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Autonomous driving (auto-driving) has been becoming a killer technology for next generation vehicles, whereas some fatal accidents grow concerns about its safety. A fundamental function for safer auto-driving is to recognize the vehicles locations, termed vehicular positioning. The state-of-the-art vehicular positioning is to rely on anchors that are stationary objects whose locations are known, i.e. satellites for GPS and base stations for cellular positioning. It is important for reliable positioning to install anchors densely, helping find enough anchors nearby. For the deployment to be cost-effective, there are some trials to use backscatter tags as alternative anchors by deploying them on a road surface, but its gain is limited by several reasons such as short contact time and difficulties in maintenance. Instead, we propose a new backscatter-tag assisted vehicular positioning system where tags are deployed along a roadside, which enables the extension of contact duration and facilitates the maintenance. On the other hand, there is a location mismatch between the vehicle and the tag, calling for developing a new backscatter transmission to estimate their relative position. To this end, we design a novel waveform called joint frequency-and-phase modulation (JFPM) for backscatter-tag assisted vehicular positioning where a transmit frequency is modulated for the distance estimation assuming that the relevant signal is clearly differentiable from the others while the phase modulation helps the differentiation. The JFPM waveform leads to exploiting the maximum Degree-of-Freedoms (DoFs) of backscatter channel in which multiple-access and broadcasting channels coexist, leading to more accurate positioning verified by extensive simulations.
Vehicle-to-Everything (V2X) will create many new opportunities in the area of wireless communications, while its feasibility on enabling vehicular positioning has not been explored yet. Vehicular positioning is a crucial operation for autonomous driv
Bistatic backscatter communication (BackCom) allows passive tags to transmit over extended ranges, but at the cost of having carrier emitters either transmitting at high powers or being deployed very close to tags. In this paper, we examine how the p
Conventional beamforming is based on channel estimation, which can be computationally intensive and inaccurate when the antenna array is large. In this work, we study the outage probability of positioning-assisted beamforming systems. Closed-form out
Multi-point detection of the full-scale environment is an important issue in autonomous driving. The state-of-the-art positioning technologies (such as RADAR and LIDAR) are incapable of real-time detection without line-of-sight. To address this issue
We consider an ambient backscatter communication (AmBC) system aided by an intelligent reflecting surface (IRS). The optimization of the IRS to assist AmBC is extremely difficult when there is no prior channel knowledge, for which no design solutions