Communication-Assisted Sensing in 6G Networks

The exploration of coordination gain achieved through the synergy of sensing and communication (S&C) functions plays a vital role in improving the performance of integrated sensing and communication systems. This paper focuses on the optimal waveform design for communication-assisted sensing (CAS) systems within the context of 6G perceptive networks. In the CAS process, the base station actively senses the targets through device-free wireless sensing and simultaneously transmits the pertinent information to end-users. In our research, we establish a CAS framework grounded in the principles of rate-distortion theory and the source-channel separation theorem (SCT) in lossy data transmission. This framework provides a comprehensive understanding of the interplay between distortion, coding rate, and channel capacity. The purpose of waveform design is to minimize the sensing distortion at the user end while adhering to the SCT and power budget constraints. In the context of target response matrix estimation, we propose two distinct waveform strategies: the separated S&C and dual-functional waveform schemes. In the former strategy, we develop a simple one-dimensional search algorithm, shedding light on a notable power allocation tradeoff between the S&C waveform. In the latter scheme, we conceive a heuristic mutual information optimization algorithm for the general case, alongside a modified gradient projection algorithm tailored for the scenarios with independent sensing sub-channels. Additionally, we identify the presence of both subspace tradeoff and water-filling tradeoff. Finally, we validate the effectiveness of the proposed algorithms through numerical simulations

Seeing is Believing: Detecting Sybil Attack in FANET by Matching Visual and Auditory Domains

The flying ad hoc network (FANET) will play a crucial role in the B5G/6G era since it provides wide coverage and on-demand deployment services in a distributed manner. The detection of Sybil attacks is essential to ensure trusted communication in FANET. Nevertheless, the conventional methods only utilize the untrusted information that UAV nodes passively ``heard'' from the ``auditory" domain (AD), resulting in severe communication disruptions and even collision accidents. In this paper, we present a novel VA-matching solution that matches the neighbors observed from both the AD and the ``visual'' domain (VD), which is the first solution that enables UAVs to accurately correlate what they ``see'' from VD and ``hear'' from AD to detect the Sybil attacks. Relative entropy is utilized to describe the similarity of observed characteristics from dual domains. The dynamic weight algorithm is proposed to distinguish neighbors according to the characteristics' popularity. The matching model of neighbors observed from AD and VD is established and solved by the vampire bat optimizer. Experiment results show that the proposed VA-matching solution removes the unreliability of individual characteristics and single domains. It significantly outperforms the conventional RSSI-based method in detecting Sybil attacks. Furthermore, it has strong robustness and achieves high precision and recall rates.Comment: 7 pages, 9 figures, 1 tabl

Convergence of quantum random walks with decoherence

In this paper, we study the discrete-time quantum random walks on a line subject to decoherence. The convergence of the rescaled position probability distribution $p(x,t)$ depends mainly on the spectrum of the superoperator $\mathcal{L}_{kk}$. We show that if 1 is an eigenvalue of the superoperator with multiplicity one and there is no other eigenvalue whose modulus equals to 1, then $\hat {P}(\frac{\nu} {\sqrt t},t)$ converges to a convex combination of normal distributions. In terms of position space, the rescaled probability mass function $p_t (x, t) \equiv p(\sqrt t x, t)$, $x \in Z/\sqrt t$, converges in distribution to a continuous convex combination of normal distributions. We give an necessary and sufficient condition for a U(2) decoherent quantum walk that satisfies the eigenvalue conditions. We also give a complete description of the behavior of quantum walks whose eigenvalues do not satisfy these assumptions. Specific examples such as the Hadamard walk, walks under real and complex rotations are illustrated. For the O(2) quantum random walks, an explicit formula is provided for the scaling limit of $p(x,t)$ and their moments. We also obtain exact critical exponents for their moments at the critical point and show universality classes with respect to these critical exponents

A Margin-based MLE for Crowdsourced Partial Ranking

A preference order or ranking aggregated from pairwise comparison data is commonly understood as a strict total order. However, in real-world scenarios, some items are intrinsically ambiguous in comparisons, which may very well be an inherent uncertainty of the data. In this case, the conventional total order ranking can not capture such uncertainty with mere global ranking or utility scores. In this paper, we are specifically interested in the recent surge in crowdsourcing applications to predict partial but more accurate (i.e., making less incorrect statements) orders rather than complete ones. To do so, we propose a novel framework to learn some probabilistic models of partial orders as a \emph{margin-based Maximum Likelihood Estimate} (MLE) method. We prove that the induced MLE is a joint convex optimization problem with respect to all the parameters, including the global ranking scores and margin parameter. Moreover, three kinds of generalized linear models are studied, including the basic uniform model, Bradley-Terry model, and Thurstone-Mosteller model, equipped with some theoretical analysis on FDR and Power control for the proposed methods. The validity of these models are supported by experiments with both simulated and real-world datasets, which shows that the proposed models exhibit improvements compared with traditional state-of-the-art algorithms.Comment: 9 pages, Accepted by ACM Multimedia 2018 as a full pape

