) delay spread, and small-scale PDP for both LOS and NLOS environments. As expected, the wide variety of the results showed that the massive MIMO antenna outperforms the MIMO antenna, especially in terms of the signal power received at the end-user and for longer path lengths.

scholarly journals Nonisotropic Scattering Characteristic in an Alternant Tree-Blocked Viaduct Scenario on High-Speed Railway at 2.35 GHz

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Rongchen Sun ◽  
Cheng Tao ◽  
Liu Liu ◽  
Zhenhui Tan ◽  
Lingwen Zhang ◽  
...  
Keyword(s):  
High Speed ◽  
Channel Model ◽  
Radio Channel ◽  
Statistical Characteristics ◽  
Real Field ◽  
Line Of Sight ◽  
Angle Of Arrival ◽  
High Speed Railway ◽  
Scattering Characteristic ◽  
Nonisotropic Scattering

This paper presents the nonisotropic scattering characteristic of the mobile radio channel in an alternant tree-blocked viaduct scenario on high-speed railway (HSR) by real field measuring at 2.35 GHz. An angle of arrival (AOA) probability density function (PDF) is proposed for the nonuniform AOA at the mobile caused by stochastically distributed scatterers. Two Von Mises angular distributions with broad applicability are used to represent the line of sight (LOS) component and part of the scattering component in the AOA model. Based on such a PDF statistical characteristics of Ricean factor,κ, and AOA of the scattering component are modeled in LOS and obstructed line of sight (OLOS) cases, respectively. The results may give a meaningful and accurate channel model and could be utilized in HSR viaduct scenario evaluation.

scholarly journals Channel Measurements and Modeling at 6 GHz in the Tunnel Environments for 5G Wireless Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Shuang-de Li ◽  
Yuan-jian Liu ◽  
Le-ke Lin ◽  
Zhong Sheng ◽  
Xiang-chen Sun ◽  
...  
Keyword(s):  
Path Loss ◽  
Measured Data ◽  
Line Of Sight ◽  
Delay Spread ◽  
Channel Measurements ◽  
Angle Of Arrival ◽  
Rms Delay Spread ◽  
K Factor ◽  
Reference Distance ◽  
Loss Models

Propagation measurements of wireless channels performed in the tunnel environments at 6 GHz are presented in this paper. Propagation characteristics are simulated and analyzed based on the method of shooting and bouncing ray tracing/image (SBR/IM). A good agreement is achieved between the measured results and simulated results, so the correctness of SBR/IM method has been validated. The measured results and simulated results are analyzed in terms of path loss models, received power, root mean square (RMS) delay spread, Ricean K-factor, and angle of arrival (AOA). The omnidirectional path loss models are characterized based on close-in (CI) free-space reference distance model and the alpha-beta-gamma (ABG) model. Path loss exponents (PLEs) are 1.50–1.74 in line-of-sight (LOS) scenarios and 2.18–2.20 in non-line-of-sight (NLOS) scenarios. Results show that CI model with the reference distance of 1 m provides more accuracy and stability in tunnel scenarios. The RMS delay spread values vary between 2.77 ns and 18.76 ns. Specially, the Poisson distribution best fits the measured data of RMS delay spreads for LOS scenarios and the Gaussian distribution best fits the measured data of RMS delay spreads for NLOS scenarios. Moreover, the normal distribution provides good fits to the Ricean K-factor. The analysis of the abovementioned results from channel measurements and simulations may be utilized for the design of wireless communications of future 5G radio systems at 6 GHz.

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