Millimeter Wave and Sub-Terahertz Spatial Statistical Channel Model for an Indoor Office Building

Ju, Shihao; Xing, Yunchou; Kanhere, Ojas; Rappaport, Theodore S.

doi:10.1109/jsac.2021.3071844

Cited by 153 publications

(156 citation statements)

References 43 publications

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“…In [12], the researchers proposed power distribution in the small cell to reduce path loss by specifying large power and controlling the distributed power to reduce the high cost and power consumption where millimetre wave hybrid beamforming exploits large bandwidth which reduces the large path loss in the Rayleigh fading channel. In [13], this paper, the researchers propose an intelligent downlink reflective surface (IRS) supported by non-orthogonal mm Wave multiple access (NOMA) and MIMO Massive antenna with lens antenna array where individual antenna users are grouped without direct correlation but are connected to the base station (BS) with the help of the IRS as a single NOMA group. The performance of the millimetre-wave beam area-weighted sum average supported by nonorthogonal multiple access (NOMA) was verified by simulations.…”

Section: Related Workmentioning

confidence: 99%

Comparative Performance of mmWave 5G System for many Beamforming Methods

Ahmed¹,

Ayoob²,

Janaby³

2022

Proceedings of 2nd International Multi-Disciplinary Conference Theme: Integrated Sciences and Technologies, IMDC-IST 2021, 7-9

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With the massive propagation of the mobile phone traffic and demand for high data rate transmission has grown this day, the current cellular spectrum for bands less than 3 GHz is severely deficient and cannot convoy these requirements, which requires the search for suitable solutions for the application of the fifth generation 5G. The potential of millimetre-wave (mm-wave) to provide a high data rate (Gigabits per second) has attracted great interest to become a broadband candidate for the fifth generation of cellular communications networks. To increase the spectral efficiency of cellular networks, Massive multi-input multi output (MMIMO) is considered one of the most promising methods, by equipping the base station with antenna arrays with hundreds or thousands of active elements with the use of beamforming technology and conducting coherent processing on both sides of the transmitter and receiver. In this paper, two mm-wave frequencies(28GHz and 73GHz) have been compared in terms of spectrum efficiency using a massive MIMO using two beamforming methods: conjugate beamforming (CB) and zero-forcing (ZF).

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Section: Related Workmentioning

confidence: 99%

Comparative Performance of mmWave 5G System for many Beamforming Methods

Ahmed¹,

Ayoob²,

Janaby³

2022

Proceedings of 2nd International Multi-Disciplinary Conference Theme: Integrated Sciences and Technologies, IMDC-IST 2021, 7-9

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“…For indoor environment, the propagation models are grouped into stochastic, empirical or site specific models. Empirical models are derived from certain propagation parameters such as the operating frequency, the distance between the transmitter (Tx) and receiver (Rx), and the height of the antenna [8]. These variables are assumed to follow the regular experimental data from measurement campaigns.…”

Section: Introductionmentioning

confidence: 99%

Adaptive 3D ray tracing approach for indoor radio signal prediction at 3.5 GHz

Kamaruddin

Geok

Aziz

et al. 2022

IJECE

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This paper explained an adaptive ray tracing technique in modelling indoor radio wave propagation. As compared with conventional ray tracing approach, the presented ray tracing approach offers an optimized method to trace the travelling radio signal by introducing flexibility and adaptive features in ray launching algorithm in modelling the radio wave for indoor scenarios. The simulation result was compared with measurements data for verification. By analyzing the results, the proposed adaptive technique showed a better improvement in simulation time, power level and coverage in modelling the radio wave propagation for indoor scenario and may benefit in the development of signal propagation simulators for future technologies.

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“…For this purpose, the Monte Carlo approachbased NYUSIM simulator (NYUSIM v3.0) was utilized to apply MIMO-Orthogonal Frequency-Division Multiplexing (OFDM) and massive MIMO technologies and generate Channel Impulse Responses (CIRs) from both omnidirectional and directional channel models at 73GHz [8][9][10]. This simulator can be also used in the THz band [11].…”

Section: Introduction Massive Multiple Input Multiple Output (Mimo) Andmentioning

confidence: 99%

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

Shamsan

2021

Eng. Technol. Appl. Sci. Res.

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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.

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Millimeter Wave and Sub-Terahertz Spatial Statistical Channel Model for an Indoor Office Building

Cited by 153 publications

References 43 publications

Comparative Performance of mmWave 5G System for many Beamforming Methods

Comparative Performance of mmWave 5G System for many Beamforming Methods

Adaptive 3D ray tracing approach for indoor radio signal prediction at 3.5 GHz

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

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