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Kaixuan Bao

dblp:343/9736 · DBLP profile ↗
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4ranked-venue papers
4as first author
4since 2021 · last 2026
0000-0002-3521-2922ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 3 · 3 first-author · 3 since 2021Theory of computation · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Coding theory · 87% Information theory · 13%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Memory systems · 100%
Computer networks
1 paper
Physical-layer communications · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Memory systems
in-memory computing
1.012026
A Framework of Arithmetic-Level Variable Precision Computing for In-Memory Architecture: Case Study in MIMO Signal Processing · IEEE Trans. Mob. Comput. 2026
Memory systems
processing-in-memory
1.012026
A Framework of Arithmetic-Level Variable Precision Computing for In-Memory Architecture: Case Study in MIMO Signal Processing · IEEE Trans. Mob. Comput. 2026
Coding theory › channel coding
finite blocklength coding
1.012026
New Sphere-Packing Bounds for Finite-Blocklength Coding Over Additive Noise Channels · IEEE Trans. Inf. Theory 2026
Coding theory › error-correcting codes › coding bounds › packing bounds
sphere-packing bound
1.012026
New Sphere-Packing Bounds for Finite-Blocklength Coding Over Additive Noise Channels · IEEE Trans. Inf. Theory 2026
Physical-layer communications › MIMO
MIMO signal processing
0.312026
A Framework of Arithmetic-Level Variable Precision Computing for In-Memory Architecture: Case Study in MIMO Signal Processing · IEEE Trans. Mob. Comput. 2026
Information theory › channel capacity
additive noise channel
0.312026
New Sphere-Packing Bounds for Finite-Blocklength Coding Over Additive Noise Channels · IEEE Trans. Inf. Theory 2026

Methods — techniques the papers use, named apart from their topics

variable precision arithmetic · 2.0in-memory architecture · 2.0sphere-packing bound · 1.0
YearPublicationVenuePosition
2026 New Sphere-Packing Bounds for Finite Blocklengths
Kaixuan Bao, Wei Xu 0001, Xiaohu You 0001, H. Vincent Poor
ICC1
2026 A Low-Complexity Markovian Arithmetic-Level Variable Precision Computing for MIMO Signal Processing
abstract
The computational complexity of multiple-input multiple-output (MIMO) signal processing algorithms grows exponentially, resulting in increasing computational latency. Conventional approaches to reducing latency are predominantly algorithm-specific, addressing only limited components within the overall MIMO system. In this paper, we propose a novel arithmetic-level variable precision computing (VPC) scheme, introducing a new universal compatible methodology for computational latency reduction. The proposed arithmetic-level VPC dynamically assigns varying levels of computing precision to individual arithmetic operations within an algorithm and employs a Markovian process model with low-complexity computations to minimize additional complexity overhead introduced by VPC. Numerical simulations demonstrate that the proposed scheme significantly outperforms conventional fixed-length computing (FLC), achieving superior performance while maintaining the same level of average computing precision.
Kaixuan Bao, Jiehao Miao, Wei Xu 0001, Yongming Huang 0001, Derrick Wing Kwan Ng
IEEE Internet Things J.1
2026 New Sphere-Packing Bounds for Finite-Blocklength Coding Over Additive Noise Channels
Kaixuan Bao, Wei Xu 0001, Xiaohu You 0001, H. Vincent Poor
IEEE Trans. Inf. Theory1
2026 A Framework of Arithmetic-Level Variable Precision Computing for In-Memory Architecture: Case Study in MIMO Signal Processing
Kaixuan Bao, Wei Xu 0001, Xiaohu You 0001, Derrick Wing Kwan Ng
IEEE Trans. Mob. Comput.1