Learning Disentangled Semantic Representations for Zero-Shot Cross-Lingual Transfer in Multilingual Machine Reading Comprehension

Multilingual pre-trained models are able to zero-shot transfer knowledge from rich-resource to low-resource languages in machine reading comprehension (MRC). However, inherent linguistic discrepancies in different languages could make answer spans predicted by zero-shot transfer violate syntactic constraints of the target language. In this paper, we propose a novel multilingual MRC framework equipped with a Siamese Semantic Disentanglement Model (SSDM) to disassociate semantics from syntax in representations learned by multilingual pre-trained models. To explicitly transfer only semantic knowledge to the target language, we propose two groups of losses tailored for semantic and syntactic encoding and disentanglement. Experimental results on three multilingual MRC datasets (i.e., XQuAD, MLQA, and TyDi QA) demonstrate the effectiveness of our proposed approach over models based on mBERT and XLM-100. Code is available at:https://github.com/wulinjuan/SSDM_MRC.Comment: Accepted to ACL 2022 (main conference

Chromosomal evolution in Brassicacae: Allopolyploidy, aneuploidy and transgene transmission [abstract]

Abstract only availablePolyploidy is a eukaryotic phenomenon common to plants that serves as an evolutionary mechanism for speciation. Diploid species undergo polyploidization through single genome duplication (autopolyploidy) or by the hybridization of genomes from two or more distinct progenitor species (allopolyploidy). Aneuploidy can arise where offspring possess extra or fewer chromosomes than their progenitors. Over successive generations, changes in chromosomal number and rearrangement can lead to speciation or differentiation of ecotypes within a species. Using advanced molecular cytogenetics and fluorescent in situ hybridization (FISH), we can distinguish chromosomes and genomic markers among different ecotypes and species. In the agricultural industry where genetically modified organisms (GMOs) are used, aneuploidy and homoeologous recombination of transgenic elements presents a potential mechanism of moving transgenes from GMO crops into the genomes of wild diploids. These wild diploids then have the potential to become "superweeds" that can disrupt ecological systems. The goal of this study was to investigate the movement of a transgene from an allopolyploid to a diploid in controlled greenhouse crosses. Transgenic Brassica napus allopolyploid plants (AACC) were backcrossed to natural Brassica rapa (AA) recurrently over three generations. We examined each of the three backcross generations for chromosome number and gene transmission. Molecular cytogenetic analysis was performed on flower buds from each backcross, chromosome numbers were recorded and gene transmission was analyzed by PCR. As expected, we found aneuploidy in Brassica napus x Brassica rapa hybrids suggesting potential for homoeologous recombination of transgenes into non-transgenic diploid species. Surprisingly, despite aneuploidy, we also found a high rate of both germination and transmission of the transgene into wild Brassica rapa, suggesting the need to find safe sites in Brassica napus to insert transgenes

Multiscale microstructures and microstructural effects on the reliability of microbumps in three-dimensional integration

The dimensions of microbumps in three-dimensional integration reach microscopic scales and thus necessitate a study of the multiscale microstructures in microbumps. Here, we present simulated mesoscale and atomic-scale microstructures of microbumps using phase field and phase field crystal models. Coupled microstructure, mechanical stress, and electromigration modeling was performed to highlight the microstructural effects on the reliability of microbumps. The results suggest that the size and geometry of microbumps can influence both the mesoscale and atomic-scale microstructural formation during solidification. An external stress imposed on the microbump can cause ordered phase growth along the boundaries of the microbump. Mesoscale microstructures formed in the microbumps from solidification, solid state phase separation, and coarsening processes suggest that the microstructures in smaller microbumps are more heterogeneous. Due to the differences in microstructures, the von Mises stress distributions in microbumps of different sizes and geometries vary. In addition, a combined effect resulting from the connectivity of the phase morphology and the amount of interface present in the mesoscale microstructure can influence the electromigration reliability of microbumps