相关论文: Control Architecture of the Double-Cross-Correlati…
The two-stage precoding has been proposed to reduce the overhead of both the channel training and the channel state information (CSI) feedback for the massive multiple-input multiple-output (MIMO) system. But the overlap of the…
Symbol-level precoding (SLP) is a promising solution for addressing the inherent interference problem in dual-functional radar-communication (DFRC) signal designs. This paper considers an SLP-DFRC signal design problem which optimizes the…
Successful detection of weak signals is a universal challenge for numerous technical and biological systems and crucially limits signal transduction and transmission. Stochastic resonance (SR) has been identified to have the potential to…
This paper presents joint sampling frequency offset (SFO) estimation and compensation algorithms based on the Farrow structure. Unlike conventional approaches that treat estimation and compensation separately, the proposed framework…
One of the main challenges in synchronizing wirelessly connected loudspeakers for spatial audio reproduction is clock skew. Clock skew arises from sample rate offsets ( SROs) between the loudspeakers, caused by the use of independent device…
Integrated sensing, communication, and computation (ISCC) is emerging as a unified design paradigm for future vehicular networks that require joint environment perception, safety-critical information exchange, and latency-sensitive task…
Real-world phenomena that can be formulated as signals are often affected by a number of factors and appear as multi-component modes. To understand and process such phenomena, "divide-and-conquer" is probably the most common strategy to…
Cross-correlation is a popular signal processing technique used in numerous location tracking systems for obtaining reliable range information. However, its efficient design and practical implementation has not yet been achieved on mote…
In distributed model predictive control (MPC), the control input at each sampling time is computed by solving a large-scale optimal control problem (OCP) over a finite horizon using distributed algorithms. Typically, such algorithms require…
In decentralized active noise control (ANC) systems, crosstalk between multichannel secondary sources and error microphones significantly degrades control accuracy. Moreover, prefiltering reference signals in filtered-x (Fx) type algorithms…
Recent advancements in speech encoders have drawn attention due to their integration with Large Language Models for various speech tasks. While most research has focused on either causal or full-context speech encoders, there's limited…
We introduce a recursive algorithm for performing compressed sensing on streaming data. The approach consists of a) recursive encoding, where we sample the input stream via overlapping windowing and make use of the previous measurement in…
One enduring challenge for controlling high frequency sound in local active noise control (ANC) systems is to obtain the acoustic signal at the specific location to be controlled. In some applications such as in ANC headrest systems, it is…
LoRa is currently one of the most widely used low-power wide-area network (LPWAN) technologies. The physical layer leverages a chirp spread spectrum modulation to achieve long-range communication with low power consumption. Synchronization…
In this paper, the parallel multi-extended state observers (ESOs) based active disturbance rejection control approach is proposed to achieve desired tracking performance by automatically selecting the estimation values leading to the least…
Distributed deep learning (DDL) is a promising research area, which aims to increase the efficiency of training deep learning tasks with large size of datasets and models. As the computation capability of DDL nodes continues to increase,…
This paper studies the finite-horizon robust optimal control of constrained linear systems subject to model mismatch and additive stochastic disturbances. Utilizing the system level synthesis (SLS) parameterization, we propose a novel SLS…
Enabling bistatic radar sensing within the context of integrated sensing and communication (ISAC) for future sixth generation mobile networks demands strict synchronization accuracy, which is particularly challenging to be achieved with…
Distributed descent-based methods are an essential toolset to solving optimization problems in multi-agent system scenarios. Here the agents seek to optimize a global objective function through mutual cooperation. Oftentimes, cooperation is…
We describe an asynchronous parallel stochastic coordinate descent algorithm for minimizing smooth unconstrained or separably constrained functions. The method achieves a linear convergence rate on functions that satisfy an essential strong…