1,009 research outputs found
Joint Millimeter-Wave Communication and Radar for Automotive Applications
DTRT13-G-UTC58Automotive 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 developed a mmWave wireless local area network (WLAN)-based automotive JCR that exploits the WLAN preamble for radars. The performance of target velocity estimation, however, was limited. In this paper, we propose an adaptive virtual JCR waveform design for automotive applications at the mmWave band. 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
Joint Beamforming Design for RIS-enabled Integrated Positioning and Communication in Millimeter Wave Systems
Integrated positioning and communication (IPAC) system and reconfigurable
intelligent surface (RIS) are both considered to be key technologies for future
wireless networks. Therefore, in this paper, we propose a RIS-enabled IPAC
scheme with the millimeter wave system. First, we derive the explicit
expressions of the time-of-arrival (ToA)-based Cram\'er-Rao bound (CRB) and
positioning error bound (PEB) for the RIS-aided system as the positioning
metrics. Then, we formulate the IPAC system by jointly optimizing active
beamforming in the base station (BS) and passive beamforming in the RIS to
minimize the transmit power, while satisfying the communication data rate and
PEB constraints. Finally, we propose an efficient two-stage algorithm to solve
the optimization problem based on a series of methods such as the exhaustive
search and semidefinite relaxation (SDR). Simulation results show that by
changing various critical system parameters, the proposed RIS-enabled IPAC
system can cater to both reliable data rates and high-precision positioning in
different transmission environments
Cooperative Passive Coherent Location: A Promising 5G Service to Support Road Safety
5G promises many new vertical service areas beyond simple communication and
data transfer. We propose CPCL (cooperative passive coherent location), a
distributed MIMO radar service, which can be offered by mobile radio network
operators as a service for public user groups. CPCL comes as an inherent part
of the radio network and takes advantage of the most important key features
proposed for 5G. It extends the well-known idea of passive radar (also known as
passive coherent location, PCL) by introducing cooperative principles. These
range from cooperative, synchronous radio signaling, and MAC up to radar data
fusion on sensor and scenario levels. By using software-defined radio and
network paradigms, as well as real-time mobile edge computing facilities
intended for 5G, CPCL promises to become a ubiquitous radar service which may
be adaptive, reconfigurable, and perhaps cognitive. As CPCL makes double use of
radio resources (both in terms of frequency bands and hardware), it can be
considered a green technology. Although we introduce the CPCL idea from the
viewpoint of vehicle-to-vehicle/infrastructure (V2X) communication, it can
definitely also be applied to many other applications in industry, transport,
logistics, and for safety and security applications
AI Empowered Channel Semantic Acquisition for 6G Integrated Sensing and Communication Networks
Motivated by the need for increased spectral efficiency and the proliferation
of intelligent applications, the sixth-generation (6G) mobile network is
anticipated to integrate the dual-functions of communication and sensing (C&S).
Although the millimeter wave (mmWave) communication and mmWave radar share
similar multiple-input multiple-output (MIMO) architecture for integration, the
full potential of dual-function synergy remains to be exploited. In this paper,
we commence by overviewing state-of-the-art schemes from the aspects of
waveform design and signal processing. Nevertheless, these approaches face the
dilemma of mutual compromise between C&S performance. To this end, we reveal
and exploit the synergy between C&S. In the proposed framework, we introduce a
two-stage frame structure and resort artificial intelligence (AI) to achieve
the synergistic gain by designing a joint C&S channel semantic extraction and
reconstruction network (JCASCasterNet). With just a cost-effective and
energy-efficient single sensing antenna, the proposed scheme achieves enhanced
overall performance while requiring only limited pilot and feedback signaling
overhead. In the end, we outline the challenges that lie ahead in the future
development of integrated sensing and communication networks, along with
promising directions for further research.Comment: 9 pages, 5 figures, accepted by the IEEE journa
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