Performance analysis of dynamic adjustment of TDD uplink-downlink configurations in outdoor picocell LTE networks

Khoryaev, Alexey; Chervyakov, Andrey; Shilov, Mikhail; Panteleev, Sergey; Lomayev, Artyom

doi:10.1109/icumt.2012.6459791

Cited by 42 publications

(17 citation statements)

References 6 publications

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“…The cross interference consists of Base Station to Base Station (BS-BS) interference and DL User Equipment to User Equipment (UE-UE) interference. Among these two interferences the BS-BS interference is the main challenge that limits the application of cell-specific dynamic UL-DL reconfiguration [12]. Hence the main target of IMTA scheme would be the improvement of UL throughput performance.…”

Section: Dynamic Tdd System Model a Dynamic Ul/dl Configurationmentioning

confidence: 99%

Max K-CUT Based Clustering for Interference Mitigation and Traffic Adaptation in TDD Systems

Tao

Cui

Hong

et al. 2014

2014 IEEE 79th Vehicular Technology Conference (VTC Spring)

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Clustering is a promising interference mitigation scheme in dynamic TDD systems. However, most previous works just took large-scale path loss or coupling loss as criteria of the clustering schemes, thus the throughput performance would be limited by the varying traffic requirements among different small cells within one cluster. In this paper, a novel dynamic clusterbased Interference Mitigation and Traffic Adaptation (IMTA) scheme is proposed and evaluated with dense deployment of small cells (SCs). Firstly, a new clustering criterion named Differentiating Metric (DM) is defined. Based on the defined DM value, a DM matrix is formed and further presented by a clustering graph. In the clustering graph, the dynamic clustering strategy is mapped to a MAX K-CUT problem, which is addressed in polynomial time by a proposed heuristic clustering algorithm. Furthermore, the system level simulation results demonstrate a promising improvement on uplink traffic throughput (UTP) in our proposed scheme compared with traditional clustering schemes.

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Section: Dynamic Tdd System Model a Dynamic Ul/dl Configurationmentioning

confidence: 99%

Max K-CUT Based Clustering for Interference Mitigation and Traffic Adaptation in TDD Systems

Tao

Cui

Hong

et al. 2014

2014 IEEE 79th Vehicular Technology Conference (VTC Spring)

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“…There are also some works analyzing the performance of dynamic TDD in LTE networks [6], [7], [8] and other cellular systems [9]. Zhu and Lei [10] propose a centralized DL/UL reconfiguration mechanism using clustering, in which femto base stations that severely interfere with each other are grouped in the same cluster and choose the same configuration.…”

Section: Introductionmentioning

confidence: 99%

Distributed dynamic-TDD resource allocation in femtocell networks using evolutionary game

Chao

Lee

Wei

et al. 2015

2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

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Since uplink (UL) and downlink (DL) traffic loads are time-variant in femtocells, it is essential to adopt dynamic time-division duplexing (TDD) to effectively adjust the uplink and downlink transmission resources. However, the cross-link interference between dynamic TDD femtocells decreases the throughput gain of dynamic TDD. In this paper, we propose an evolutionary game-based distributed approach to choose the UL-DL configuration in order to minimize interference and maximize the system throughput in a large-scale femtocell network. A multiple populations evolutionary game is formulated to model femtocells with different traffic loads. We prove that the evolutionarily stable strategy (ESS) of the considered multiple populations evolutionary game is the optimal configuration which maximizes the system throughput. Simulation results confirm the effectiveness of the proposed evolutionary game-based approach for system throughput optimization in femtocells employing dynamic TDD.

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“…In [10], a dynamic TDD adjustment in outdoor LTE picocells was discussed. The results of this paper indicate that, in a TD-LTE network, dynamic subframe configuration provides major performance benefits.…”

Section: Overview Of Dynamic Td-ltementioning

confidence: 99%

Dynamic TDD in LTE small cells

Kerttula

Marttinen

Ruttik

et al. 2016

J Wireless Com Network

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Dynamic time-division duplexing (TDD) enables adjustments of uplink (UL) and downlink (DL) resources flexibly according to the instantaneous traffic load. Long-Term Evolution (LTE) systems can be implemented in TDD mode (TD-LTE). However, the dynamic change of a TDD configuration has not been well supported and investigated. In large macro cells, the high transmit power of base stations (BSs) easily blocks the weaker user equipment's (UE) UL signal (called the UL-DL interference); and therefore, neighboring cells usually operate with the same TDD configuration. In small cells, such as femtocells, the BS and UE transmission powers are in the same order and the system can afford to have overlapping UL-DL subframes. In addition, when DL load is light, the BS transmits empty DL subframes with only a reference signal (RS). In this paper, we measured the interference caused by DL RS. This interference is not negligible; and therefore, it is beneficial to reduce the amount of DL subframes by switching lightly loaded BSs to UL-heavy subframe configuration. We illustrate with simulations that this can improve system efficiency. Changing the subframe configuration dynamically has a switching-related cost. Frequent switching between subframe configurations can actually decrease throughput. We describe conditions where configuration change is beneficial. We also propose an algorithm that decreases the switching overhead and improves the ability to adapt to varying loads.

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Performance analysis of dynamic adjustment of TDD uplink-downlink configurations in outdoor picocell LTE networks

Cited by 42 publications

References 6 publications

Max K-CUT Based Clustering for Interference Mitigation and Traffic Adaptation in TDD Systems

Max K-CUT Based Clustering for Interference Mitigation and Traffic Adaptation in TDD Systems

Distributed dynamic-TDD resource allocation in femtocell networks using evolutionary game

Dynamic TDD in LTE small cells

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