Directional Cell Discovery in Millimeter Wave Cellular Networks

C. Nicolas Barati, S. Amir Hosseini, Sundeep Rangan, Pei Liu, Thanasis Korakis, Shivendra S. Panwar, Theodore S. Rappaport

Research output: Contribution to journalArticlepeer-review


The acute disparity between increasing bandwidth demand and available spectrum has brought millimeter wave (mmWave) bands to the forefront of candidate solutions for the next-generation cellular networks. Highly directional transmissions are essential for cellular communication in these frequencies to compensate for higher isotropic path loss. This reliance on directional beamforming, however, complicates initial cell search since mobiles and base stations must jointly search over a potentially large angular directional space to locate a suitable path to initiate communication. To address this problem, this paper proposes a directional cell discovery procedure where base stations periodically transmit synchronization signals, potentially in time-varying random directions, to scan the angular space. Detectors for these signals are derived based on a Generalized Likelihood Ratio Test (GLRT) under various signal and receiver assumptions. The detectors are then simulated under realistic design parameters and channels based on actual experimental measurements at 28 GHz in New York City. The study reveals two key findings: 1) digital beamforming can significantly outperform analog beamforming even when digital beamforming uses very low quantization to compensate for the additional power requirements and 2) omnidirectional transmissions of the synchronization signals from the base station generally outperform random directional scanning.

Original languageEnglish (US)
Article number7161389
Pages (from-to)6664-6678
Number of pages15
JournalIEEE Transactions on Wireless Communications
Issue number12
StatePublished - Dec 2015


  • cellular systems
  • directional cell discovery
  • millimeter wave radio

ASJC Scopus subject areas

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


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