Performance Comparison of Cooperative and Distributed Spectrum Sensing in Cognitive Radio

In this paper, we compare the performances of cooperative and distributed spectrum sensing in wireless sensor networks. After introducing the basic problem, we describe two strategies: 1) a cooperative sensing strategy, which takes advantage of cooperation diversity gain to increase probability of detection and 2) a distributed sensing strategy, which by passing the results in an inter-node manner increases energy efficiency and fairness among nodes. Then, we compare the performances of the strategies in terms of three criteria: agility, energy efficiency, and robustness against SNR changes, and summarize the comparison. It shows that: 1) the non-cooperative strategy has the best fairness of energy consumption, 2) the cooperative strategy leads to the best agility, and 3) the distributed strategy leads to the lowest energy consumption and the best robustness against SNR changes.Comment: submitte

Restoration of pseudo-spin symmetry in N=32N=32 and 3434 isotones described by relativistic Hartree-Fock theory

Restoration of pseudo-spin symmetry (PSS) along the $N=32$ and $34$ isotonic chains and the physics behind are studied by applying the relativistic Hartree-Fock theory with effective Lagrangian PKA1. Taking the proton pseudo-spin partners $(\pi2s_{1/2},\pi1d_{3/2})$ as candidates, systematic restoration of PSS along both isotonic chains is found from sulphur (S) to nickel (Ni), while distinct violation from silicon (Si) to sulphur is discovered near the drip lines. The effects of the tensor-force components introduced naturally by the Fock terms are investigated, which can only partly interpret the systematics from calcium to nickel, but fail for the overall trends. Further analysis following the Schr\"{o}dinger-like equation of the lower component of Dirac spinor shows that the contributions from the Hartree terms dominate the overall systematics of the PSS restoration, and such effects can be self-consistently interpreted by the evolution of the proton central density profiles along both isotonic chains. Specifically the distinct PSS violation is found to tightly relate with the dramatic changes from the bubble-like density profiles in silicon to the central-bumped ones in sulphur.Comment: 4 figures, to be published in Chinese Physics

HyCell: Enabling GREEN Base Station Operations in Software-Defined Radio Access Networks

The radio access networks (RANs) need to support massive and diverse data traffic with limited spectrum and energy. To cope with this challenge, software-defined radio access network (SDRAN) architectures have been proposed to renovate the RANs. However, current researches lack the design and evaluation of network protocols. In this paper, we address this problem by presenting the protocol design and evaluation of hyper-cellular networks (HyCell), an SDRAN framework making base station (BS) operations globally resource-optimized and energy-efficient (GREEN). Specifically, we first propose a separation scheme to realize the decoupled air interface in HyCell. Then we design a BS dispatching protocol which determines and assigns the optimal BS for serving mobile users, and a BS sleeping protocol to improve the network energy efficiency. Finally, we evaluate the proposed design in our HyCell testbed. Our evaluation validates the feasibility of the proposed separation scheme, demonstrates the effectiveness of BS dispatching, and shows great potential in energy saving through BS sleeping control.Comment: 6 pages, 4 figures, accepted by IEEE ICC 2015 Workshop on Next Generation Green IC

Towards Service-oriented 5G: Virtualizing the Networks for Everything-as-a-Service

It is widely acknowledged that the forthcoming 5G architecture will be highly heterogeneous and deployed with a high degree of density. These changes over the current 4G bring many challenges on how to achieve an efficient operation from the network management perspective. In this article, we introduce a revolutionary vision of the future 5G wireless networks, in which the network is no longer limited by hardware or even software. Specifically, by the idea of virtualizing the wireless networks, which has recently gained increasing attention, we introduce the Everything-as-a-Service (XaaS) taxonomy to light the way towards designing the service-oriented wireless networks. The concepts, challenges along with the research opportunities for realizing XaaS in wireless networks are overviewed and discussed.Comment: 18 pages, 5 figure

Organization mechanism and counting algorithm on Vertex-Cover solutions

Counting the solution number of combinational optimization problems is an important topic in the study of computational complexity, especially on the #P-complete complexity class. In this paper, we first investigate some organizations of Vertex-Cover unfrozen subgraphs by the underlying connectivity and connected components of unfrozen vertices. Then, a Vertex-Cover Solution Number Counting Algorithm is proposed and its complexity analysis is provided, the results of which fit very well with the simulations and have better performance than those by 1-RSB in a neighborhood of c = e for random graphs. Base on the algorithm, variation and fluctuation on the solution number statistics are studied to reveal the evolution mechanism of the solution numbers. Besides, marginal probability distributions on the solution space are investigated on both random graph and scale-free graph to illustrate different evolution characteristics of their solution spaces. Thus, doing solution number counting based on graph expression of solution space should be an alternative and meaningful way to study the hardness of NP-complete and #P-complete problems, and appropriate algorithm design can help to achieve better approximations of solving combinational optimization problems and the corresponding counting problems.Comment: 17 pages, 6 figure

