Dual connectivity in LTE HetNets with split control- and user-plane

Zakrzewska, Anna; Liu, David; Kučera, Štěpán; Claußen, Holger

doi:10.1109/glocomw.2013.6825019

Cited by 73 publications

(41 citation statements)

References 7 publications

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“…Figure 3 illustrates the coordinated resources. The impacts of different TTT setting to HF rates and PP rates are evaluated in [9,15,16]. Chuan M et al [17] investigated the inter-tier HO among a three-tier HetNet of macro cells, relays and picocells.…”

Section: Handover Processmentioning

confidence: 99%

Survey on Algorithms and Strategies for Mobility Enhancement under Heterogeneous Network (HetNet) Deployment Circumstances

Yu¹

2016

IJFGCN

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Section: Handover Processmentioning

confidence: 99%

Survey on Algorithms and Strategies for Mobility Enhancement under Heterogeneous Network (HetNet) Deployment Circumstances

Yu¹

2016

IJFGCN

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“…The basic concept of DC is introduced in [8,9]. The issues regarding the pairing of base stations and the grouping of mobile UEs are examined in [10].…”

Section: Introductionmentioning

confidence: 99%

Dual connectivity for LTE-advanced heterogeneous networks

Wang

Rosa²,

Pedersen

2015

Wireless Netw

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Dual connectivity (DC) allows user equipments (UEs) to receive data simultaneously from different eNodeBs (eNBs) in order to boost the performance in a heterogeneous network with dedicated carrier deployment. Yet, how to efficiently operate with DC opens a number of research questions. In this paper we focus on the case where a macro and a small cell eNBs are inter-connected with traditional backhaul links characterized by certain latency, assuming independent radio resource management (RRM) functionalities residing in each eNB. In order to fully harvest the gain provided by DC, an efficient flow control of data between the involved macro and small cell eNBs is proposed. Moreover, guidelines for the main performance determining RRM algorithms such as UE cell association and packet scheduling are also presented. It is demonstrated how proper configuration of the proposed flow control algorithm offers efficient trade-offs between reducing the probability that one of the eNBs involved in the DC runs out of data and limiting the buffering time. Simulation results show that the performance of DC over traditional backhaul connections is close to that achievable with inter-site carrier aggregation (CA) and virtually zerolatency fronthaul connections, and in any case it is significantly higher compared to the case without DC.

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“…The control plane handles UE connectivity as well as different radio-specific functions, which primarily cover: 1) RRC connection management, 2) system information broadcast and synchronization, 3) configuration and measurement reporting, and 4) cell handover and network controlled mobility. In contrast, the data plane handles UE specific data, and its functionalities are unicast and synchronization [23], [24]. Consequently, UEs requiring high data rate transmission are connected to both the control and data BSs, while low rate UEs are connected to just the control BS.…”

Section: System Architecture a Split Architecturementioning

confidence: 99%

“…We consider the new paradigm of HetNets architecture where the data and control/signaling planes are decoupled at the air interface, as recently proposed in [20]- [24]. The control plane provides ubiquitous network access and is made up of macro base station (BS)s, which we refer to as control BSs.…”

Section: System Architecture a Split Architecturementioning

confidence: 99%

“…In such architecture, the control and data planes are separated and are not necessarily handled by the same node. Consequently, this gives the network operator more flexibility, since the small/data cells can be activated on demand to deliver UE-specific data only when and where needed, while the macro/control cells manage UEs connectivity and mobility [24]. Thus, the separated plane architecture allows for improved mobility management performance, since the radio resource control (RRC) layers of the UEs and other control messaging, such as paging, will be handled by the control cells.…”

Section: Introductionmentioning

confidence: 99%

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A Cell Outage Management Framework for Dense Heterogeneous Networks

Onireti

Zoha

Moysen

et al. 2016

IEEE Trans. Veh. Technol.

106

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Abstract-In this paper, we present a novel cell outage management (COM) framework for heterogeneous networks (HetNets) with split control and data planes -a candidate architecture for meeting future capacity, quality of service and energy efficiency demands. In such architecture, the control and data functionalities are not necessarily handled by the same node. The control base stations (BSs) manage the transmission of control information and user equipment (UE) mobility, while the data BSs handle UE data. An implication of this split architecture is that, an outage to a BS in one plane has to be compensated by other BSs in the same plane. Our COM framework addresses this challenge by incorporating two distinct cell outage detection (COD) algorithms to cope with the idiosyncrasies of both the data and control planes. The COD algorithm for control cells leverages the relatively larger number of UEs in the control cell to gather large scale minimize drive testing (MDT) reports data, and detects outage by applying machine learning and anomaly detection techniques. To improve outage detection accuracy, we also investigate and compare the performance of two anomaly detecting algorithms, i.e. k− nearest neighbor and local outlier factor based anomaly detector, within the control COD. On the other hand, for data cells COD, we propose a heuristic grey-prediction based approach, which can work with the small number of UEs in the data cell, by exploiting the fact that the control BS manages UE-data BS connectivity, by receiving a periodic update of the received signal reference power (RSRP) statistic between the UEs and data BSs in its coverage. The detection accuracy of the heuristic data COD algorithm is further improved by exploiting the Fourier series of residual error that is inherent to grey prediction model. Our COM framework integrates these two COD algorithms with a cell outage compensation (COC) algorithm which can be applied to both planes. Our COC solution utilizes an actor critic (AC) based reinforcement learning (RL) algorithm, which optimizes the capacity and coverage of the identified outage zone in a plane, by adjusting the antenna gain and transmission power of the surrounding BSs in that plane. The simulation results show that the proposed framework can detect both data and control cell outage, and also compensate for the detected outage in a reliable manner.

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Dual connectivity in LTE HetNets with split control- and user-plane

Cited by 73 publications

References 7 publications

Survey on Algorithms and Strategies for Mobility Enhancement under Heterogeneous Network (HetNet) Deployment Circumstances

Survey on Algorithms and Strategies for Mobility Enhancement under Heterogeneous Network (HetNet) Deployment Circumstances

Dual connectivity for LTE-advanced heterogeneous networks

A Cell Outage Management Framework for Dense Heterogeneous Networks

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