26 papers · ranked by Valyu relevance
Tingting Zhang, Haibo Dai, Stefano Savazzi
Affine frequency division multiplexing (AFDM) is regarded as a promising waveform for high-mobility wireless systems. However, the public codebook used in AFDM raises security concerns when the link is observed by an eavesdropper, and meanwhile AFDM communication suffers from a high peak-to-average power ratio (PAPR).…
Wang, Lingyi, Rashed Shelim, Walid Saad + 1 more
—The use of a learnable codebook provides an efficient way for semantic communications to map vectorbased high-dimensional semantic features onto discrete symbol representations required in digital communication systems. In this paper, the problem of codebook-enabled quantization mapping for digital semantic…
Zian Meng, Qiang Li, W.H. Wilson Tang, Yan + 2 more
—Deep learning-based semantic communication has largely relied on analog or semi-digital transmission, which limits compatibility with modern digital communication infrastructures. Recent studies have employed vector quantization (VQ) to enable discrete semantic transmission, yet existing methods neglect channel state…
Yuhao Liu, Xinwei Li, Shuqin Pang, Hao Wu + 1 more
This work extends the generalized nearest neighbor decoding (GNND), originally developed as a receiver architecture for memoryless channels, to a vectorized GNND (Vec-GNND) suitable for in-block memory (IBM) channels. Leveraging the generalized mutual information (GMI) as an operational lower bound on the mismatch…
Zihao Liu, Zilong Liu, Leila Musavian
Sparse code multiple access (SCMA) is a promising code-domain non-orthogonal multiple access scheme which is transmitted over orthogonal frequency division multiplexing (OFDM) to exploit multicarrier diversity. In practice, however, carrier frequency offset (CFO) and phase noise (PN) may disrupt the subcarrier…
Junyu Fan, Chuanlin Liao, Endi Xie, Dongyue Guo + 4 more
As a fundamental imaging task, All-in-One Image Restoration (AiOIR) aims to achieve image restoration caused by multiple degradation patterns via a single model with unified parameters. However, existing methods typically rely on sample-wise supervision, which tends to entangle degradation features with image content.…
Yunxing Xiang, Yi Yan, Yunchao Song, Jing Gao + 6 more
For XL-MIMO multi-user frequency division duplex systems, this paper proposes a near-field beam training scheme using a two-phase combinatorial multi-armed bandit (MAB) framework. This scheme leverages the MAB framework, integrating energy-aware user scheduling and hierarchical beam training to balance communication…
Xi Chen, Homa Esfahanizadeh, Foad Sohrabi
—Efficient channel state information (CSI) compression at the user equipment plays a key role in enabling accurate channel reconstruction and precoder design in massive multipleinput multiple-output systems. A key challenge lies in balancing the CSI feedback overhead with the achievable downlink rate, i.e., maximizing…
Jenkin Tsui, Naila Adam, Woongcheol Choi, Luna Liu + 10 more
Imaging based spatial transcriptomics technologies such as MERFISH have opened new avenues for studying cellular organization and gene expression within intact tissues. However, the accuracy of downstream analyses depends critically on the decoding step that reconstructs barcodes from fluorescence patterns and maps…
Jenkin Tsui, Naila Adam, Woongcheol Choi, Luna Y. Liu + 10 more
Imaging-based spatial transcriptomics technologies have opened new avenues for studying cellular organization and gene expression within intact tissues. However, the accuracy of downstream analyses depends critically on the decoding step that reconstructs barcodes from fluorescence patterns and maps them to gene…
Yuqi Jiang, Tianyi Mao, Jianyong Zhou, Qile Zhao + 4 more
Coded aperture X-ray computed tomography (CAXCT) measures coded X-ray projections to reconstruct the inner structure of an object. Coded apertures, which determine the point spread function, can be designed to improve the reconstruction quality, but most approaches are computationally expensive, leading to very small…
Guoming Song, Dongming Pi, Shancheng Zhao, Chi Wan Sung
Product codes (PCs) are widely used in high-speed communication systems due to their attractive trade-off between error-correction performance and complexity. To further meet the rapidly growing demand for higher data rates, soft-aided hard-decision decoders (SA-HDDs) have been developed. In this paper, we present a…
Han-Ju Yoo, Choi, Dongha, Songkuk Kim + 2 more
—Semantic communication systems often use an endto-end neural network to map input data into continuous symbols. These symbols, which are essentially neural network features, usually have fixed dimensions and heavy-tailed distributions. However, due to the end-to-end training nature of the neural network encoder, the…
Wenbo Shi, Wenlong Xie, Jiashen Hu, Lishan Liu + 1 more
Future wireless networks require channel coding schemes that can provide high reliability, low latency, and strong adaptability under finite-blocklength and structurally heterogeneous transmission scenarios. Globally coupled low-density parity-check (GC-LDPC) codes are promising for such systems because their coupled…
Andreas Straßhofer
This paper presents an improved FEC decoder design outperforming Chase-Pyndiah decoding of product codes by $0.23$ dB. To achieve this, the decoder does not require iteration-dependent coefficients, making it implementation-friendly for sliding-window decoding of staircase codes.
