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Millimeter-wave (mmWave) joint communication-radar (JCR) will enable high data rate communication and high-resolution radar sensing for applications such as autonomous driving. Prior JCR systems that are based on the mmWave communications hardware, however, suffer from a limited angular field-of-view and low estimation accuracy for radars due to the employed directional communication beam. In this paper, we propose an adaptive and fast combined waveform-beamforming design for the mmWave automotive JCR with a phased-array architecture that permits a trade-off between communication and radar performances. To rapidly estimate the mmWave automotive radar channel in the Doppler-angle domain with a wide field-of-view, our JCR design employs a few circulant shifts of the transmit beamformer and apply two-dimensional partial Fourier compressed sensing technique. We optimize these circulant shifts to achieve minimum coherence in compressed sensing. We evaluate the JCR performance trade-offs using a normalized mean square error (MSE) metric for radar estimation and a distortion MSE metric for data communication, which is analogous to the distortion metric in the rate distortion theory. Additionally, we develop a MSE-based weighted average optimization problem for the adaptive JCR combined waveform-beamforming design. Numerical results demonstrate that our proposed JCR design enables the estimation of short- and medium-range radar channels in the Doppler-angle domain with a low normalized MSE, at the expense of a small degradation in the communication distortion MSE., Comment: Submitted to the IEEE Journal on Selected Topics in Signal Processing. Copyright may be transferred without notice, after which this version may no longer be accessible

A fully-digital wideband joint communication-radar (JCR) with a multiple-input-multiple-output (MIMO) architecture at the millimeter-wave (mmWave) band will enable high joint communication and radar performance with enhanced design flexibility. A quantized receiver with few-bit analog-to-digital converters (ADCs) will enable a practical JCR solution with reduced power consumption for futuristic portable devices and autonomous vehicles. In this paper, we present a joint communication-radar proof-of-concept platform, named JCR70, to evaluate and demonstrate the performance of these JCR systems using real channel measurements in the 71-76 GHz band. We develop this platform by extending a mmWave communication set-up with an additional full-duplex radar receiver and by capturing the MIMO JCR channel using a moving antenna on a sliding rail. To characterize the JCR performance of our developed tested, we conduct several indoor and outdoor experiments and apply traditional as well as advanced processing algorithms on the measured data. Additionally, we compare the performance of our JCR70 platform with the INRAS Radarbook, which is a state-of-the-art automotive radar evaluation platform at 77 GHz. The results demonstrate that a quantized receiver with 2-4 bit ADCs generally performed quite close to the high-resolution ADC for a signal-to-noise ratio of up to 5 dB. Our JCR70 platform with a fully digital JCR waveform at 73 GHz and 2 GHz bandwidth achieved higher resolution capability than the Radarbook due to higher bandwidth and larger synthesized antenna aperture., Comment: 14 pages

Joint communication and radar (JCR) waveforms with fully digital baseband generation and processing can now be realized at the millimeter-wave (mmWave) band. Prior work has proposed a mmWave wireless local area network (WLAN)-based JCR that exploits the WLAN preamble for radars. The performance of target velocity estimation, however, was limited. In this paper, we propose a virtual waveform design for an adaptive mmWave JCR. The proposed system transmits a few non-uniformly placed preambles to construct several receive virtual preambles for enhancing velocity estimation accuracy, at the cost of only a small reduction in the communication data rate. We evaluate JCR performance trade-offs using the Cramer-Rao Bound (CRB) metric for radar estimation and a novel distortion minimum mean square error (MMSE) metric for data communication. Additionally, we develop three different MMSE-based optimization problems for the adaptive JCR waveform design. Simulations show that an optimal virtual (non-uniform) waveform achieves a significant performance improvement as compared to a uniform waveform. For a radar CRB constrained optimization, the optimal radar range of operation and the optimal communication distortion MMSE (DMMSE) are improved. For a communication DMMSE constrained optimization with a high DMMSE constraint, the optimal radar CRB is enhanced. For a weighted MMSE average optimization, the advantage of the virtual waveform over the uniform waveform is increased with decreased communication weighting. Comparison of MMSE-based optimization with traditional virtual preamble count-based optimization indicated that the conventional solution converges to the MMSE-based one only for a small number of targets and a high signal-to-noise ratio.

In this paper we show that state-of-the-art commercial off-the-shelf Flash memory chip technology (20 nm technology node with multi-level cells) is quite sensitive to ionizing radiation. We find that the fail-bit count in these Flash chips starts to increase monotonically with gamma or X-ray dose at 100 rad(SiO2). Significantly more fail bits are observed in X-ray irradiated devices, most likely due to dose enhancement effects due to high-Z back-end-of-line materials. These results show promise for dosimetry application.

Millimeter-wave (mmWave) radar is widely used in vehicles for applications such as adaptive cruise control and collision avoidance. In this paper, we propose an IEEE 802.11ad-based radar for long-range radar (LRR) applications at the 60 GHz unlicensed band. We exploit the preamble of a single-carrier (SC) physical layer (PHY) frame, which consists of Golay complementary sequences with good correlation properties, as a radar waveform. This system enables a joint waveform for automotive radar and a potential mmWave vehicular communication system based on IEEE 802.11ad, allowing hardware reuse. To formulate an integrated framework of vehicle-to-vehicle (V2V) communication and LRR based on a mmWave consumer wireless local area network (WLAN) standard, we make typical assumptions for LRR applications and incorporate the full duplex radar assumption due to the possibility of sufficient isolation and self-interference cancellation. We develop single- and multi-frame radar receiver algorithms for target detection as well as range and velocity estimation within a coherent processing interval. Our proposed radar processing algorithms leverage channel estimation and time-frequency synchronization techniques used in a conventional IEEE 802.11ad receiver with minimal modifications. Analysis and simulations show that in a single target scenario, a Gbps data rate is achieved simultaneously with cm-level range accuracy and cm/s-level velocity accuracy. The target vehicle is detected with a high probability of detection ($>$99.9$\%$) at a low false alarm of 10$^{-6}$ for an equivalent isotropically radiated power (EIRP) of 43 dBm up to a vehicle separation distance of 200 m.