Bibliografías temáticas / Multi-sender index coding problem

Literatura académica sobre el tema "Multi-sender index coding problem"

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Publicado: 6 de septiembre de 2023

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Artículos de revistas sobre el tema "Multi-sender index coding problem"

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Ong, Lawrence, Chin Keong Ho y Fabian Lim. "The Single-Uniprior Index-Coding Problem: The Single-Sender Case and the Multi-Sender Extension". IEEE Transactions on Information Theory 62, n.º 6 (junio de 2016): 3165–82. http://dx.doi.org/10.1109/tit.2016.2555950.

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Thapa, Chandra, Lawrence Ong, Sarah Johnson y Min Li. "Structural Characteristics of Two-Sender Index Coding". Entropy 21, n.º 6 (21 de junio de 2019): 615. http://dx.doi.org/10.3390/e21060615.

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This paper studies index coding with two senders. In this setup, source messages are distributed among the senders possibly with common messages. In addition, there are multiple receivers, with each receiver having some messages a priori, known as side-information, and requesting one unique message such that each message is requested by only one receiver. Index coding in this setup is called two-sender unicast index coding (TSUIC). The main goal is to find the shortest aggregate normalized codelength, which is expressed as the optimal broadcast rate. In this work, firstly, for a given TSUIC problem, we form three independent sub-problems each consisting of the only subset of the messages, based on whether the messages are available only in one of the senders or in both senders. Then, we express the optimal broadcast rate of the TSUIC problem as a function of the optimal broadcast rates of those independent sub-problems. In this way, we discover the structural characteristics of TSUIC. For the proofs of our results, we utilize confusion graphs and coding techniques used in single-sender index coding. To adapt the confusion graph technique in TSUIC, we introduce a new graph-coloring approach that is different from the normal graph coloring, which we call two-sender graph coloring, and propose a way of grouping the vertices to analyze the number of colors used. We further determine a class of TSUIC instances where a certain type of side-information can be removed without affecting their optimal broadcast rates. Finally, we generalize the results of a class of TSUIC problems to multiple senders.
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3

Reddy, Kota Srinivas y Nikhil Karamchandani. "Structured Index Coding Problem and Multi-Access Coded Caching". IEEE Journal on Selected Areas in Information Theory 2, n.º 4 (diciembre de 2021): 1266–81. http://dx.doi.org/10.1109/jsait.2021.3126663.

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Thomas, Anoop y Balaji Sundar Rajan. "Generalized Index Coding Problem and Discrete Polymatroids". Entropy 22, n.º 6 (10 de junio de 2020): 646. http://dx.doi.org/10.3390/e22060646.

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The connections between index coding and matroid theory have been well studied in the recent past. Index coding solutions were first connected to multi linear representation of matroids. For vector linear index codes, discrete polymatroids, which can be viewed as a generalization of the matroids, were used. The index coding problem has been generalized recently to accommodate receivers that demand functions of messages and possess functions of messages. In this work we explore the connections between generalized index coding and discrete polymatroids. The conditions that need to be satisfied by a representable discrete polymatroid for a generalized index coding problem to have a vector linear solution is established. From a discrete polymatroid, an index coding problem with coded side information is constructed and it is shown that if the index coding problem has a certain optimal length solution then the discrete polymatroid is representable. If the generalized index coding problem is constructed from a matroid, it is shown that the index coding problem has a binary scalar linear solution of optimal length if and only if the matroid is binary representable.
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5

Arunachala, Chinmayananda, Vaneet Aggarwal y B. Sundar Rajan. "On the Optimal Broadcast Rate of the Two-Sender Unicast Index Coding Problem With Fully-Participated Interactions". IEEE Transactions on Communications 67, n.º 12 (diciembre de 2019): 8612–23. http://dx.doi.org/10.1109/tcomm.2019.2941470.

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Zhu, Yongjia, Yuyao He, Ye Fan y Rugui Yao. "Protection scheme of subcarrier index in OFDM with index modulation aided by LDPC coding". Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 39, n.º 4 (agosto de 2021): 818–23. http://dx.doi.org/10.1051/jnwpu/20213940818.

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The receiver of OFDM with Index Modulation (OFDM-IM) usually adopts a Log Likelihood Ratio (LLR) detection algorithm based on the activation state of subcarriers. However, the LLR detection algorithm will cause detection errors in subcarrier activation pattern (SAP) or get illegal SAP. Consequently, further errors occur in demodulation, increasing the bit error rate (BER). To solve this problem, we propose the protection scheme of subcarrier index aided by LDPC coding, which reduces the SAP detection errors by encoding the index information bits. On the receiver, the LDPC Coding Aided (LA) detection algorithm is designed, and the formula of LLR of index information bits is derived in detail. Monte Carlo simulation is carried out over multi-path fading channel by MATLAB software. The results show that under the condition that the spectrum efficiency is not lower than the classical OFDM-IM scheme, the proposed protection scheme can obtain a gain of about 5~9 dB when the BER is 10-4, effectively improving the BER performance of OFDM-IM scheme.
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7

Li, Min, Lawrence Ong y Sarah J. Johnson. "Cooperative Multi-Sender Index Coding". IEEE Transactions on Information Theory 65, n.º 3 (marzo de 2019): 1725–39. http://dx.doi.org/10.1109/tit.2018.2869161.

