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Joint Channel Identification and Estimation in Wireless Network: Sparsity and Optimization
Nguyen, Thang Van,Quek, Tony Q. S.,Shin, Hyundong IEEE 2018 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS Vol.17 No.5
<P>In this paper, we study channel identification for a wireless network with the aid of compressed sensing (CS) in both cases of known and unknown sparsity levels of clusters. For the unknown case, we propose using <I>blind</I> CS signal recovery algorithm to sequentially estimate both sparsity level and channel gains. The <I>refined</I> version of blind CS technique is also provided to improve the <I>consistency</I> of channel identification process. The <I>convergence</I> of two algorithms is guaranteed by ensuring that the cost functions decrease after each update. We then investigate the cluster sparsity of users in the case of known sparsity levels of all clusters. By exploiting the alternating direction method of multipliers algorithm through distributed optimization, we can identify channels in sparse clusters parallelly and efficiently compared with conventional convex techniques. In summary, this paper provides some insight into employing sparse and distributed algorithms to efficiently solve the problem of fast channel identification and estimation of users in future network.</P>
Content-Aware Proactive Caching for Backhaul Offloading in Cellular Network
Doan, Khai Nguyen,Van Nguyen, Thang,Quek, Tony Q. S.,Shin, Hyundong IEEE 2018 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS Vol.17 No.5
<P>Proactive caching is considered a cost-effective method to address the backhaul bottleneck problem in cellular network. In this paper, we propose a novel popularity predicting–caching procedure that takes raw video data as an input to determine an optimal cache placement policy, which deals with both published and unpublished videos. To anticipate the popularity of unpublished videos of which the statistical information is not available, we apply the content-based approach by extracting and condensing video features into a high-dimensional vector. Subsequently, we form <TEX>$G$</TEX> clusters of features representing the potential video categories (VCs) and map the feature vector into a <TEX>$G$</TEX>-dimensional space, where each element indicates the percentage to which the video contains the features of the corresponding VC. Finally, we train a prediction model to foresee the popularity, where the set of published videos is used as training data. Last, the prediction with expert advice method is used to update the training set, and to gain insight into how the predictor output will deviate from the best expert prediction, we address the concept of expected cumulative loss and derive the analytical expression for its upper bound. Extensive simulation results are shown to gain insight into our proposed system subject to different factors, such as network size, cache capacity, and user’s preference profile. In summary, we show that applying intelligence-based content-aware proactive caching is an efficient approach to significantly improving the operation of cellular networks in the future.</P>
N-Capping Effects of Stapled Heptapeptides on Antimicrobial and Hemolytic Activities
Thuy T. T. Dinh,김도희,Thang Q. Nguyen,이봉진,김영우 대한화학회 2015 Bulletin of the Korean Chemical Society Vol.36 No.10
In our previous study, we showcased the potential of an all-hydrocarbon stapled heptapeptide as a privileged scaffold for the design of artificial antimicrobial peptides. We demonstrated that the amphipathic helicity and the subtle balance between hydrophobicity and hydrophilicity are important structural features for the antimicrobial activities of this class of antimicrobial agents. In this study, we show that elimination of the N-acetyl cap can further improve the pharmacological properties of the most potent stapled heptapeptides. The structure–activity relationships newly established in this study would serve as a critical asset for the further development of a new class of antimicrobial agents to combat the rising problem of antibiotic resistance.