Huazi Zhang, Xianbin Wang, Jiajie Tong, Jun Wang + 1 more
This paper introduces a novel framework for polar codes, designed for flexible Incremental Redundancy Hybrid Automatic Repeat Request (IR-HARQ). By generalizing the decoding order beyond the standard 1$\to$N sequence, we enable a capacity-aware scheduling strategy that prioritizes the decoding of reliable subblocks.…
Simrandeep Singh, Harbinder Singh, Seyed Jaleleddin Mousavirad, Diego Oliva + 2 more
Image thresholding is one of the fastest and easiest approach for image segmentation and serves as a preprocessing step in computer vision and image processing applications, such as surveillance, image perception, scene understanding, artificial intelligence, augmented reality, biomedical imaging, remote sensing, image…
Paul Ghanem, Armin Moharrer, Mathew Yarossi, Alan D. Dorval + 2 more
Transcranial temporal interference stimulation (tTIS) is a promising non-invasive brain stimulation technique that has the potential to selectively modulate deep brain regions by delivering two high-frequency alternating currents that interfere to produce a low-frequency amplitude-modulated envelope at the target. A…
Authors not listed
Continuous manufacturing processes offer significant advantages over batch processes, including easier scalability, reduced costs, lower raw material and solvent consumption, and improved energy efficiency. A robust techno-economic assessment is therefore essential to evaluate and facilitate the adoption of such…
Authors not listed
Inverse molecular design aims to generate novel chemical structures that satisfy multiple property constraints, yet reinforcement-learning (RL) fine-tuning can be sensitive to how objectives are converted into a scalar reward. Here, we systematically analyze how scalarization choices and stabilization mechanisms shape…
Authors not listed
Incorporating prior domain knowledge into Bayesian optimization (BO) remains difficult for statistical methods, which also typically suffer from limited interpretability. Large language models (LLMs) offer complementary strengths in reasoning and knowledge integration, but it remains unclear when and how they improve…
Sumedh S Nagrale, Alik S Widge
The use of Deep Brain Stimulation (DBS) on the ventral capsule/ventral striatum (VCVS) has therapeutic potential for patients with refractory psychiatric disorders, but clinical success is impeded by the need for a time-consuming and trial-and-error process when setting the parameters, this process relying on…
Authors not listed
Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
Authors not listed
This work provides a rigorous theoretical investigation of selective error correction strategies for variational quantum algorithms, with focus on understanding the interplay between error suppression, circuit trainability, and computational resource requirements. We develop a mathematical framework that characterizes…
Changin Oh, Kathleen P. Wilkie
We present the Toroidal Search Algorithm (TSA), a novel population-based metaheuristic optimization method inspired by the topology of a torus. Conventional metaheuristics frequently suffer from boundary stagnation, a phenomenon that severely degrades performance in bounded and high-dimensional search spaces. TSA…
GilHwan Kim, Fabrizio Sergi
Human-in-the-loop optimization (HILO) is an established method for identifying subject-specific optimal controllers for performance augmentation. For HILO algorithms to be useful in rehabilitation, however, the optimization algorithm may need to account for how the human response changes over time in response to…