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

Makhanbet, Meruyert; Lv, Tiejun; Orynbet, Marat; Suleimenov, Batyrbek

doi:10.1109/tvt.2020.3013329

Cited by 10 publications

(3 citation statements)

References 42 publications

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“…In [72], an ultra-dense UAV network communication downlink power management model is suggested, which will optimize the EE by learning the best power control policy. A power management model is investigated in [73], this time focused on the power control of uplink connections in usercentric ultra-dense HetNets. A unique strategy for combining power control and user scheduling for optimizing energy efficiency in ultra-dense small cell networks in terms of bits per unit power is suggested in [74].…”

Section: Energy and Spectrum Efficiencymentioning

confidence: 99%

Ultra-Dense Networks: Taxonomy and Key Performance Indicators

et al. 2022

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One major influence on the future deployment of cellular networks will be a continuous increase in traffic inside mobile broadband systems. Moreover, traditional macrocell-based mobile communication networks will struggle to keep up with the enormous expansion in the demand for communications services in the future. Densification of networks is required if we are to meet the comprehensive needs for end terminals for a wide range of applications. One of the leading concepts in this competitive environment is the Ultra-Dense Network (UDN) where the access nodes and/or the communication links per unit area are densified, with the aim of improving overall network performance. The location of the UDN nodes meets the criteria for symmetry with a high probability. Ultra-dense cell deployment aims to reduce the physical distance between the transmitter and receiver in order to boost system performance and generally optimize the values of a wide variety of key performance indicators (KPIs). This paper aims to provide a taxonomy of UDNs and specifically of UDN-related KPIs. Initially, we address the complex questions “What is the current understanding of what ultra-dense networks are and what they should be, and how can we measure their performance?” by shedding light on the fundamental characteristics of UDNs.

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Section: Energy and Spectrum Efficiencymentioning

confidence: 99%

Ultra-Dense Networks: Taxonomy and Key Performance Indicators

et al. 2022

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“…The results presented in Reference 41 show that the proposed joint scheme of frequency allocation and convergent power control achieved better system data rates and improved user performance than the existing frequency allocation or power control schemes. In Reference 42, the authors have investigated uplink performance using fully distributed and clustered learning of power control in user‐centric ultra‐dense coupled' HetNets. They have used cooperative game of power allocation for users to address the problem of user power control and interference coordination among neighboring users in ultra‐dense HetNets.…”

Section: Introductionmentioning

confidence: 99%

Impact of fractional power control on downlink uplink decoupled‐based HetNets in varying path loss exponent environment

Ali

Aslam

Ahmed

2022

Trans Emerging Tel Tech

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Uplink power control in cellular networks have proved to be an effective technique for reducing uplink interference levels, resulting in improved uplink signal to interference and noise ratio, especially for cell-edge user equipments (UEs). Having said that, the impact of fractional power control (FPC) on the performance of downlink uplink decoupled-(DUDe) based HetNets while considering varying path loss exponent (PLE) environment has not been investigated as of yet, the reason behind which was to simplify the system model and obtain tractable results. In this article, we have developed a generalized analytical framework, incorporating the effect of FPC, in an effort to investigate its impact on DUDe performance in varying PLE environment. Furthermore, we have considered different small base station's (SBS) transmit powers to study its effect, paired with FPC, on DUDe-based HetNets. Moreover, we have performed a baseline comparison of DUDe performance against conventional coupled UE association based on maximum downlink received power. Performance indicators like decoupled and coupled uplink coverage probability and decoupled and coupled average spectral efficiency have been analyzed in this paper. The results presented in this paper highlight the impact of the FPC on DUDe performance in varying PLE environment.

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“…However, the NE cannot guarantee an efficient EE performance, since the obtained power control during the game can be unstable under the deviation of selfish users [24]. The non-cooperative game results in the inefficient power control during the uplink transmission since the users with strong channel gain are given priority [25]. Another issue revealed by the non-cooperative game is the per-user power control.…”

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

Cited by 10 publications

References 42 publications

Ultra-Dense Networks: Taxonomy and Key Performance Indicators

Ultra-Dense Networks: Taxonomy and Key Performance Indicators

Impact of fractional power control on downlink uplink decoupled‐based HetNets in varying path loss exponent environment

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

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