On muting mobile terminals for uplink interference mitigation in HetNets—system-level analysis via stochastic geometry

Martín, Francisco Javier; Xi, Xiaojun; Renzo, Marco Di; Aguayo-Torres, Mari Carmen; Gómez, Gerardo

doi:10.1186/s13638-019-1400-x

Cited by 3 publications

(1 citation statement)

References 19 publications

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“…Authors of [12] propose joint optimization of resource allocation and cell association for hybrid HetNets during the uplink transmission by maximizing the total network capacity. Furthermore, an interference aware muting (IAM) scheme is demonstrated to mitigate multi-user interferences among uplink users [13], [14]. The IAM exploits the interference-awareness during the scheduling of the users' transmission.…”

Section: Introductionmentioning

confidence: 99%

Users First: A Robust Two-Level Learning of Power Control in Uplink Ultra-Dense HetNets

Makhanbet

2020

IEEE Access

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In this article, power control of uplink connection in the ultra-dense heterogeneous networks (HetNets), which are studied as different types of access points (APs), is investigated. It is demonstrated that an efficient performance of users during the uplink transmission is limited to the issue of per-user power control. Although the per-user power control allows users to transmit with full power to maintain a stable connection, it also causes a higher outage probability during the uplink transmission. In light of this, we propose a robust distributed energy-efficient scheme for uplink power control in HetNets, which confronts the per-user power control problem and coordination of the multi-user interferences. Therefore, firstly, Jarvic-Patric (JP) algorithm is adopted for the users' clustering. Unlike the traditional JP algorithm, conditions for the formation of users' clustering are extended with a term named the degree of membership in this article. Secondly, the distributed energy efficiency (EE) problem is formulated as the mean-metric of the EE, i.e., a sum of users' cooperative EE functions to address the cooperation problem among clustered interfering users at the local level and coordination of multi-user interferences at a global level. The formulation of the EE problem in this fashion reveals the interdependence of power optimization at local and global levels, which brings about the necessity of joint optimization. Hence, we propose a novel 2level distributed cooperative learning (DCL) scheme, where users act as self-organized agents and optimize power control at local and global levels jointly. In the 2-level DCL scheme, clustered users are engaged in the cooperative game of power control at the local level to maximize the cooperative EE. Meantime, users communicate with each other to learn an online power control at the global level. Besides, a popular performance metric for a machine learning scheme named regret is demonstrated for the 2-level DCL scheme. Finally, the numerical results demonstrate that the proposed scheme significantly improves the EE compared to existing works.

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Section: Introductionmentioning

confidence: 99%

Users First: A Robust Two-Level Learning of Power Control in Uplink Ultra-Dense HetNets

Makhanbet

2020

IEEE Access

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A Fully Distributed and Clustered Learning of Power Control in User-Centric Ultra-Dense HetNets

Makhanbet

Orynbet

et al. 2020

IEEE Trans. Veh. Technol.

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Treating Interference as Noise in Cellular Networks: A Stochastic Geometry Approach

Bacha

Renzo

Clerckx

2020

IEEE Trans. Wireless Commun.

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The interference management technique that treats interference as noise (TIN) is optimal when the interference is sufficiently low. Scheduling algorithms based on the TIN optimality condition have recently been proposed, e.g., for application to device-to-device communications. TIN, however, has never been applied to cellular networks. In this work, we propose a scheduling algorithm for application to cellular networks that is based on the TIN optimality condition. In the proposed scheduling algorithm, each base station (BS) first randomly selects a user equipment (UE) in its coverage region, and then checks the TIN optimality conditions. If the latter conditions are not fulfilled, the BS is turned off.In order to assess the performance of TIN applied to cellular networks, we introduce an analytical framework with the aid of stochastic geometry theory. We develop, in particular, tractable expressions of the signal-to-interference-and-noise ratio (SINR) coverage probability and average rate of cellular networks. In addition, we carry out asymptotic analysis to find the optimal system parameters that maximize the SINR coverage probability. By using the optimized system parameters, it is shown that TIN applied to cellular networks yields significant gains in terms of SINR coverage probability and average rate. Specifically, the numerical results show that average rate gains of the order of 21% over conventional scheduling algorithms are obtained. Index TermsTreating interference as noise (TIN), cellular networks, user scheduling, Poisson point processes, stochastic geometry, system level analysis.

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On muting mobile terminals for uplink interference mitigation in HetNets—system-level analysis via stochastic geometry

Cited by 3 publications

References 19 publications

Users First: A Robust Two-Level Learning of Power Control in Uplink Ultra-Dense HetNets

Users First: A Robust Two-Level Learning of Power Control in Uplink Ultra-Dense HetNets

A Fully Distributed and Clustered Learning of Power Control in User-Centric Ultra-Dense HetNets

Treating Interference as Noise in Cellular Networks: A Stochastic Geometry Approach

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