An official website of the United States government
With significant commercial potentials, millimeter- wave (mmWave) based wireless local area networks (WLANs) have attracted intensive attention lately. Unfortunately, the susceptible transmission characteristics over mmWave bands, especially the vulnerability to blockages, poses significant design challenges. Although existing solutions, such as beamforming, can overcome some of the problems, they usually focus on enhancing end transceivers to adapt to the transmission environments, and sometimes are still less effective. In this paper, by deploying highly-reflective cheap metallic plates as tunable reflectors without damaging the aesthetic nature of the environments, we propose to augment WLAN transmission environments in a way to create more effective alternative indirect line-of-sight (LOS) links by adjusting the orientations of the reflectors. Based on this idea, we design a novel adaptive mechanism, called mmRef, to effectively tune the angels of the deployed reflectors and develop corresponding operational procedures. Our performance study demonstrates our proposed scheme could achieve significant gain by tuning the angles of deployed reflectors in the augmented transmission environment.
more »
« less
Learning-based mmWave V2I environment augmentation through tunable reflectors
To support the demand of multi-Gbps sensory data exchanges for enhancing (semi)-autonomous driving, millimeter-wave bands (mmWave) vehicular-to-infrastructure (V2I) communications have attracted intensive attention. Unfortunately, the vulnerability to blockages over mmWave bands poses significant design challenges, which can be hardly addressed by manipulating end transceivers, such as beamforming techniques. In this paper, we propose to enhance mmWave V2I communications by augmenting the transmission environments through reflection, where highly-reflective cheap metallic plates are deployed as tunable reflectors without damaging the aesthetic nature of the environments. In this way, alternative indirect line-of-sight (LOS) links are established by adjusting the angle of reflectors. Our fundamental challenge is to adapt the time-consuming reflector angle tuning to the highly dynamic vehicular environment. By using deep reinforcement learning, we propose the learning-based Fast Reflection (LFR) algorithm, which autonomously learns from the observable traffic pattern to select desirable reflector angles in advance for probably blocked vehicles in near future. Simulation results demonstrate our proposal could effectively augment mmWave V2I transmission environments with significant performance gain.
more »
« less
- Award ID(s):
- 1722791
- PAR ID:
- 10172946
- Date Published:
- Journal Name:
- IEEE Global Communications Conference
- ISSN:
- 2576-6813
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Autonomous vehicles are equipped with multiple high-resolution sensors and cameras for an accurate local view of their surroundings. Equally important, they will need to exchange such high data-rate among each other for a wider view of their environments. The use of high-bandwidth millimeter-wave (mmWave) spectrum bands in vehicular communications can satisfy such demand for high data-rate exchange. Before attempting to design any mmWave vehicular communication system, there is a need to fully understand the propagation characteristics of such mmWave mobile environment. In this paper, we leverage the ray tracing capabilities in the WinProp software suite and study the propagation characteristics of mmWave channels in vehicular communications. In doing so, we present the implementation of the Vehicle-to-Infrastructure (V2I) communication scenario in WinProp. Via simulation results, we are able to show that approximately 20 dB degradation of signal strength can happen within 5 seconds.more » « less
-
The integration of sub-6 GHz and millimeter wave (mmWave) bands has a great potential to enable both reliable coverage and high data rate in future vehicular networks. Nevertheless, during mmWave vehicle-to-infrastructure (V2I) handovers, the coverage blindness of directional beams makes it a significant challenge to discover target mmWave remote radio units (mmW-RRUs) whose active beams may radiate somewhere that handover vehicles are not in. Besides, fast and soft handovers are also urgently needed in vehicular networks. Based on these observations, to solve the target discovery problem, we utilize channel state information (CSI) of sub-6 GHz bands and Kernel-based machine learning (ML) algorithms to predict vehicles’ positions and then use them to pre-activate target mmW-RRUs. Considering that the regular movement of vehicles on almost linearly paved roads with finite corner turns will generate some regularity in handovers, to accelerate handovers, we propose to use historical handover data and K-nearest neighbor (KNN) ML algorithms to predict handover decisions without involving time-consuming target selection and beam training processes. To achieve soft handovers, we propose to employ vehicle-to-vehicle (V2V) connections to forward data for V2I links. Theoretical and simulation results are provided to validate the feasibility of the proposed schemes.more » « less
-
Abstract—Millimeter wave wireless spectrum deployments will allow vehicular communications to share high data rate vehicular sensor data in real-time.The highly directional nature of wireless links in millimeter spectral bands will require continuous channel measurements to ensure the transmitter (TX) and receiver (RX) beams are aligned to provide the best channel. Using real-world vehicular mmWave measurement data at 28GHz, we determine the optimal beam sweeping period, i.e. the frequency of the channel measurements,to align the RX beams to the best channel directions for maximizing the vehicle-to-infrastructure (V2I) throughput.We show that in a realistic vehicular traffic environment in Austin,TX, for a vehicle traveling at an average speed of 10.5mph,a beam sweeping period of 300 ms in future V2I communication standards would maximize theV2I throughput,using a system of four RX phased arrays that scanned the channel 360 degrees in the azimuth and 30 degrees above and below the boresight.We also investigate the impact of the number of active RX chains controlling the steerable phased arrays on V2I throughput. Reducing the number of RX chains controlling the phased arrays helps reduce the cost of the vehicular mmWave hardware while multiple RX chains, although more expensive,provide more robustness to beam direction changes at the vehicle,allowing near maximum throughput over a wide range of beam sweep periods.We show that the overhead of utilizing one RX chain instead of four leads to a10% drop in mean V2I throughput over six non-line- of-sight runs in real traffic conditions, with each run being 10 to 20 seconds long over a distance of 40 to 90 meters. Index Terms—mmWave;beam management;channel sound- ing; phased arrays;V2X;V2V;5G;sidelinkmore » « less
-
To accommodate increasingly intensive application bandwidth demands, mmWave WLAN at 60 GHz has been identified as a promising technology with the potential to achieve Gbps throughput. However, mmWave performance is highly dependent on the signal's line-of-sight (LoS) condition due to its high penetration loss when obstructed. We study the use of dedicated flat passive reflectors to improve coverage in indoor mmWave WLANs through a reflector placement scheme that accommodates any general indoor scenario with pre-deployed ceiling-mounted access points (APs). The reflector locations are efficiently selected among all available vertical surfaces within the indoor environment. Through simulations, we show that deployment of intelligently placed reflectors can improve LoS coverage by up to 10%, which is more than deploying one additional AP. Results are provided to illustrate how different factors affect coverage and insights about preferred reflector placements are provided.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/GLOBECOM38437.2019.9013979
