Optimal Relay Beamforming with Predictive Relay Selection for mmWave Communications in Urban Environments




    Millimeter wave (mmWave) communications supports high data rates with extremely high frequency, showing the promising potential in the future wireless communications including 5G networks. However, their sensitivity to blockage and severe signal attenuation present challenges in their deployment in urban settings. Current solutions to this dilemma are resource demanding and introduce network latency.


    Rutgers scientists have introduced a novel relay beamforming approach for mmWave communications in an urban scenario. The system model consists of static relays deployed in clusters across streets. It uses a novel, resource efficient scheme for joint optimal relay selection implemented in a predictive and distributed manner, and optimal distributed cooperative beamforming. This technique exploits the shadowing-induced correlation structure of the channel to predict the channel in time and space, thus reducing both latency and Channel State Information (CSI) overhead that is typically involved in relay selection. The simulations verified that the invention outperform any randomized selection policy, while, at the same time, achieves comparable performance to an ideal selection scheme that relies on perfect CSI estimates for all candidate relays. 



  • Optimal performance: Comparable to an ideal selection scheme relying on perfect CSI estimates
  • Increased communication range
  • Improved security: few hops with few relay points

Market Applications: 

Improved efficiency and security in the applications in the field of:

  • Vehicle to vehicle communications in a city, vehicle to infrastructure, vehicle to everything or communications within some industrial site.
  • Autonomous Driving.
  • Communications of mobile users in an urban environment.

Intellectual Property & Development Status: Patent Pending. Available for licensing and/or research collaboration.


Publications: Cooperative Beamforming with Predictive Relay Selection for Urban mmWave Communications.  Anastasios Dimas et al. 2019


Patent Information:
For Information, Contact:
Andrea Dick
Associate Director, Licensing
Rutgers University