Impact of Microwave and mmWave Channel Models on 5G Systems Performance

Neil, Callum T.; Shafi, Mansoor; Smith, Peter J.; Dmochowski, Pawel A.; Zhang, Jianhua

doi:10.1109/tap.2017.2759958

Cited by 40 publications

(40 citation statements)

References 37 publications

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“…The M ×1 channel vector between the BS and the l th user is modeled by the generic clustered ray-based model [15], [17]…”

Section: A Channel Modelmentioning

confidence: 99%

“…However, the mathematical difficulties attached to such models have systematically obstructed the progress in the performance characterization of linear transceivers. Many papers therefore necessarily focus on numerical simulations [17]- [20]. Some analysis of ray-based models in regard to favorable propagation (FP) and channel hardening has appeared in [21]- [23].…”

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confidence: 99%

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Analytical Framework for Full-Dimensional Massive MIMO With Ray-Based Channels

Miller

Smith

Dmochowski

et al. 2019

IEEE J. Sel. Top. Signal Process.

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The performance of baseband beamforming in multiuser multiple-input multiple-output (MU-MIMO) systems has been extensively studied for simplified statistical channel models where no angular parameters are taken into account. In contrast, there is little performance analysis with ray-based models, which are more physically motivated, feature prominently in standardization and have been experimentally validated. Thus, unlike previous studies, we present a mathematical framework to analyze the performance of zero forcing (ZF) and minimum mean-squared error (MMSE) combining. Using a central result for averaging in the angular domain, we derive tight approximations for the uplink signal-to-noise ratio and signal-to-interference-and-noise ratio (SINR) for ZF and MMSE processing, respectively, and the resulting spectral efficiencies. The remarkably simple expressions offer the following insights into the effects of the propagation environment. We demonstrate an improvement in performance when moving from vertical uniform rectangular array (URA) to horizontal URA to uniform linear array (ULA) antenna configurations. There is also a corresponding increase in the robustness of the performance to propagation scenarios. We demonstrate that under specific conditions increasing the angular spread can decrease the SINR for a ULA-an unexpected behavior which we link to the effects of end-fire radiation. Furthermore, our results allow us to investigate the impact of different array configurations and system parameters on the rate of convergence to favorable propagation conditions. Finally, we evaluate the spatial correlation properties intrinsically present in ray-based models, and compare them to the commonly used simple exponential model which yields equal, fixed correlation characteristics for each user. Index Terms-Ergodic spectral efficiency, favorable propagation, linear processing, MU-MIMO, ray-based channel models. I. INTRODUCTION Performance analysis of linear transceiver techniques for conventional and massive multiuser multiple-input multipleoutput (MU-MIMO) systems is well advanced for simple statistical channel models [2]-[7]. Early work on independent, identically distributed Rayleigh fading channels has been extended to a wide range of more complex and realistic channel C. L. Miller and P. A. Dmochowski are with the School of Engineering and Computer Science,

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“…The M ×1 channel vector between the BS and the l th user is modeled by the generic clustered ray-based model [15], [17]…”

Section: A Channel Modelmentioning

confidence: 99%

mentioning

confidence: 99%

Analytical Framework for Full-Dimensional Massive MIMO With Ray-Based Channels

Miller

Smith

Dmochowski

et al. 2019

IEEE J. Sel. Top. Signal Process.

Self Cite

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“…To the best of our knowledge, SCMs and Nakagami-based models have not been compared for the evaluation of the performance of an end-to-end mmWave network. In [29], the authors compare different SCMs for mmWave cellular networks, but they only consider link level metrics for their evaluation. Similarly, [30] compares the different models available in the ns-3 mmWave module using as performance metric the Medium Access Control (MAC) layer throughput of a single user.…”

Section: Overview Of Mmwave Channel Modelsmentioning

confidence: 99%

Impact of Channel Models on the End-to-End Performance of Mmwave Cellular Networks

Polese

Zorzi

2018

2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

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Communication at mmWave frequencies is one of the major innovations of the fifth generation of cellular networks, because of the potential multi-gigabit data rate given by the large amounts of available bandwidth. The mmWave channel, however, makes reliable communications particularly challenging, given the harsh propagation environment and the sensitivity to blockage. Therefore, proper modeling of the mmWave channel is fundamental for accurate results in system simulations of mmWave cellular networks. Nonetheless, complex models, such as the 3GPP channel model for frequencies above 6 GHz, may introduce a significant overhead in terms of computational complexity. In this paper we investigate the trade offs related to the accuracy and the simplicity of the channel model in end-to-end network simulations, and the impact on the performance evaluation of transport protocols.

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“…Nowadays, with the convenience and flexibility of highspeed railway (HSR), more and more people prefer to take rail traffic for travel or for work. In order to meet these goals in regard to safety, convenience, and efficiency, the investigations about the fifth-generation (5G) wireless communication system have become a trend [1][2][3][4] in different railway scenes. At present, the first 5G smart railway station has been established at Shanghai Hongqiao Railway Station, which is expected to have the ability to guarantee the 5G network depth coverage in this year.…”

Section: Introductionmentioning

confidence: 99%

Channel Characteristics of High-Speed Railway Station Based on Ray-Tracing Simulation at 5G mmWave Band

Xiong

Miao

et al. 2019

International Journal of Antennas and Propagation

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In order to satisfy the increasing demand for the higher transmission capacity of "smart station", millimeter wave (mmWave) technology is expected to play a significant role in the high data rate communication system. Based on the ray-tracing simulation technology, this paper would study wireless channel characteristics of the three-dimensional (3D) model of high-speed railway station at the mmWave band. Key parameters such as path loss exponent, shadow fading factor, delay spread, Rician K-factor, angular spread, power angle spectrum, and spatial correlation are extracted and investigated. ese channel characteristics are of value for the selection of antenna arrays and even the design of future 5G communication networks in the railway environment.

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Impact of Microwave and mmWave Channel Models on 5G Systems Performance

Cited by 40 publications

References 37 publications

Analytical Framework for Full-Dimensional Massive MIMO With Ray-Based Channels

Analytical Framework for Full-Dimensional Massive MIMO With Ray-Based Channels

Impact of Channel Models on the End-to-End Performance of Mmwave Cellular Networks

Channel Characteristics of High-Speed Railway Station Based on Ray-Tracing Simulation at 5G mmWave Band

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