Cell cluster-based dynamic TDD DL/UL reconfiguration in TD-LTE systems

Sun, Fanglei; Zhao, Yan

doi:10.1109/wcnc.2016.7565057

Cited by 10 publications

(6 citation statements)

References 5 publications

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“…Additionally, the number of UL and DL sub-frames can be configured to adapt to the changing traffic conditions. As [15] confirms that the D-TDD outperforms the static TDD from the aspect of reducing DL interference, a dynamic D-TDD network system deployed with the cellular network and co-existing mMTC is considered in this study like [16,17]. Under such a circumstance, how to design the flexible D-TDD frame structure to cater for the asymmetry UL/DL traffic from the cellular networks and mMTC network while mitigating the interference between them is the major challenge.…”

Section: Introductionmentioning

confidence: 93%

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Traffic‐aware resource allocation scheme for mMTC in dynamic TDD systems

2018

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Section: Introductionmentioning

confidence: 93%

“…Then, (17) becomes the problem of minimising the solution of Q j * under the condition of the convex constraint domain (17b).…”

Section: Mmtc Slots Resource Allocation Algorithmmentioning

confidence: 99%

Traffic‐aware resource allocation scheme for mMTC in dynamic TDD systems

2018

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“…Commonly used clustering methods include threshold method [16][17][18] and heuristic algorithm [19]. Without losing generality, we use a threshold method that based on link coupling loss [17].…”

Section: System Modelmentioning

confidence: 99%

Service- and interference-aware dynamic TDD design in 5G ultra-dense network scenario

Gao¹,

Binyong²,

Chuai³

2017

J Wireless Com Network

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The 5G wireless communication system supports varied applications, making the uplink/downlink traffic asymmetry more and more serious. Dynamic time division duplex (TDD) technique has become a key technology of 5G networks due to its flexibility to support asymmetric services. In this paper, we study dynamic TDD sub-frame reconfiguration algorithm based on shifting. Firstly, we define cell shifting priority considering both traffic and interference. Then, we perform cell shifting-based TDD sub-frame reconfiguration following cell shifting priority. Simulation results show that the proposed dynamic TDD algorithm can guarantee high data rate and low interference, thus effectively increases the network throughput.

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“…To reduce the inter-cell interference, cell clustering has been proposed as an effective approach [8]- [10]. With the cell clustering scheme, small cells in close proximity are classified into the same cluster, and adopt S-TDD in a per-cluster basis.…”

Section: Introductionmentioning

confidence: 99%

“…As such, SAPs within the same cluster synchronize their transmissions, and the SAP-to-SAP and MU-to-MU interference can be eliminated within the cluster. Although the benefit of cell-clustering scheme has been evaluated in heterogeneous network [8] or centralized radio access network (C-RAN) [9] via simulations, an analytical framework is essential to fully understand the performance of clustered D-TDD scheme, and capture the effect of key network parameters. However, the spatial randomness of node's geographical location and the resulting aggregated interference distribution within a given cluster, put rigorous challenges for the development of analytical framework [11].…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis for Multi-Antenna Small Cell Networks with Clustered Dynamic TDD

Sun

Yang

Wang

et al. 2020

Preprint

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Small cell networks with dynamic time-division duplex (D-TDD) have emerged as a potential solution to address the asymmetric traffic demands in 5G wireless networks. By allowing the dynamic adjustment of cell-specific UL/DL configuration, D-TDD flexibly allocates percentage of subframes to UL and DL transmissions to accommodate the traffic within each cell. However, the unaligned transmissions bring in extra interference which degrades the potential gain achieved by D-TDD. In this work, we propose an analytical framework to study the performance of multi-antenna small cell networks with clustered D-TDD, where cell clustering is employed to mitigate the interference from opposite transmission direction in neighboring cells. With tools from stochastic geometry, we derive explicit expressions and tractable tight upper bounds for success probability and network throughput. The proposed analytical framework allows to quantify the effect of key system parameters, such as UL/DL configuration, cluster size, antenna number, and SINR threshold. Our results show the superiority of the clustered D-TDD over the traditional D-TDD, and reveal the fact that there exists an optimal cluster size for DL performance, while UL performance always benefits from a larger cluster.

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Cell cluster-based dynamic TDD DL/UL reconfiguration in TD-LTE systems

Cited by 10 publications

References 5 publications

Traffic‐aware resource allocation scheme for mMTC in dynamic TDD systems

Traffic‐aware resource allocation scheme for mMTC in dynamic TDD systems

Service- and interference-aware dynamic TDD design in 5G ultra-dense network scenario

Performance Analysis for Multi-Antenna Small Cell Networks with Clustered Dynamic TDD

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