Abstract-As driving becomes more automated, vehicles are being equipped with more sensors generating even higher data rates. Radars (RAdio Detection and Ranging) are used for object detection, visual cameras as virtual mirrors, and LIDARs (LIght Detection and Ranging) for generating high resolution depth associated range maps, all to enhance the safety and efficiency of driving. Connected vehicles can use wireless communication to exchange sensor data, allowing them to enlarge their sensing range and improve automated driving functions. Unfortunately, conventional technologies, such as dedicated short-range communication (DSRC) and 4G cellular communication, do not support the gigabit-per-second data rates that would be required for raw sensor data exchange between vehicles. This paper makes the case that millimeter wave (mmWave) communication is the only viable approach for high bandwidth connected vehicles. The motivations and challenges associated with using mmWave for vehicle-tovehicle and vehicle-to-infrastructure applications are highlighted. A high-level solution to one key challenge -the overhead of mmWave beam training -is proposed. The critical feature of this solution is to leverage information derived from the sensors or DSRC as side information for the mmWave communication link configuration. Examples and simulation results show that the beam alignment overhead can be reduced by using position information obtained from DSRC.

As the result designed 16-element antenna array with corporate feed network, it has about 20% bandwidth and about 18 dBi gain. Designed antenna can be easily fabricated on LTCC substrate. ABSTRACT: This letter investigates design considerations and impact of technological parametric variations on microwave performance of gate electrode workfunction engineered recessed channel (GEWE-RC) MOSFET using ATLAS. Results reveal significantly enhanced microwave performance of GEWE-RC over bulk in terms of intrinsic delay, gains, cut-off frequency, S-parameters proving its effectiveness in radiofrequency-wireless, and RFID technology.

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Abstract-Increasing safety and automation in transportation systems has led to the proliferation of radar and IEEE 802.11p-based dedicated short range communication (DSRC) in vehicles. Current implementations of vehicular radar devices, however, are expensive, use a substantial amount of bandwidth, and are susceptible to multiple security risks. In this paper, we use the IEEE 802.11 orthogonal frequency division multiplexing (OFDM) communications waveform, as found in IEEE 802.11a/g/p, to perform radar functions. In this paper, we present an approach that determines the mean-normalized channel energy from frequency domain channel estimates and models it as a direct sinusoidal function of target range, enabling closest-target range estimation. In addition, we propose an alternative to vehicular forward collision detection by extending IEEE 802.11 dedicated short-range communications (DSRC) and WiFi technology to radar, extending the foundation of joint communications and radar frameworks. Furthermore, we perform an experimental demonstration near DSRC spectrum using IEEE 802.11 standard compliant sotware defined radios with potentially minimal modification through algorithm processing on frequency-domain channel estimates. The results of this paper show that our solution delivers sufficient accuracy and reliability for vehicular RADAR if we use the largest bandwidth available to IEEE 802.11p (20 MHz). This indicates significant potential for industrial devices with joint vehicular communications and radar capabilities.