On the Analysis of Scheduling in Dynamic Duplex Multihop mmWave Cellular Systems

Juan García-Rois, Felipe Gómez-Cuba, Mustafa Riza Akdeniz, Francisco J. González-Castaño, Juan C. Burguillo, Sundeep Rangan, Beatriz Lorenzo

Research output: Contribution to journalArticlepeer-review


With the shortage of spectrum in conventional cellular frequencies, millimeter-wave (mmWave) bands are being widely considered for use in next-generation networks. Multihop relaying is likely to play a significant role in mmWave cellular systems for self backhauling, range extension and improved robustness from path diversity. However, designing scheduling policies for these systems is challenging due to the need to account for both adaptive directional transmissions and dynamic time-division duplexing schedules, which are key enabling features of mmWave systems. This paper considers the problem of joint scheduling and congestion control in a multihop mmWave network using a Network Utility Maximization (NUM) framework. Interference is modeled with an exact model and two auxiliar simplified models: actual interference (AI), with a graph-based calculation of the Signal to Interference plus Noise Ratio (SINR) depending on dynamic link activity and directivity, as well as upper and lower bounds computed from worst-case interference (WI) and interference free (IF) approximations. Throughput and utility optimal policies are derived for all interference models (AI, WI and IF) with both deterministic Maximum Weighted and randomized Pick and Compare scheduling algorithms, jointly with decentralized Dual Congestion Control. Results are evaluated with numerical simulations, using accurate mmWave channel and beamforming gain approximations based on measurement campaigns.

Original languageEnglish (US)
Article number7128403
Pages (from-to)6028-6042
Number of pages15
JournalIEEE Transactions on Wireless Communications
Issue number11
StatePublished - Nov 2015


  • 5G
  • beamforming
  • dynamic duplexing
  • millimeter-wave
  • scheduling
  • utility maximization

ASJC Scopus subject areas

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


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