no code implementations • 20 Nov 2023 • Yating Chen, Cai Wen, Yan Huang, Le Liang, Jie Li, HUI ZHANG, Wei Hong
In this paper, we formulate the precoding problem of integrated sensing and communication (ISAC) waveform as a non-convex quadratically constrainted quadratic program (QCQP), in which the weighted sum of communication multi-user interference (MUI) and the gap between dual-use waveform and ideal radar waveform is minimized with peak-to-average power ratio (PAPR) constraints.
no code implementations • 12 Aug 2023 • Xingyu Zhou, Le Liang, Jing Zhang, Chao-Kai Wen, Shi Jin
However, optimal MIMO detection is associated with a complexity that grows exponentially with the MIMO dimensions and quickly becomes impractical.
no code implementations • 5 Apr 2022 • Yuzhu Mao, Zihao Zhao, Meilin Yang, Le Liang, Yang Liu, Wenbo Ding, Tian Lan, Xiao-Ping Zhang
It is demonstrated that SAFARI under unreliable communications is guaranteed to converge at the same rate as the standard FedAvg with perfect communications.
no code implementations • 12 Aug 2019 • Liang Wang, Hao Ye, Le Liang, Geoffrey Ye Li
The centralized decision unit employs a deep Q-network to allocate resources and then sends the decision results to all vehicles.
no code implementations • 30 Jul 2019 • Liang Wang, Hao Ye, Le Liang, Geoffrey Ye Li
Meanwhile, there exists an optimal number of continuous feedback and binary feedback, respectively.
no code implementations • 7 Jul 2019 • Le Liang, Hao Ye, Guanding Yu, Geoffrey Ye Li
The traditional wisdom is to explicitly formulate resource allocation as an optimization problem and then exploit mathematical programming to solve the problem to a certain level of optimality.
1 code implementation • 8 May 2019 • Le Liang, Hao Ye, Geoffrey Ye Li
This paper investigates the spectrum sharing problem in vehicular networks based on multi-agent reinforcement learning, where multiple vehicle-to-vehicle (V2V) links reuse the frequency spectrum preoccupied by vehicle-to-infrastructure (V2I) links.
Information Theory Information Theory
no code implementations • 6 Mar 2019 • Hao Ye, Le Liang, Geoffrey Ye Li, Biing-Hwang Fred Juang
We propose to use a conditional generative adversarial net (GAN) to represent channel effects and to bridge the transmitter DNN and the receiver DNN so that the gradient of the transmitter DNN can be back-propagated from the receiver DNN.
Information Theory Information Theory
no code implementations • 1 Apr 2018 • Le Liang, Hao Ye, Geoffrey Ye Li
As wireless networks evolve towards high mobility and providing better support for connected vehicles, a number of new challenges arise due to the resulting high dynamics in vehicular environments and thus motive rethinking of traditional wireless design methodologies.