On an HARQ-based coordinated multi-point network using dynamic point selection

Makki, Behrooz; Eriksson, Thomas; Svensson, Tommy

doi:10.1186/1687-1499-2013-209

Cited by 5 publications

(1 citation statement)

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“…We take user i and user j as candidates in one cluster, and assume the composite channel vector as H i,C i (composite channel vector of user i in virtual cell C i ), and H j,C j (composite channel vector of user j in virtual cell C j ). The weight between user i in virtual cell C i and user j in virtual cell C j is noted as (12) where coefficients α and β denote the proportions of power and space in multi-dimensional cooperation respectively.…”

Section: A Interference Weitht Designmentioning

confidence: 99%

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%