CDL-based Channel Model for 5G MIMO Systems in Remote Rural Areas

Pessoa, Alexandre M.; Sokal, Bruno; Silva, Carlos F. M. e; Maciel, Tarcísio F.; Almeida, André L. F. de; Sousa, Diego Aguiar; Silva, Yuri C. B.; Cavalcanti, Francisco R. P.

doi:10.1109/iswcs.2019.8877334

Cited by 7 publications

(8 citation statements)

References 12 publications

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“…Fig. 4 evaluates the Symbol Error Rate (SER) performance of this algorithm for the LOS and Non-Line-of-Sight (NLOS) long-range channel models from [39] as well as for an Additive White Gaussian Noise (AWGN) channel. It can be observed that the SER performance with channel estimation is very close to the performance with perfect channel state information (denoted as estimated and perfect, respectively).…”

Section: B Channel Estimationmentioning

confidence: 99%

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Enhanced Remote Areas Communications: The Missing Scenario for 5G and Beyond 5G Networks

Mendes

Moreno

Marquezini³

et al. 2020

IEEE Access

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Section: B Channel Estimationmentioning

confidence: 99%

“…Evaluation of IFPI channel estimation algorithm[38] performance for long-range channel models from[39] and AWGN channel. Numerical results are obtained assuming block fading and by simulating 10 4 random channel realizations while employing numerology 0 of the 5G-RANGE PHY (cf.…”

mentioning

confidence: 99%

Enhanced Remote Areas Communications: The Missing Scenario for 5G and Beyond 5G Networks

Mendes

Moreno

Marquezini³

et al. 2020

IEEE Access

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“…Based on the measurement results, a rural channel model has been developed including path loss and multi-path fading characteristics. The path loss model for 50 km cell radius was defined to be [26] PL…”

Section: System Modelmentioning

confidence: 99%

Energy Detection Based Spectrum Sensing for Rural Area Networks

Vartiainen¹,

Karvonen²,

Matinmikko-Blue³

et al. 2020

EAI Endorsed Transactions on Wireless Spectrum

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Remote and rural areas are a challenge to deploy cost-efficient connectivity solutions. 5G technology needs lower frequencies, which calls for spectrum sharing for local networks. Spectrum sensing could complement traditional database approach for spectrum sharing in these areas. This paper studies a windowing based (WIBA) blind spectrum sensing method and compares its performance to a localization algorithm based on double-thresholding (LAD). Both methods are based on energy detection and can be used in any band for detecting rather narrowband signals. Probabilities of detection and false alarm, relative mean square error, number of detected signals and detection distances were evaluated in multipath, multi-signal and rural area channel conditions. The simulation results show tha the WIBA method is suitable for 5G remote areas, due to its good detection performance in low signal-to-noise ratios (SNR) with low complexity. Results also show importance of the detection window selection.

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“…respectively. Note that tan −1 (•, •) and cos −1 (•) in (13) and (14), respectively, denote the arctangent function (which takes into account the sign of its input arguments) and the arccosine function.…”

Section: Channel Generation Proceduresmentioning

confidence: 99%

“…The results also include an analysis of the channel eigenvalues and the evaluation of the achievable data rate when the user equipment (UE) is in the cell-edge considering singleinput single-output (SISO) and MIMO (2 × 2 and 4 × 4) configurations. In fact, this work is an extension of [13], whereas the main differences are listed below:…”

Section: Introductionmentioning

confidence: 99%

A CDL-Based Channel Model With Dual-Polarized Antennas for 5G MIMO Systems in Rural Remote Areas

et al. 2020

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In the fifth-generation (5G) mobile networks, it is expected that users experience high throughputs with an ultra-low-latency network, while a massive number of devices are connected to the network. However, in remote rural areas, there is still a large number of people that do not have access to broadband Internet. To overcome this issue, a possible strategy is to exploit the excellent propagation conditions of very high frequency (VHF) and ultra-high frequency (UHF) bands by allowing secondary spectrum reuse in the TV white space (TVWS) channels. But for that, a reliable channel model is required to perform valid coverage and data rate prediction studies. In this paper, a channel model is proposed that takes into account large and small scale fading effects, as well as the particularities of such remote rural areas. The proposed model makes use of measurements along with the clustered delay line (CDL) profiles from 3rd Generation Partnership Project (3GPP). It is a simple model to implement and can be used to provide fast link and system-level simulations. Numerical and analytical results are provided to validate the proposed model and a data rate evaluation is carried out for single-input single-output (SISO) and multiple-input multiple-output (MIMO) configurations, as well as for single-polarized (SP) and dual-polarized (DP) antennas. INDEX TERMS Channel modeling, remote rural areas, CDL, MIMO and dual-polarized antennas.

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CDL-based Channel Model for 5G MIMO Systems in Remote Rural Areas

Cited by 7 publications

References 12 publications

Enhanced Remote Areas Communications: The Missing Scenario for 5G and Beyond 5G Networks

Enhanced Remote Areas Communications: The Missing Scenario for 5G and Beyond 5G Networks

Energy Detection Based Spectrum Sensing for Rural Area Networks

A CDL-Based Channel Model With Dual-Polarized Antennas for 5G MIMO Systems in Rural Remote Areas

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