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| 1 | V2X-Communication Assisted Interference Minimization for Automotive Radars显示文摘With the development of automated driving vehicles, more and more vehicles will be fitted with more than one automotive radars, and the radar mutual interference will become very significant. Vehicle to everything (V2X) communication is a potential way for coordinating automotive radars and reduce the mutual interference. In this paper, we analyze the positional relation of the two radars that interfere with each other, and evaluate the mutual interference for different types of automotive radars based on Poisson point process (PPP). We also propose a centralized framework and the corresponding algorithm, which relies on V2X communication systems to allocate the spectrum resources for automotive radars to minimize the interference. The minimum spectrum resources required for zero-interference are analyzed for different cases. Simulation results validate the analysis and show that the proposed framework can achieve near-zero-interference with the minimum spectrum resources. | Jingxuan Huang Zesong Fei Tianxiong Wang Xinyi Wang Fan Liu Haijun Zhou J.Andrew Zhang Guohua Wei | 2019 | China Communications2019，16，10： | 4 |
| 2 | Distributed Transmit Beamforming for UAV to Base Communications显示文摘Distributed transmit beamforming(DTB) is very efficient for extending the communication distance between a swarm of UAVs and the base,particularly when considering the constraints in weight and battery life for payloads on UAVs.In this paper,we review major function modules and potential solutions in realizing DTB in UAV systems,such as timing and carrier synchronization,phase drift tracking and compensation,and beamforming vector generation and updating.We then focus on beamforming vector generation and updating,and introduce a concatenated training scheme,together with a recursive channel estimation and updating algorithm.We also propose three approaches for tracking the variation of channels and updating the vectors.The effectiveness of these approaches is validated by simulation results. | Yin Lu Jun Fang Zhong Guo J.Andrew Zhang | 2019 | China Communications2019，16，1： | 2 |
| 3 | Performance Characterization and Receiver Design for Random Temporal Multiple Access in Non-Coordinated Networks显示文摘Random access is a well-known multiple access method for uncoordinated communication nodes.Existing work mainly focuses on optimizing iterative access protocols,assuming that packets are corrupted once they are collided,or that feedback is available and can be exploited.In practice,a packet may still be able to be recovered successfully even when collided with other packets.System design and performance analysis under such a situation,particularly when the details of collision are taken into consideration,are less known.In this paper,we provide a framework for analytically evaluating the actual detection performance in a random temporal multiple access system where nodes can only transmit.Explicit expressions are provided for collision probability and signal to interference and noise ratio(SINR)when different numbers of packets are collided.We then discuss and compare two receiver options for the AP,and provide detailed receiver design for the premium one.In particular,we propose a synchronization scheme which can largely reduce the preamble length.We also demonstrate that system performance could be a convex function of preamble length both analytically and via simulation,as well as the forward error correction(FEC)coding rate. | Yin Lu Jun Fang Zhong Guo J.Andrew Zhang | 2019 | China Communications2019，16，6： | 1 |
| 4 | Joint resource allocation and power control for radar interference mitigation in multi-UAV networks显示文摘Navigation problems of unmanned air vehicles(UAVs)flying in a formation have been investigated recently,where collision avoidance is a significant issue to be addressed.In this paper,we study resource allocation and power control for radar sensing in a multi-unmanned aerial vehicle(multi-UAV)formation flight system where multiple UAVs simultaneously perform radar sensing.To cope with mutual radar interference among the UAVs,we formulate a joint channel allocation and UAV transmission power control problem to maximize the minimum signal-to-interference-plus-noise ratio(SINR)of the radar echo signals.We then propose a computationally practical method to solve this NP-hard problem by decomposing it into two sub-problems,i.e.,channel allocation and transmission power control.An iterative channel allocation and power control algorithm(ICAPCA)is proposed to jointly solve these two sub-problems.We also propose a reduced-complexity greedy channel allocation algorithm(GCAA),which can also be used to provide an initial solution to ICAPCA.Simulation results show that the proposed ICAPCA and GCAA can improve the minimum SINR and radar sensing performance significantly. | Xinyi WANG Zesong FEI Jingxuan HUANG J.Andrew ZHANG Jinhong YUAN | 2021 | Science China(Information Sciences)2021，64，8： | 0 |
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