Distributed Randomized -Clustering Based PCID Assignment for Ultra-Dense Femtocellular Networks

Pratap, Ajay; Singhal, Rishabh; Misra, Rajiv; Das, Sajal K.

doi:10.1109/tpds.2018.2800050

Cited by 17 publications

(7 citation statements)

References 36 publications

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“…Efficient operation of cellular networks, especially LAA/5G-NRU deployments, requires reliable mechanisms for network configuration and re-configuration with minimal human intervention. This served as the motivation for the paradigm of Self-Organizing Networks (SON), where seamless and uninterrupted service is provided to the end-user through small-cells capable of self-configuration [12].…”

Section: A Role Of Pci In Cell Selectionmentioning

confidence: 99%

“…Despite these provisions, two major PCI related problems are encountered, which are illustrated in Figure 3 Since, LTE-A/LAA has only 504 unique PCI values, strategic reuse and network planning is done for reliable identification of cells/eNBs. However, with increasing network density and deployment of low power cells, as shown in Figure 3(b), an LAA cell has to compete with other small cells and macro cells for a limited number of PCIs, leading to a higher frequency of PCI collisions and PCI confusions [12]. An important reason is that cells/eNBs of different operators belonging to different Public Land Mobile Network (PLMNN) may assign the same PCI to their respective eNBs [2], [18].…”

Section: B New Challenges In the Unlicensed Bandmentioning

confidence: 99%

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Identification and Analysis of a Unique Cell Selection Phenomenon in Public Unlicensed Cellular Networks Through Machine Learning

et al. 2022

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Cellular operators deploy 4G License Assisted Access (LAA) and 5G NR-U base stations in the unlicensed spectrum, to enhance the overall network capacity. This work highlights a unique Physical Cell Id (PCI) related phenomenon observed in the public LAA operator deployments. Notably, the licensed and unlicensed carriers of a device may have the same PCI or different PCIs. The phenomenon is triggered by the combined effect of unlicensed deployment architectures and cell selection mechanisms. Consequently, the phenomenon will intensify manifold in 5G NR-U whose public deployment will soon commence. Unfortunately, the impact of this phenomenon on coexistence network performance is unexplored. It is also desirable to accurately identify the PCI scenarios at the device for improved cell selection and network performance. However, the data imbalance makes the classification problem challenging. This work addresses these problems through the following approach. Operator data from three LAA cellular providers is gathered and analyzed using machine learning algorithms. The impact of the phenomenon on LTE, LAA, and Wi-Fi components is demonstrated in three steps: First, the variation in network performance prediction accuracy in the PCI scenarios is examined. Second, the efficacy of numerosity reduction techniques used in data-driven cell selection is evaluated in both PCI scenarios. The third step entails a comparison of operator data analysis with network measurements. On-site experiments are conducted at the same PCI and different PCI sites to study the differences in real-time network performance. A controlled LTE-WiFi coexistence environment is created and multiple traffic categories are considered. Finally, a class-weight-based solution is proposed for PCI scenario identification. F-score of 0.75 and AUC-ROC of 0.84 is achieved for LAA, with a minimalist feature-set of SINR and Throughput.

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Section: A Role Of Pci In Cell Selectionmentioning

confidence: 99%

Section: B New Challenges In the Unlicensed Bandmentioning

confidence: 99%

Identification and Analysis of a Unique Cell Selection Phenomenon in Public Unlicensed Cellular Networks Through Machine Learning

et al. 2022

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“…For LAA, we first sort the data by the Physical Cell ID (PCI). Since PCIs are often reused, we define a reuse threshold of 1 km, i.e., if we observe the same PCI at a distance greater than 1 km, we treat that as a different cell [15]. We take the geographic centroid of the GPS coordinates of all the data corresponding to an unique PCI and use this as the approximate location of the LAA BS with that PCI.…”

Section: ) Deployment Mapsmentioning

confidence: 99%

Measurement-based coexistence studies of LAA & Wi-Fi deployments in Chicago

Sathya¹,

Rochman²,

Ghosh³

2020

Preprint

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LTE-Licensed Assisted Access (LAA) networks are beginning to be deployed widely in major metropolitan areas in the US in the unlicensed 5 GHz bands, which have existing dense deployments of Wi-Fi as well. Various aspects of the coexistence scenarios such deployments give rise to have been considered in a vast body of academic and industry research. However, there is very little data and research on how these coexisting networks will behave in practice. The question of "fair coexistence" between Wi-Fi and LAA has moved from a theoretical question to reality. The recent roll-out of LAA deployments provides an opportunity to collect data on the operation of these networks as well as studying coexistence issues on the ground. In this paper we describe the first results of a measurement campaign conducted over many months, using custom apps as well as off-the-shelf tools, in several areas of Chicago where the major carriers have been expanding LAA deployments. The measurements reveal that coexistence between LAA and Wi-Fi in dense, urban environments where both systems aggregate multiple channels, continues to be a challenging problem that requires further research.

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“…The results demonstrate significant improvement in system utility compared to existing methods. Another interesting method that demonstrated promising results with various type of access modes is the Fraction Frequency Reuse (FFR) [25], [26]. A cell sizing based energy optimization method has been proposed for Macro-Femto networks in open access mode by [27].…”

Section: Related Workmentioning

confidence: 99%

User Association, Power Control and Channel Access Schemes for Two-Tier Macro-Femto Networks: CDF of SINR Analysis

Ghosh

Gupta

Hacı

et al. 2020

IETE Technical Review

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In the rapid development of wireless communications Femtocells provide tremendous improvement in coverage and quality of service for users. Macro-Femto based networks are envisioned to be the de-facto solution for providing ultrahigh speed communications in next generation mobile wireless networks. This paper studies two-tier Macro-Femto networks and proposes a collection of novel technologies to address the interference problems. First, a novel user association scheme is proposed that aims to optimize the load among Femto base stations (FBSs). Second, a near-optimal ergodic search algorithm is proposed to regulate the power consumption at Macro base stations (MBSs) and improve energy efficiency. Third, a channel access mechanism is proposed for FBSs that aims to minimize inter-tier interference. For the proposed system, CDF of SINR is derived and used for performance investigation. Simulation results show that the proposed system can significantly outperform a popular, conventional cognitive radio based system for all the considered simulation scenarios.

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Distributed Randomized -Clustering Based PCID Assignment for Ultra-Dense Femtocellular Networks

Cited by 17 publications

References 36 publications

Identification and Analysis of a Unique Cell Selection Phenomenon in Public Unlicensed Cellular Networks Through Machine Learning

Identification and Analysis of a Unique Cell Selection Phenomenon in Public Unlicensed Cellular Networks Through Machine Learning

Measurement-based coexistence studies of LAA & Wi-Fi deployments in Chicago

User Association, Power Control and Channel Access Schemes for Two-Tier Macro-Femto Networks: CDF of SINR Analysis

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