Analysis of Packet Throughput in Small Cell Networks under Clustered Dynamic TDD

Jiamin Li, Aiping Huang, Hangguan Shan, Howard H. Yang, Tony Q.S. Quek

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)


Small cell networks under dynamic time-division duplex (D-TDD) transmission have emerged as a promising solution to accommodate the varied uplink (UL) and downlink (DL) traffic in next generation cellular mobile communication networks. By allowing each cell to individually configure its communication direction, D-TDD allocates resources to accommodate whichever transmission direction needs it most. However, with unaligned transmissions, the interference increases and limits the performance of mean packet throughput (MPT). In this paper, we study the small cell networks under D-TDD with cell clustering being the interference mitigation technique (clustered D-TDD). By leveraging stochastic geometry and queuing theory, we develop an analytical framework that captures both spatial and temporal randomness. We study the MPT whose analytical expression is verified via simulation, and based on the analysis, we explore the impact from different network and service parameters. In particular, numerical results show that there is an optimal cluster size for DL MPT, while UL MPT always benefits from increasing cluster size. By grouping cells into clusters, the clustered D-TDD can provide the flexible service compared with static time-division duplex (S-TDD), and provide significant improvement over a traditional D-TDD in terms of UL MPT at a small cost of DL MPT.

Original languageEnglish
Article number8399860
Pages (from-to)5729-5742
Number of pages14
JournalIEEE Transactions on Wireless Communications
Issue number9
Publication statusPublished - 2018 Sep

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics


Dive into the research topics of 'Analysis of Packet Throughput in Small Cell Networks under Clustered Dynamic TDD'. Together they form a unique fingerprint.

Cite this