A General 3-D Non-Stationary 5G Wireless Channel Model

Wu, Shaoen; Wang, Cheng-Xiang; Aggoune, El‐Hadi M.; Alwakeel, Mohammed M.; You, Xiaohu

doi:10.1109/tcomm.2017.2779128

Cited by 284 publications

(153 citation statements)

References 54 publications

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“…Massive multiple-input-multiple-output (MIMO) is an emerging technology for communication application which contributes a promising technology for the wireless sensor networks (WSNs) [1][2][3] and the fifth generation (5G) wireless communications [4]. In such systems, the base station (BS) was equipped with hundreds of antennas serving tens of single-antenna users in the same frequency band [5][6][7]. Benefit from the massive MIMO system is capable of achieving higher multiplexing and diversity gains compared with the conventional small-scale MIMO system [8,9].…”

Section: Introductionmentioning

confidence: 99%

An Improved Jacobi-Based Detector for Massive MIMO Systems

Zhao

Xing

et al. 2019

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Massive multiple-input-multiple-output (MIMO) is one of the key technologies in the fifth generation (5G) cellular communication systems. For uplink massive MIMO systems, the typical linear detection such as minimum mean square error (MMSE) presents a near-optimal performance. Due to the required direct matrix inverse, however, the MMSE detection algorithm becomes computationally very expensive, especially when the number of users is large. For achieving the high detection accuracy as well as reducing the computational complexity in massive MIMO systems, we propose an improved Jacobi iterative algorithm by accelerating the convergence rate in the signal detection process.Specifically, the steepest descent (SD) method is utilized to achieve an efficient searching direction. Then, the whole-correction method is applied to update the iterative process. As the result, the fast convergence and the low computationally complexity of the proposed Jacobi-based algorithm are obtained and proved. Simulation results also demonstrate that the proposed algorithm performs better than the conventional algorithms in terms of the bit error rate (BER) and achieves a near-optimal detection accuracy as the typical MMSE detector, but utilizing a small number of iterations.

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Section: Introductionmentioning

confidence: 99%

An Improved Jacobi-Based Detector for Massive MIMO Systems

Zhao

Xing

et al. 2019

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“…In the work of Chen et al, three popular technologies are amalgamated to deliver a promising performance, ie, nonorthogonal multiple access, spatial modulation, and massive MIMO, whereas the bit‐error‐rate performance of the proposed system in V2V communication scenarios is investigated. Similarly, Wu et al extended WINNER II and Saleh‐Valenzuela channel models to incorporate spatial‐temporal nonstationarity. A combination of ray tracing and spatial channel modeling approaches is presented in the work of Medbo et al, where the channel characteristics for integrated promising techniques of fifth‐generation communications are investigated (ie, together for massive MIMO, spherical wavefront, mmWave, 3D propagation, and dual‐end mobility).…”

Section: Introductionmentioning

confidence: 99%

“…The deployment of massive multiple-input-multiple-output (MIMO) systems in vehicular communications is a relatively new and highly significant topic of research. [4][5][6] Using large-scale multiple antennas at the communicating nodes has a significant scope in increasing the system performance through increased spatial diversity and/or spatial multiplexing. The large amount of available antennas at the vehicular nodes can help achieve the optimal antenna beam pattern through antenna and beam selection.…”

Section: Introductionmentioning

confidence: 99%

Second‐order fading statistics of massive‐MIMO vehicular radio communication channels

