Intensive Benchmarking of D2D communication over 5G cellular networks: prototype, integrated features, challenges, and main applications

Hussein, Hanan; El-Sayed, Hesham; El-Kader, Sherine M. Abd

doi:10.1007/s11276-019-02131-2

Cited by 37 publications

(22 citation statements)

References 73 publications

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“…The Performance of PAPR is measured either by the cumulative distribution function (CDF) or by the complementary CDF (CCDF). However, CCDF is more commonly used than the (CDF) [22]- [25]. CCDF is defined as the probability that PAPR exceeds some threshold value that is denoted by (PAPR0).…”

Section: Peak To Average Power Ratio Comparisonmentioning

confidence: 99%

A Modified Interference Approximation Scheme for Improving Preamble Based Channel Estimation Performance in FBMC System

Roshdy¹,

Aboul-Dahab²,

Fouad³

2020

IJCNC

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Filter bank multicarrier (FBMC) is considered a competitive waveform candidate for 5G that can replace orthogonal frequency division multiplexing (OFDM). However, channel estimation (CE) is a big challenge in FBMC because it suffers from intrinsic interference which is due to the orthogonality of the subcarrier functions in the real field only. In this paper, we investigate a proposed modified interference approximation scheme (M-IAM) by approximating the intrinsic interference from the neighbouring pilots to accommodate the complex channel frequency and thus improving CE performance besides simplifying its processing. The M-IAM scheme has a larger pseudo pilot magnitude than other conventional preamble schemes, namely the interference approximation method (IAM) with its versions (IAM-C) and (E-IAM-C); in addition to the novel preamble design (NPS). In addition, the proposed (M-IAM) scheme is characterized by the lower transmitted power needed. The CE performance of the M-IAM is investigated through 512 and 2048 subcarriers via different types of outdoor and indoor multipath fading channels that are timeinvariant such as IEEE 802.22, IEEE 802.11, Rician, and additive white Gaussian noise (AWGN), as well as time-varying channels such as Rayleigh and Vehicular A (Veh-A). Simulation results demonstrate that the proposed M-IAM scheme achieves a lower bit error rate (BER), lower normalized mean square error (NMSE) and lower peak-to-average power ratio (PAPR) over the conventional preamble schemes under the aforementioned channel models. The proposed scheme has the advantage of saving the transmitted power, a requirement that could match 5G low power requirements. KEYWORDSFilter bank multicarrier (FBMC), intrinsic interference, preamble based channel estimation methods

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Section: Peak To Average Power Ratio Comparisonmentioning

confidence: 99%

A Modified Interference Approximation Scheme for Improving Preamble Based Channel Estimation Performance in FBMC System

Roshdy¹,

Aboul-Dahab²,

Fouad³

2020

IJCNC

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“…With the rapid popularization of mobile computing, users have higher expectations and requirements for the speed and capacity of wireless networks, which has led to a sharp increase in the demand for spectrum resources from mobile terminals [1,2]. In response to the growing mobile service demands of the Internet and the Internet of Things (IoT), 5G mobile communication systems have proposed performance indicators that can support peak rates of up to tens of Gbps and large-scale connection densities of 1 million/km 2 [3][4][5][6][7]. Faced with the technical challenges of high traffic density and a large number of connections in 5G scenarios, the traditional weak cellular network at the base station side will face serious problems, such as low spectrum efficiency and base station overload [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Spark Spectrum Allocation for D2D Communication in Cellular Networks

Ahmad¹,

Khan²,

Irshad³

et al. 2022

Computers, Materials &Amp; Continua

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The device-to-device (D2D) technology performs explicit communication between the terminal and the base station (BS) terminal, so there is no need to transmit data through the BS system. The establishment of a short-distance D2D communication link can greatly reduce the burden on the BS server. At present, D2D is one of the key technologies in 5G technology and has been studied in depth. D2D communication reuses the resources of cellular users to improve system key parameters like utilization and throughput. However, repeated use of the spectrum and coexistence of cellular users can cause co-channel interference. Aiming at the interference problem under the constraint of fair resource allocation and improving the system throughput, this paper proposes an effective resource optimization scheme based on the firework method. The main idea is to expand the weighted sum rate and convert the allocated resource expression into fireworks to determine the correlation matrix. The simulation results show that, compared with the existing scheme, this scheme improves system performance by reducing interference.

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“…D2D communication is implemented as direct communication between devices in close proximity without any infrastructure. Because of such a characteristic of D2D communication, D2D techniques have been applied to many research areas such as public safety services, traffic offloading, multi-hop relaying, coverage extension, proximity-based services, vehicular networks, and internet-of-things services [1]- [5].…”

Section: Introductionmentioning

confidence: 99%

Deep Learning-Based Power Control Scheme With Partial Channel Information in Overlay Device-to-Device Communication Systems

Kim

Jung

2021

IEEE Access

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In the overlay device-to-device (D2D) communication systems, transmit power control is critical to better manage interference, so that the sum rate is maximized. Such power control for sumrate optimization is NP-hard, which is typically tackled by iterative algorithms such as weighted minimum mean square error (WMMSE) method. However, the iterative power control schemes inherently incur high complexity and excessive latency. To overcome the limitations, we propose a deep learning-based power control scheme with reduced complexity and latency, where partial and outdated channel state information (CSI) is considered. Using a deep neural network (DNN)-based approach, we formulate an optimization problem to maximize the spectral efficiency under the constraints of user fairness and energy efficiency, where the DNN-based method is based on unsupervised learning with no label data generation process. In addition, a CSI reporting method based on the channel-to-interference power ratio is proposed for partial CSI feedback, which considerably reduces the feedback overhead. Through simulations, we show the results of the spectral efficiency, energy efficiency, and fairness performance for various topographical sizes and channel correlation coefficients. Also, it is shown that the proposed scheme achieves better spectral efficiency and energy efficiency than the WMMSE scheme even when it uses a small amount of CSI feedback.INDEX TERMS Deep neural network, transmit power control, spectral efficiency, energy efficiency, index of fairness, partial channel state information.

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Intensive Benchmarking of D2D communication over 5G cellular networks: prototype, integrated features, challenges, and main applications

Cited by 37 publications

References 73 publications

A Modified Interference Approximation Scheme for Improving Preamble Based Channel Estimation Performance in FBMC System

A Modified Interference Approximation Scheme for Improving Preamble Based Channel Estimation Performance in FBMC System

Spark Spectrum Allocation for D2D Communication in Cellular Networks

Deep Learning-Based Power Control Scheme With Partial Channel Information in Overlay Device-to-Device Communication Systems

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