483 research outputs found

    Sub-6GHz Assisted MAC for Millimeter Wave Vehicular Communications

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    Sub-6GHz vehicular communications (using DSRC, ITS-G5 or C-V2X) have been developed to support active safety applications. Future connected and automated driving applications can require larger bandwidth and higher data rates than currently supported by sub-6GHz V2X technologies. This has triggered the interest in developing mmWave vehicular communications. However, solutions are necessary to solve the challenges resulting from the use of high-frequency bands and the high mobility of vehicles. This paper contributes to this active research area by proposing a sub-6GHz assisted mmWave MAC that decouples the mmWave data and control planes. The proposal offloads mmWave MAC control functions (beam alignment, neighbor identification and scheduling) to a sub-6GHz V2X technology, and reserves the mmWave channel for the data plane. This approach improves the operation of the MAC as the control functions benefit from the longer range, and the broadcast and omnidirectional transmissions of sub-6GHz V2X technologies. This simulation study demonstrates that the proposed sub-6GHz assisted mmWave MAC reduces the control overhead and delay, and increases the spatial sharing compared to a mmWave-only configuration (IEEE 802.11ad tailored to vehicular networks). The proposed MAC is here evaluated for V2V communications using 802.11p for the control plane and 802.11ad for the data plane. However, the proposal is not restricted to these technologies, and can be adapted to other technologies such as C-V2X and 5G NR.Comment: 8 pages, 5 figure

    Robust Location-Aided Beam Alignment in Millimeter Wave Massive MIMO

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    Location-aided beam alignment has been proposed recently as a potential approach for fast link establishment in millimeter wave (mmWave) massive MIMO (mMIMO) communications. However, due to mobility and other imperfections in the estimation process, the spatial information obtained at the base station (BS) and the user (UE) is likely to be noisy, degrading beam alignment performance. In this paper, we introduce a robust beam alignment framework in order to exhibit resilience with respect to this problem. We first recast beam alignment as a decentralized coordination problem where BS and UE seek coordination on the basis of correlated yet individual position information. We formulate the optimum beam alignment solution as the solution of a Bayesian team decision problem. We then propose a suite of algorithms to approach optimality with reduced complexity. The effectiveness of the robust beam alignment procedure, compared with classical designs, is then verified on simulation settings with varying location information accuracies.Comment: 24 pages, 7 figures. The short version of this paper has been accepted to IEEE Globecom 201

    Throughput and Robustness Guaranteed Beam Tracking for mmWave Wireless Networks

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    With the increasing demand of ultra-high-speed wireless communications and the existing low frequency band (e.g., sub-6GHz) becomes more and more crowded, millimeter-wave (mmWave) with large spectra available is considered as the most promising frequency band for future wireless communications. Since the mmWave suffers a serious path-loss, beamforming techniques shall be adopted to concentrate the transmit power and receive region on a narrow beam for achieving long distance communications. However, the mobility of users will bring frequent beam handoff, which will decrease the quality of experience (QoE). Therefore, efficient beam tracking mechanism should be carefully researched. However, the existing beam tracking mechanisms concentrate on system throughput maximization without considering beam handoff and link robustness. This paper proposes a throughput and robustness guaranteed beam tracking mechanism for mobile mmWave communication systems which takes account of both system throughput and handoff probability. Simulation results show that the proposed throughput and robustness guaranteed beam tracking mechanism can provide better performance than the other beam tracking mechanisms.Comment: Accepted by IEEE/CIC ICCC 201

    Machine Learning Solutions for Context Information-aware Beam Management in Millimeter Wave Communications

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