Waseer

Nawaz

Gulfam

et al. 2018

Trans Emerging Tel Tech

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This paper presents an intensive study on the fading statistics of massive multiple‐input–multiple‐output vehicular communication channels. A geometry‐based channel model is proposed, where both ends of the link are considered to be equipped with large‐scale three‐dimensional antenna arrays, whereas the scattering volumes in their vicinity are modeled as flexible (ie, shiftable, scalable, and rotatable) along all the dimensions to adapt various dynamic vehicle‐to‐everything radio propagation scenarios. Both ends of the link are modeled as flexible to be static or mobile in different directions and with independent velocities, to adapt both the vehicle‐to‐vehicle and vehicle‐to‐infrastructure scenarios. Joint and marginal three‐dimensional angle‐of‐arrival and angle‐of‐departure statistics of the channel are studied. The analysis is further extended from plain angle‐of‐arrival/angle‐of‐departure statistics to the characterization of dispersion of energy in the angular domain by using various notable angular spread quantifiers. A correlation between the received signals on two different antenna elements of the array, at two different time instants, on two distinct frequencies, and at two different spatial positions along the node mobility route is thoroughly investigated. This analysis is further extended to analytically study the Doppler spectrum characteristics and second‐order fading statistics of the channel. The considered second‐order fading statistics quantifiers are fading rate variance, level crossing rate, average fade duration, and coherence distance. The impact of various physical (eg, link distance, direction, and speed of node mobility), geometric (eg, shape and orientation of scattering volume), and antenna (eg, beam pattern, beam width, and beam switching) parameters on the angular spread, received signal correlations, Doppler spectrum characteristics, and second‐order fading statistics of the channel is thoroughly investigated. The conducted analysis is highly significant for devising efficient interference mitigation methods, error correction codes, modulation schemes, antenna beams, and receiver designs for emerging massive multiple‐input–multiple‐output vehicle‐to‐vehicle communication links, which, in turn, serves the purpose of efficient spectrum utilization.

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“…Recently, the deployment of massive multiple-input multiple-output (MIMO), a key enabling technology for the 5th generation (5G) of mobile communication systems, has been advocated for V2V communication systems [5,6]. Apart from providing advantages of spatial multiplexing and/or diversity, these large antenna arrays can help to achieve optimal thin beams, which in turn can increase the channel coherence time.…”

Section: Introductionmentioning

confidence: 99%

“…In this context, various channel models considering spherical wavefront and/or channel non-stationarity have been proposed in the literature, see e.g., [10][11][12][13]. In [6], the channel's spatio-temporal nonstationarity for WINNER II and Saleh-Valenzuela models is studied for their applicability in V2V communication scenarios. In [14], a thorough comparative study on the applicability of various existing models for massive-MIMO systems is conducted and the COST 2100, METIS, and IEEE 802.11ad models are suggested as suitable choices.…”

Section: Introductionmentioning

confidence: 99%

Angular Spread Quantification of Multi-Antenna Vehicular Radio Communication Channels

Ahmed

Nawaz

Gulfam

et al. 2018

2018 IEEE Globecom Workshops (GC Wkshps)

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The deployment of multi-antenna systems with software defined reconfigurable beam patterns can potentially benefit vehicle-to-vehicle (V2V) communications by increasing the channel coherence time. This in turn necessitates an accurate characterization and modeling of the angular statistics of vehicular radio propagation environments. This work proposes an improved three-dimensional (3-D) spatial description of vehicular propagation environments and derives the closed-form analytical expressions for the joint and marginal statistics of the 3-D angleof-arrival (AoA) and angle-of-departure (AoD). Then, based on the proposed geometric channel model, the AoA and AoD angular spreads are quantified in terms of the joint angular spread, elevational constriction, and the azimuthal constriction. These considered quantifiers are shown to be of high significance in quantification of angular spread in V2V radio propagation environments. The impact of various physical parameters on the angular spread is also investigated. These parameters include the link-distance, scattering volume, and the number of scatterers along the azimuth and elevation axes. The derived analytical expressions are also validated by simulations.

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A General 3-D Non-Stationary 5G Wireless Channel Model

Cited by 284 publications

References 54 publications

An Improved Jacobi-Based Detector for Massive MIMO Systems

An Improved Jacobi-Based Detector for Massive MIMO Systems

Second‐order fading statistics of massive‐MIMO vehicular radio communication channels

Angular Spread Quantification of Multi-Antenna Vehicular Radio Communication Channels

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