Fast Antenna and Beam Switching Method for mmWave Handsets With Hand Blockage

Shih, Wan-Ting; Wen, Chao; Tsai, Shang Ho; Jin, Shi

doi:10.1109/twc.2021.3090447

Cited by 7 publications

(1 citation statement)

References 25 publications

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“…Different from conventional beam sweeping in communication systems, the agent meanwhile listens to the reflected signal by the receive antenna array, thus enabling sensing the surrounding environment. We assume that transmit and receive antenna arrays are placed separately on the agent to relax the self-interference [13], [40] 1 . Therefore, during beam sweeping, the agent sends RF signals in beams then captures the reflective surfaces from the echo signals, which serve as active sensing.…”

Section: System Model and Problem Formulationmentioning

confidence: 99%

Hybrid Active and Passive Sensing for SLAM in Wireless Communication Systems

Yang,

Wen,

Jin

2022

Preprint

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Integrating sensing functions into future mobile equipment has become an important trend. Realizing different types of sensing and achieving mutual enhancement under the existing communication hardware architecture is a crucial challenge in realizing the deep integration of sensing and communication.In the 5G New Radio context, active sensing can be performed through uplink beam sweeping on the user equipment (UE) side to observe the surrounding environment. In addition, the UE can perform passive sensing through downlink channel estimation to measure the multipath component (MPC) information. This study is the first to develop a hybrid simultaneous localization and mapping (SLAM) mechanism that combines active and passive sensing, in which mutual enhancement between the two sensing modes is realized in communication systems. Specifically, we first establish a common feature associated with the reflective surface to bridge active and passive sensing, thus enabling information fusion. Based on the common feature, we can attain physical anchor initialization through MPC with the assistance of active sensing. Then, we extend the classic probabilistic data association SLAM mechanism to achieve UE localization and continuously refine the physical anchor and target reflections through the subsequent passive sensing. Numerical results show that the proposed hybrid active and passive sensing-based SLAM mechanism can work successfully in tricky scenarios without any prior information on the floor plan, anchors, or agents. Moreover, the proposed algorithm demonstrates significant performance gains compared with active or passive sensing only mechanisms.

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Section: System Model and Problem Formulationmentioning

confidence: 99%