ERA: Towards Privacy Preservation and Verifiability for Online Ad Exchanges

Ad exchanges are kind of the most popular online advertising marketplaces for trading ad spaces over the Internet. Ad exchanges run auctions to sell diverse ad spaces on the publishers' web-pages to advertisers, who want to display ads on ad spaces. However, the parties in an ad auction cannot verify whether the auction is carried out correctly or not. Furthermore, the advertisers are usually unwilling to reveal their sensitive bids and identities. In this paper, we jointly consider the auction verifiability and the advertisers' privacy preservation, and thus propose ERA, which is an Efficient, pRivacy-preserving, and verifiAble online auction mechanism for ad exchanges. ERA exploits an order preserving encryption scheme to guarantee privacy preservation, and achieves verifiability by constructing a novel protocol of privacy preserving integer comparison, which is built on the Paillier homomorphic encryption scheme. We extensively evaluate the performance of ERA, and our evaluation results show that ERA satisfies several desirable properties with low computation, communication, and storage overheads, so ERA can be easily deployed in today's ad exchanges

Solving the inverse problem of noise-driven dynamic networks

Nowadays massive amount of data are available for analysis in natural and social systems. Inferring system structures from the data, i.e., the inverse problem, has become one of the central issues in many disciplines and interdisciplinary studies. In this Letter, we study the inverse problem of stochastic dynamic complex networks. We derive analytically a simple and universal inference formula called double correlation matrix (DCM) method. Numerical simulations confirm that the DCM method can accurately depict both network structures and noise correlations by using available kinetic data only. This inference performance was never regarded possible by theoretical derivation, numerical computation and experimental design.Comment: 4 pages, 2 figure

Research on Solution Space of Bipartite Graph Vertex-Cover by Maximum Matchings

Some rigorous results and statistics of the solution space of Vertex-Covers on bipartite graphs are given in this paper. Based on the $K\ddot{o}nig$'s theorem, an exact solution space expression algorithm is proposed and statistical analysis of the nodes' states is provided. The statistical results fit well with the algorithmic results until the emergence of the unfrozen core, which makes the fluctuation of statistical quantities and causes the replica symmetric breaking in the solutions. Besides, the entropy of bipartite Vertex-Cover solutions is calculated with the clustering entropy using a cycle simplification technique for the unfrozen core. Furthermore, as generalization of bipartite graphs, bipartite core graph is proposed, the solution space of which can also be easily determined; and based on these results, how to generate a $K\ddot{o}nig-Egerv\acute{a}ry$ subgraph is studied by a growth process of adding edges. The investigation of solution space of bipartite graph Vertex-Cover provides intensive understanding and some insights on the solution space complexity, and will produce benefit for finding maximal $K\ddot{o}nig-Egerv\acute{a}ry$ subgraphs, solving general graph Vertex-Cover and recognizing the intrinsic hardness of NP-complete problems.Comment: 19 pages, 8 figure

Towards Conversational Recommendation over Multi-Type Dialogs

We propose a new task of conversational recommendation over multi-type dialogs, where the bots can proactively and naturally lead a conversation from a non-recommendation dialog (e.g., QA) to a recommendation dialog, taking into account user's interests and feedback. To facilitate the study of this task, we create a human-to-human Chinese dialog dataset \emph{DuRecDial} (about 10k dialogs, 156k utterances), which contains multiple sequential dialogs for every pair of a recommendation seeker (user) and a recommender (bot). In each dialog, the recommender proactively leads a multi-type dialog to approach recommendation targets and then makes multiple recommendations with rich interaction behavior. This dataset allows us to systematically investigate different parts of the overall problem, e.g., how to naturally lead a dialog, how to interact with users for recommendation. Finally we establish baseline results on DuRecDial for future studies. Dataset and codes are publicly available at https://github.com/PaddlePaddle/models/tree/develop/PaddleNLP/Research/ACL2020-DuRecDial.Comment: Accepted by ACL 202

Attention-based Temporal Weighted Convolutional Neural Network for Action Recognition

Research in human action recognition has accelerated significantly since the introduction of powerful machine learning tools such as Convolutional Neural Networks (CNNs). However, effective and efficient methods for incorporation of temporal information into CNNs are still being actively explored in the recent literature. Motivated by the popular recurrent attention models in the research area of natural language processing, we propose the Attention-based Temporal Weighted CNN (ATW), which embeds a visual attention model into a temporal weighted multi-stream CNN. This attention model is simply implemented as temporal weighting yet it effectively boosts the recognition performance of video representations. Besides, each stream in the proposed ATW framework is capable of end-to-end training, with both network parameters and temporal weights optimized by stochastic gradient descent (SGD) with backpropagation. Our experiments show that the proposed attention mechanism contributes substantially to the performance gains with the more discriminative snippets by focusing on more relevant video segments.Comment: 14th International Conference on Artificial Intelligence Applications and Innovations (AIAI 2018), May 25-27, 2018, Rhodes, Greec