Milimeter-wave links can provide GBit/s data rates but are highly susceptible to blockage. In case a direct line-of-sight communication path becomes blocked, communication via a reflected path may allow to maintain connectivity. A common approach is to switch to such an alternative path whenever the first path becomes blocked. However, this requires detecting the blockage and then reconfiguring the transceiver to use the new path which incurs latency. For traffic with strict latency or reliability requirements, or in highly dynamic environments where path switching would be frequent, using both paths concurrently can be more beneficial. In this paper, we consider using multiple paths and dividing the transmission power over those paths, instead of path switching. We propose an algorithm to allocate power among the different mmWave communication paths to overcome link blockage under randomly distributed obstacles. The power allocation algorithm is based on analysis of the blockage probabilities of the direct and reflected paths using geometric probability, to statistically maximize the overall capacity of the path between two nodes. We evaluate the performance of the proposed algorithm via simulation for various wireless environments.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Multi-Beam Power Allocation for mmWave Communications under Random Blockage


    Contributors:


    Publication date :

    2018-06-01


    Size :

    2034317 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Multi-beam power allocation for mmwave communications under random blockage

    Kwon, Sungoh / Widmer, Joerg | BASE | 2018

    Free access

    Contextual Multi-Armed Bandit based Beam Allocation in mmWave V2X Communication under Blockage

    Cassillas, Arturo Medina / Kose, Abdulkadir / Lee, Haeyoung et al. | IEEE | 2023


    Diffraction Characteristics Aided Blockage and Beam Prediction for mmWave Communications

    Li, Xiaogang / Yu, Li / Zhang, Yuxiang et al. | IEEE | 2022


    Deep Spatio-temporal Beam Training for mmWave Communications with Human Self-blockage

    Shan, Wenxing / Ma, Yiming / Wang, Zicun et al. | IEEE | 2023


    Markov Chain for Modeling 3D Blockage in mmWave V2I Communications

    Alsaleem, Fahd / Thompson, John S. / Laurenson, D. I. | IEEE | 2019