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Ya-Feng Liu

24 accepted papers

2025

A Gradient Guided Diffusion Framework for Chance Constrained Programming

NeurIPS 2025poster

Chance constrained programming (CCP) is a powerful framework for addressing optimization problems under uncertainty. In this paper, we introduce a novel Gradient-Guided Diffusion-based Optimization framework, termed GGDOpt, which tackles CCP through three key innovations. First, GGDOpt accommodates…

Cited by 0SourcecodeScholar
2025

Symbol-Level Precoding-Based Self-Interference Cancellation for ISAC Systems

ICASSP 2025accepted

Consider an integrated sensing and communication (ISAC) system where a base station (BS) employs a full-duplex radio to simultaneously serve multiple users and detect a target. The detection performance of the BS may be compromised by self-interference (SI) leakage. This paper investigates the feasi…

Cited by 0SourceScholar
2024

An Efficient Alternating Riemannian/Projected Gradient Descent Ascent Algorithm for Fair Principal Component Analysis

ICASSP 2024accepted

Fair principal component analysis (FPCA), a ubiquitous dimensionality reduction technique in signal processing and machine learning, aims to find a low-dimensional representation for a high-dimensional dataset in view of fairness. The FPCA problem involves optimizing a non-convex and non-smooth func…

Cited by 0SourceScholar
2024

Globally Optimal Beamforming Design for Integrated Sensing and Communication Systems

ICASSP 2024accepted

In this paper, we propose a multi-input multi-output beamforming transmit optimization model for joint radar sensing and multi-user communications, where the design of the beamformers is formulated as an optimization problem whose objective is a weighted combination of the sum rate and the Cramér-Ra…

Cited by 0SourceScholar
2024

Joint Beamforming and Compression Design for Per-Antenna Power Constrained Cooperative Cellular Networks

ICASSP 2024accepted

In the cooperative cellular network, relay-like base stations are connected to the central processor (CP) via rate-limited fronthaul links and the joint processing is performed at the CP, which thus can effectively mitigate the multiuser interference. In this paper, we consider the joint beamforming…

Cited by 0SourceScholar
2023

A Riemannian Exponential Augmented Lagrangian Method for Computing the Projection Robust Wasserstein Distance

NeurIPS 2023poster

Projection robust Wasserstein (PRW) distance is recently proposed to efficiently mitigate the curse of dimensionality in the classical Wasserstein distance. In this paper, by equivalently reformulating the computation of the PRW distance as an optimization problem over the Cartesian product of the…

Cited by 9SourcePDFScholar
2023

Efficient Quantized Constant Envelope Precoding for Multiuser Downlink Massive MIMO Systems

ICASSP 2023accepted

Quantized constant envelope (QCE) precoding, a new transmission scheme that only discrete QCE transmit signals are allowed at each antenna, has gained growing research interests due to its ability of reducing the hardware cost and the energy consumption of massive multiple-input multiple-output (MIM…

Cited by 0SourceScholar
2023

Scaling Law Analysis for Covariance Based Activity Detection in Cooperative Multi-Cell Massive Mimo

ICASSP 2023accepted

This paper studies the covariance based activity detection problem in a multi-cell massive multiple-input multiple-output (MIMO) system, where the active devices transmit their signature sequences to multiple base stations (BSs), and the BSs cooperatively detect the active devices based on the recei…

Cited by 0SourceScholar
2022

A Novel Negative ℓ1 Penalty Approach for Multiuser One-Bit Massive MIMO Downlink with PSK Signaling

ICASSP 2022accepted

This paper considers the one-bit precoding problem for the multiuser downlink massive multiple-input multiple-output (MIMO) system with phase shift keying (PSK) modulation and focuses on the celebrated constructive interference (CI)-based problem formulation. The existence of the discrete one-bit co…

Cited by 0SourceScholar
2022

Efficiently and Globally Solving Joint Beamforming and Compression Problem in the Cooperative Cellular Network Via Lagrangian Duality

ICASSP 2022accepted

Consider the joint beamforming and quantization problem in the cooperative cellular network, where multiple relay-like base stations (BSs) connected to the central processor (CP) via rate-limited fronthaul links cooperatively serve the users. This problem can be formulated as the minimization of the…

Cited by 0SourceScholar
2022

Optimal Qos-Aware Network Slicing for Service-Oriented Networks with Flexible Routing

ICASSP 2022accepted

In this paper, we consider the network slicing problem which attempts to map multiple customized virtual network requests (also called services) to a common shared network infrastructure and allocate network resources to meet diverse quality of service (QoS) requirements. We first propose a mixed in…

Cited by 0SourceScholar
2021

An Efficient Active Set Algorithm for Covariance Based Joint Data and Activity Detection for Massive Random Access with Massive MIMO

ICASSP 2021accepted

This paper proposes a computationally efficient algorithm to solve the joint data and activity detection problem for massive random access with massive multiple-input multiple-output (MIMO). The BS acquires the active devices and their data by detecting the transmitted preassigned nonorthogonal sign…

Cited by 0SourceScholar
2021

An Efficient Algorithm For Device Detection And Channel Estimation In Asynchronous IOT Systems

ICASSP 2021accepted

A great amount of endeavour has recently been devoted to the joint device activity detection and channel estimation problem in massive machine-type communications. This paper targets at two practical issues along this line that have not been addressed before: asynchronous transmission from uncoordin…

Cited by 0SourceScholar
2021

An Efficient Linear Programming Rounding-and-Refinement Algorithm for Large-Scale Network Slicing Problem

ICASSP 2021accepted

In this paper, we consider the network slicing problem which attempts to map multiple customized virtual network requests (also called services) to a common shared network infrastructure and allocate network resources to meet diverse service requirements, and propose an efficient two-stage algorithm…

Cited by 0SourceScholar
2019

On the Equivalence of Semidifinite Relaxations for MIMO Detection with General Constellations

ICASSP 2019accepted

The multiple-input multiple-output (MIMO) detection problem is a fundamental problem in modern digital communications. Semidefinite relaxation (SDR) based algorithms are a popular class of approaches to solving the problem because the algorithms have a polynomial-time worst-case complexity and gener…

Cited by 0SourceScholar
2018

Software Defined Resource Allocation for Service-Oriented Networks

ICASSP 2018accepted

To support multiple on-demand services over several fixed communication networks, the network operators must allow flexible customization and fast provision of their network resources. One effective approach is network virtualization, whereby each service is mapped to a virtual subnetwork providing…

Cited by 0SourceScholar
2017

A two-stage optimization approach to the asynchronous multi-sensor registration problem

ICASSP 2017accepted

An important step in multi-sensor data fusion is sensor registration, namely, to estimate sensors' range and azimuth biases from their asynchronous measurements. Assuming the target moves in a straight line with an unknown constant velocity, we propose a two-stage nonlinear least square (LS) approac…

Cited by 0SourceScholar
2017

Uplink and downlink user pairing in full-duplex multi-user systems: Complexity and algorithms

ICASSP 2017accepted

In this paper, we consider a wireless network with one full-duplex (FD) base station (BS) and a set of half-duplex (HD) user equipments (UEs). In such scenario, in addition to the self-interference, the co-channel interference from uplink UEs to downlink UEs is the main bottleneck for the network pe…

Cited by 0SourceScholar
2015

An iterative reweighted minimization framework for joint channel and power allocation in the OFDMA system

ICASSP 2015accepted

We consider the joint channel and power allocation problem for the OFDMA system. The problem is to find a joint channel and power allocation strategy to minimize the total transmission power subject to quality of service constraints and the OFDMA constraint (i.e, at most one user is allowed to acces…

Cited by 0SourceScholar