On the Virtual Cell Transmission in Ultra Dense Networks

Zhu, Xiaoliang; Zeng, Jie; Su, Xin; Xiao, Chiyang; Wang, Jing; Huang, Lianfen

doi:10.3390/e18100374

Cited by 9 publications

(6 citation statements)

References 19 publications

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“…In (11), a, b, c, d, e, f represent the interference value respectively. In this example, a = Wab (1,2), which means the interference between user 1 and user 2 in Fig.2. It also means the element of the 1 st row and the 2 nd column of matrix (11).…”

Section: A Interference Weitht Designmentioning

confidence: 99%

“…It also means the element of the 1 st row and the 2 nd column of matrix (11). Similarly, b = Wab (1,3), c = Wab(1,4), d = Wab (2,3), e = Wab (2,4), f = Wab (3,4). The matrix is symmetric because we assume that the interference between users is undirected, which means Wab(i, j) = Wab(j, i).…”

Section: A Interference Weitht Designmentioning

confidence: 99%

“…Traditional spectrum management and cell division techniques have been unable to meet the increasing traffic demand. Ultra-Dense Network (UDN) [1] is considered to be a key technology to addresses the issues of indoor coverage and capacity in the nextgeneration of cellular networks [2], [3].…”

Section: Introductionmentioning

confidence: 99%

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An Efficiency-Improved Clustering Algorithm Based on KNN Under Ultra-Dense Network

et al. 2020

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Ultra-Dense Network (UDN) is one of the key techniques for the next generation of mobile network due to providing high system throughput. However, severe interference often occurs in UDN, which greatly impact the data rates of cell-edge users. User-centric wireless access virtualization has been widely adopted in UDN to mitigate the interference of cell-edge users by sharing resources and eliminating cell boundary. However, it's only effective for moderate scale networks. Moreover, the efficiency needs further improvement. In this paper, we study effective cooperative clustering method for large scale UDN with less computations in order to improve the throughput of cell-edge users. We formulate a convex optimization problem in which the objective is to maximize the system throughput with overlapping virtual cells. We propose a clustering method to solve this optimization problem. We design a fast-convergent iterative algorithm called K-Nearest Neighbor (KNN) algorithm to perform users clustering. Simulation results show that our proposed algorithm has better throughput performance for both average and cell-edge users. Especially, the per-carrier throughput is improved, which leads to more serviceable users with limited resources. INDEX TERMS Ultra-dense networks, virtual cell, interference mitigation, green communications, clustering.

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Section: A Interference Weitht Designmentioning

confidence: 99%

Section: A Interference Weitht Designmentioning

confidence: 99%

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An Efficiency-Improved Clustering Algorithm Based on KNN Under Ultra-Dense Network

et al. 2020

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“…In a wireless urban area network, most users fall victim to excessive interference by nearby devices and suffer scattering issues. This phenomenon is due to the high user density, numerous buildings, and unpredictable obstacles [23], [24]. Therefore, users who are located on a cell edge experience weaker signals than the minimum desired signal level that is required for seamless connectivity [12].…”

Section: Introductionmentioning

confidence: 99%

A Stochastically Geometrical Poisson Point Process Approach for the Future 5G D2D Enabled Cooperative Cellular Network

et al. 2019

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Due to recent developments in the cellular communication system, stochastic process implementation is necessary. The cellular communication system exhibits random patterns in various domains, thereby compelling the utilization of stochastic processes to achieve an optimal output. User behaviors with respect to the variable geographical pattern, population density, architecture, data usage, and mobility over various cells are random in nature. Therefore, the stochastic-geometry-based Poisson point process (PPP) technique can be implemented to accurately analyze these random processes in device-to-device (D2D)based cooperative cellular networks. The stochastic modeling entails the consideration of transmitters and receivers as the elements of stochastic point processes. The hexagonal method is not applicable for the implementation of heterogeneous network topologies, as it is not suitable for topologies, in which the cell size is not fixed. Therefore, a randomly designed heterogeneous network uses stochastic geometry as a viable solution for predicting the probabilistic parameters, including the cell interference, load distribution, coverage probability, base station (BS) mapping, and signal-to-interference-plus-noise ratio (SINR). Moreover, as a network architecture that is based on relay nodes (RNs), cellular and D2D users can be utilized in the domain of homogeneous random models. The associated phenomenon can be considered independent and Poisson. In this paper, the stochastic-geometric-based PPP approach is introduced for modeling the SINR, success probability, ergodic capacity, and outage probability for the D2D-enabled cooperative cellular network. The proposed PPP realistic model utilizes BS, RN, the cellular user (CU), and D2D user positioning method to design an interference-free network. The success probability, ergodic capacity, and outage probability for cellular and D2D users are used as metrics for evaluating the results with respect to various SINR threshold values and node densities. Moreover, the total success probability, ergodic capacity, and outage probability have been calculated for various multiple-input-multiple-output (MIMO) antenna configurations to validate the results. The results confirmed that the proposed PPP model approach outperforms the grid model and conventional multi-antenna ultra-dense network (UDN) approaches. INDEX TERMS 5G, stochastic geometry, interference cancellation, multi-hop communication, Poisson point process (PPP), D2D enabled cellular network.

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“…9 In a wireless urban area network, where a number of users are high in a small geographic area, most users fall victims of high interference by nearby devices and suffer more from scattering issues; this is because of a large number of obstacles and buildings present in the area. 10,11 Furthermore, in the communication between base station (BS) and user equipment (UE) located at the edge of the cell, the received signal at the end is weak enough as compared to the minimum desired signal level required for communication. 12,13 In this situation, deploying a small BS within the cell to boost the signal strength for the celledge users is not considered as a viable solution.…”

Section: Introductionmentioning

confidence: 99%

Interference cancelation for high-density fifth-generation relaying network using stochastic geometrical approach

Hindia

Qamar

Abbas

et al. 2019

International Journal of Distributed Sensor Networks

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In order to resolve the issue of coverage limitation for the future fifth-generation network, deploying a relay node within a cell is one of the most capable and cost-effective solution, which not only enhances the coverage but also improves the spectral efficiency. However, this solution leads to the undesired interferences from nearby base station and relay nodes that affects user’s signal-to-interference-plus-noise ratio and can cause the ambiguous received signal at the user end. In this article, we have analyzed a relay-based interference-limited network at millimeter wave frequency and proposed a Poisson point process–based model using a stochastic geometrical approach. The results for the proposed Poisson point process model have been evaluated in terms of success probability, network ergodic capacity, and outage probability, compared with the ideal grid model and conventional multiple-antenna ultra-dense network model. The results proved that the success probability and ergodic capacity for the proposed model are 3.5% and 2.3% higher as compared to the most commonly used model for the high-density network, respectively. Furthermore, the results have been analyzed at different multiple-input-multiple-output antenna configuration, which validates the model in the improvement of overall network performance even for higher number of antennas.

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On the Virtual Cell Transmission in Ultra Dense Networks

Cited by 9 publications

References 19 publications

An Efficiency-Improved Clustering Algorithm Based on KNN Under Ultra-Dense Network

An Efficiency-Improved Clustering Algorithm Based on KNN Under Ultra-Dense Network

A Stochastically Geometrical Poisson Point Process Approach for the Future 5G D2D Enabled Cooperative Cellular Network

Interference cancelation for high-density fifth-generation relaying network using stochastic geometrical approach

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