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Krishnan, Prasad, Lakshmi Natarajan y V. Lalitha. "An Umbrella Converse for Data Exchange: Applied to Caching, Computing, and Shuffling". Entropy 23, n.º 8 (30 de julio de 2021): 985. http://dx.doi.org/10.3390/e23080985.

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The problem of data exchange between multiple nodes with storage and communication capabilities models several current multi-user communication problems like Coded Caching, Data Shuffling, Coded Computing, etc. The goal in such problems is to design communication schemes which accomplish the desired data exchange between the nodes with the optimal (minimum) amount of communication load. In this work, we present a converse to such a general data exchange problem. The expression of the converse depends only on the number of bits to be moved between different subsets of nodes, and does not assume anything further specific about the parameters in the problem. Specific problem formulations, such as those in Coded Caching, Coded Data Shuffling, and Coded Distributed Computing, can be seen as instances of this generic data exchange problem. Applying our generic converse, we can efficiently recover known important converses in these formulations. Further, for a generic coded caching problem with heterogeneous cache sizes at the clients with or without a central server, we obtain a new general converse, which subsumes some existing results. Finally we relate a “centralized” version of our bound to the known generalized independence number bound in index coding and discuss our bound’s tightness in this context.
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9

Wu, Gongxing, Yuchao Li, Chunmeng Jiang, Chao Wang, Jiamin Guo y Rui Cheng. "MULTI-VESSELS COLLISION AVOIDANCE STRATEGY FOR AUTONOMOUS SURFACE VEHICLES BASED ON GENETIC ALGORITHM IN CONGESTED PORT ENVIRONMENT". Brodogradnja 73, n.º 3 (1 de julio de 2022): 69–91. http://dx.doi.org/10.21278/brod73305.

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An improved genetic collision avoidance algorithm is proposed in this study to address the problem that Autonomous Surface Vehicles (ASV) need to comply with the collision avoidance rules at sea in congested sea areas. Firstly, a collision risk index model for ASV safe encounters is established taking into account the international rules for collision avoidance. The ASV collision risk index and the distance of safe encounters are taken as boundary values of the correlation membership function of the collision risk index model to calculate the optimal heading of ASV in real-time. Secondly, the genetic coding, fitness function, and basic parameters of the genetic algorithm are designed to construct the collision avoidance decision system. Finally, the simulation of collision avoidance between ASV and several obstacle vessels is performed, including the simulation of three collision avoidance states head-on situation, crossing situation, and overtaking situation. The results show that the proposed intelligent genetic algorithm considering the rules of collision avoidance at sea can effectively avoid multiple other vessels in different situations.
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10

Ghaffari, Fatemeh, Seyed Pooya Shariatpanahi, Mahdi Jafari Siavoshani y Behnam Bahrak. "Multi-Sender Index Coding Over Linear Networks". IEEE Communications Letters 26, n.º 2 (febrero de 2022): 273–76. http://dx.doi.org/10.1109/lcomm.2021.3132988.

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Actas de conferencias sobre el tema "Multi-sender index coding problem"

1

Ong, Lawrence, Fabian Lim y Chin Keong Ho. "The multi-sender multicast index coding". En 2013 IEEE International Symposium on Information Theory (ISIT). IEEE, 2013. http://dx.doi.org/10.1109/isit.2013.6620406.

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Li, Min, Lawrence Ong y Sarah J. Johnson. "Improved bounds for multi-sender index coding". En 2017 IEEE International Symposium on Information Theory (ISIT). IEEE, 2017. http://dx.doi.org/10.1109/isit.2017.8007092.

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Chinmayananda, A. y B. Sundar Rajan. "Optimal Scalar Linear Index Codes for Some Two-Sender Unicast Index Coding Problems". En 2018 International Symposium on Information Theory and Its Applications (ISITA). IEEE, 2018. http://dx.doi.org/10.23919/isita.2018.8664234.

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Arunachala, Chinmayananda, Vaneet Aggarwal y B. Sundar Rajan. "Optimal Broadcast Rate of a Class of Two-Sender Unicast Index Coding Problems". En 2019 IEEE Information Theory Workshop (ITW). IEEE, 2019. http://dx.doi.org/10.1109/itw44776.2019.8989283.

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Reddy, Kota Srinivas y Nikhil Karamchandani. "Structured Index Coding Problems and Multi-access Coded Caching". En 2020 IEEE Information Theory Workshop (ITW). IEEE, 2021. http://dx.doi.org/10.1109/itw46852.2021.9457671.

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