Pilot Decontamination over Time Frequency and Space Domains in Multi-Cell Massive MIMO System

Hachad, Lamiae; Mrabti, Fatiha; Ghennioui, Hicham; Zouak, M.

doi:10.11591/ijece.v8i5.pp3609-3619

Cited by 4 publications

(4 citation statements)

References 20 publications

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“…A fair pilot allocation method has proposed in [23] for the multi-cell mMIMO, to reduce the PC effect and increase the sum rate (SR) of system with assuring the services among the users. Min Leakage algorithm (MLA) that is a heuristic algorithm is proposed to resolve the problem of optimization with lower system complexity, while considering the MLA can only deliver a suboptimal performance.…”

Section: Literature Surveymentioning

confidence: 99%

“…Min Leakage algorithm (MLA) that is a heuristic algorithm is proposed to resolve the problem of optimization with lower system complexity, while considering the MLA can only deliver a suboptimal performance. Moreover, a greedy pilot allocation based User-Exchange approach is proposed to further improve the system SR and the services among users [23]. In [24], author considered the problem of resource allocation for the uplink mMIMO system, where the antennas at BS are priced and the virtualization has done across the service providers; though the mobile network provider (MNP) holds the complete infrastructure of antennas decides the price, also the Stackelberg game is considered for the maximization of net profit of MNP, whereas the minimum SR necessities of service providers are fulfilled.…”

Section: Literature Surveymentioning

confidence: 99%

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Network efficiency enhancement by reactive channel state based allocation scheme

Umesh

Swamy

2020

IJECE

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Now a day the large MIMO has considered as the efficient approach to improve the spectral and energy efficiency at WMN. However, the PC is a big issue that caused by reusing similar pilot sequence at cells, which also restrict the performance of massive MIMO network. Here, we give the alternative answer, where each of UEs required allotting a channel sequences before passing the payload data, so as to avoid the channel collision of inter-cell. Our proposed protocol will ready to determine the channel collisions in distributed and scalable process, however giving unique properties of the large MIMO channels. Here we have proposed a RCSA (Reactive channel state based allocation) scheme, which will very productively work with the RAP blockers at large network of MIMO. The position of time-frequency of RAP blocks is modified in the middle of the adjacent cells, because of this design decision the RAP defend from the hardest types of interference at inter-cell. Further, to validate the performance of our proposed scheme it will be compared with other existing technique.

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Section: Literature Surveymentioning

confidence: 99%

Section: Literature Surveymentioning

confidence: 99%

Network efficiency enhancement by reactive channel state based allocation scheme

Umesh

Swamy

2020

IJECE

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“…, N, which are unique to the specific emotional characteristics of that body. Therefore, the Analyzing of the micro-Doppler signatures for target detection, classification, and recognition is more accurate when analyzed by using the joint time-frequency to provide useful information for that target compatible with its movement with time [26].…”

Section: The Wall Effects; Loss and MDmentioning

confidence: 99%

Human Motion Detection through Wall Based on Micro-Doppler Using Kalman Filter Combined with Convolutional Neural Network

Saeed¹,

Abbas²,

Abed³

et al. 2019

IJIES

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Human motion detection, classification, and perceiving, the dynamics of moving objects in the environment, are crucial in many applications. Many sensors have been used to this detection; the radar represents one of the promising sensors. Kalman filter (KF) and convolutional neural network (CNN) represents a powerful tool for estimation and classification respectively. In this paper, a combination between the KF and CNN have been proposed to detect and classify human behavior. This proposal presents two important points, the precise features map from the combination of Kalman Filter and CNN, as well as the use of the radar, which is working under all circumstances and does not break the privacy. Twenty different experiments with three scenarios for different motion with and without glass wall have been studied, and they are classified. The results show that the overperform of the proposed algorithm and the classification accuracy can reach 98.7%. This advancement of the proposed algorithm depends on the efficient Wigner-Ville short time Fourier transform (STFT) which is used as a feature extractor and make Range-Doppler (RD) map.

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“…Analysis of the micro-Doppler signatures in the joint time-frequency domain can provide useful information for target detection, classification, and recognition [8], [26]. Therefore, the micro-Doppler signatures from the scene are calculated by applying a time-frequency transforms, such as the Short-Time Fourier Transform (STFT) with a Gaussian window, to the scattered fields.…”

Section: Wall Effectsmentioning

confidence: 99%

Through the Wall, Recognize Moving Targets Based on Micro-Doppler Signatures

Saeed

Al-Muifraje

Hatem

2018

IJECE

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Radar is a promising device for detection and recognition of invisible moving objects, Where, the micro-Doppler frequency shift caused by moving the object's parts have been represented as an attractive feature in the recognition process. In spite of that, no thorough analysis of human movement by bicycle and no discriminate from the running one through the wall in the literature. This paper presents a mathematical model of bicycle movement, then, the recognition of moving objects through the wall. Where three human movements; walking, running and on a bicycle have been recognized through two types of wall wood and cork. The theoretical analysis and measured was given a recognition 98.7% for human walking on his feet, 99% of the passenger on a bicycle, and 98% of the person running have been achieved without walls. While, a 95.4%, 96.2%, and 95% recognition have been gained from walking, moving by bicycle and running with wooden wall and 94%, 94.8%, and 93.3% respectively with cork wall. 2.4 GHz as a detector and SVM as classifier are used.

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Pilot Decontamination over Time Frequency and Space Domains in Multi-Cell Massive MIMO System

Cited by 4 publications

References 20 publications

Network efficiency enhancement by reactive channel state based allocation scheme

Network efficiency enhancement by reactive channel state based allocation scheme

Human Motion Detection through Wall Based on Micro-Doppler Using Kalman Filter Combined with Convolutional Neural Network

Through the Wall, Recognize Moving Targets Based on Micro-Doppler Signatures

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