Pilot Decontamination Using Asynchronous Fractional Pilot Scheduling in Massive MIMO Systems

Zahoor, Muhammad Irshad; Dou, Zheng; Shah, Syed Bilal Hussian; Khan, Imran Ullah; Ayub, Sikander; Gadekallu, Thippa Reddy

doi:10.3390/s20216213

Cited by 20 publications

(3 citation statements)

References 43 publications

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“…Meanwhile, the VAS and ODI scores were regarded as the primary evaluation tools; these subjective data offered “real world” insights into guiding and improving surgical techniques ( 15 , 16 ). Moreover, a series of reported model evaluation metrics indicate that the deep learning can provide satisfactory performance in distinguishing target patients, demonstrating good clinical application ( 17 , 18 ). A broad application prospect requires additional data science techniques to support, including supervised dimensionality reduction for big data ( 19 ), deep learning networks for diabetic retinopathy ( 20 ), and identification of malnourished patients ( 21 ).…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the Predictors for Unfavorable Clinical Outcomes of Degenerative Lumbar Spondylolisthesis After Lumbar Interbody Fusion Using Machine Learning

Dong

Zhu

Yang

et al. 2022

Front. Public Health

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BackgroundAn increasing number of geriatric patients are suffering from degenerative lumbar spondylolisthesis (DLS) and need a lumbar interbody fusion (LIF) operation to alleviate the symptoms. Our study was performed aiming to determine the predictors that contributed to unfavorable clinical efficacy among patients with DLS after LIF according to the support vector machine (SVM) algorithm.MethodsA total of 157 patients with single-segment DLS were recruited and performed LIF in our hospital from January 1, 2015 to October 1, 2020. Postoperative functional evaluation, including ODI and VAS were, performed, and endpoint events were defined as significant relief of symptom in the short term (2 weeks postoperatively) and long term (1 year postoperatively). General patient information and radiological data were selected and analyzed for statistical relationships with the endpoint events. The SVM method was used to establish the predictive model.ResultsAmong the 157 consecutive patients, a postoperative unfavorable clinical outcome was reported in 26 patients (16.6%) for a short-term cohort and nine patients (5.7%) for a long-term cohort. Based on univariate and multivariate regression analysis, increased disc height (DH), enlarged facet angle (FA), and raised lateral listhesis (LLS) grade were confirmed as the risk factors that hindered patients' short-term functional recovery. Furthermore, long-term functional recovery was significantly associated with DH alone. In combination with the SVM method, a prediction model with consistent and superior predictive performance was achieved with average and maximum areas under the receiver operating characteristic curve (AUC) of 0.88 and 0.96 in the short-term cohort, and 0.78 and 0.82 in the long-term cohort. The classification results of the discriminant analysis were demonstrated by the confusion matrix.ConclusionsThe proposed SVM model indicated that DH, FA, and LLS were statistically associated with a clinical outcome of DLS. These results may provide optimized clinical strategy for treatment of DLS.

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Section: Discussionmentioning

confidence: 99%

Evaluation of the Predictors for Unfavorable Clinical Outcomes of Degenerative Lumbar Spondylolisthesis After Lumbar Interbody Fusion Using Machine Learning

Dong

Zhu

Yang

et al. 2022

Front. Public Health

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“…Hence, the pilot contamination is avoided when there are no pilots. In [16,17], the authors modeled a multicell MIMO system with favorable propagation conditions for a multicell massive MIMO network for the 5G cellular networks. Tey analyzed the SE performance on the efect of pilot contamination and several base station antennas.…”

Section: Related Workmentioning

confidence: 99%

Spectral Efficiency Analysis for Uplink Multicell Massive MIMO Cellular Communication System under Fading Channels

Abebaw,

Shakya,

Gelmecha

et al. 2023

Journal of Electrical and Computer Engineering

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In multicell massive MIMO system, the maximum limit on area throughput can be achieved by improving spectral efficiency and cell density, as well as bandwidth. In order to evaluate the area throughput for such scenarios, the spectral efficiency (SE) that utilizes the linear zero forcing uplink combining scheme, can be modeled under the Rician fading channel and the BS in case of up-links, is responsible to estimate the channel. Different from existing work, the proposed model incorporates various estimators such as minimum mean square error (MMSE), element-wise minimum mean square error estimators under Rician fading. The multicell scenarios with uplink (UL) massive MIMO has been analyzed using the proposed model under different cases such as pilot reuse factor, coherence block length, different number of antennas, and different estimators. The simulation results and analysis are presented based on these parameters. It is found that the average summation of SE per cell can be improved by optimizing MMSE channel estimation using ZF UL combiner, installing multiple BS antennas, serving multiple number of UEs per cell, and using efficient pilot reuse factor. The MMSE and ZF uplink combining are found to be more suitable in improving SE as compared to MMSE-MR. For example, the uplink SE of MMSE channel estimator for pilot reuse factors, 1, 3, and 4, is calculated as 22.5 bit/s/Hz/cell, 22.3 bit/s/Hz/cell, and 21 bit/s/Hz/cell, respectively. The uplink SE for EW-MMSE channel estimator with pilot reuse factors, 1, 3, and 4, is calculated as 22.5 bit/s/Hz/cell, 22 bit/s/Hz/cell, and 22 bit/s/Hz/cell, respectively. For the uplink SE of LS channel estimators, it can be 17.9 bit/s/Hz/cell, 20.2 bit/s/Hz/cell, and 20 bit/s/Hz/cell with pilot reuse factors as f = 1, 3, and 4, respectively. So, for f = 3, the maximum calculated uplink SE for MMSE, EW-MMSE, and LS is 17.6 bit/s/Hz/cell, 17.8 bit/s/Hz/cell, and 13 bit/s/Hz/cell, respectively. It can be concluded that the improved performance is obtained by reducing the pilot contamination at a pilot reuse factor f = 3 with different values of SNR, coherence block length, number of UEs, and number of BS antennas. There is also trade-off between the pilot contamination mitigation and the larger SE. However, there is not much effect on coherence block as when it increases, then the SE increases as well.

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“…Besides simplifying the network architectures, SDN is also able to improve Quality-of-Service (QoS) of an industrial cyber-physical systems, typically robotic cyber-physical system using SDN-based routing mechanism [1] and network slicing purpose [2]. Further, SDN has the potential to ease the manageability of the Multiple-Input-Multiple-Output (MIMO) system as there are plenty of research has been carried out to focus on improving the performance of massive MIMO system, for example, pilot contamination [3].…”

Section: Introductionmentioning

confidence: 99%

Flow Management Mechanism in Software-Defined Network

Tan¹,

Chong²,

Anbar³

2022

Computers, Materials &Amp; Continua

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Software-defined networking (SDN) is a paradigm shift in modern networking. However, centralised controller architecture in SDN imposed flow setup overhead issue as the control plane handles all flows regardless of size and priority. Existing frameworks strictly reduce control plane overhead and it does not focus on rule placement of the flows itself. Furthermore, existing frameworks do not focus on managing elephant flows like RTSP. Thus, the proposed mechanism will use the flow statistics gathering method such as random packet sampling to determine elephant flow and microflow via a predefined threshold. This mechanism will ensure that the control plane works at an optimum workload because the controller only manages elephant flows via reactive routing and rule placement respectively. Reactive routing has reduced link bandwidth usage below the pre-defined threshold. Furthermore, rule placement has increased average throughput and total transfer to 238%. Meanwhile, the data plane switches will be able to forward microflows via multipath wildcard routing without invoking controller in greater responding time by 85 ms faster in two Transmission Control Protocol (TCP) traffic and achieved 11% and 12% higher total transfer size and throughput respectively. Hence, the controller's workload reduced significantly to 48% in two TCP traffic.

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Pilot Decontamination Using Asynchronous Fractional Pilot Scheduling in Massive MIMO Systems

Cited by 20 publications

References 43 publications

Evaluation of the Predictors for Unfavorable Clinical Outcomes of Degenerative Lumbar Spondylolisthesis After Lumbar Interbody Fusion Using Machine Learning

Evaluation of the Predictors for Unfavorable Clinical Outcomes of Degenerative Lumbar Spondylolisthesis After Lumbar Interbody Fusion Using Machine Learning

Spectral Efficiency Analysis for Uplink Multicell Massive MIMO Cellular Communication System under Fading Channels

Flow Management Mechanism in Software-Defined Network

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