FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4285289110> ?p ?o ?g. }

• W4285289110 endingPage "9201" @default.
• W4285289110 startingPage "9186" @default.
• W4285289110 abstract "The efficiency of link adaptation in wireless communications relies greatly on the accuracy of channel knowledge and transmission mode selection. In this paper, a novel deep learning based link adaptation framework is proposed for the orthogonal frequency-division multiplexing (OFDM) systems with compressed-sensing-assisted index modulation, termed as OFDM-CSIM, communicating over millimeter-wave (mmWave) channels. To achieve link adaptation, a novel multi-layer sparse Bayesian learning (SBL) algorithm is proposed for accurately and instantaneously providing the required channel state information. Meanwhile, a deep neural networks (DNN)-assisted adaptive modulation algorithm is proposed to choose the best possible transmission mode to maximize the achievable throughput. Simulation results show that the proposed multi-layer SBL algorithm enables more accurate channel estimation than the conventional techniques. The DNN-based adaptive modulator is capable of achieving a higher throughput than the learning-assisted solution based on the <inline-formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink><tex-math notation=LaTeX>$k$</tex-math></inline-formula> nearest neighbor ( <inline-formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink><tex-math notation=LaTeX>$k$</tex-math></inline-formula> -NN) algorithm, and also the classic average signal-to-noise ratio (SNR)-based solutions. Moreover, analysis shows that both the multi-layer SBL algorithm and the DNN-assisted adaptive modulator achieve better performance than their respective conventional counterparts while at a significantly lower computational complexity cost." @default.
• W4285289110 created "2022-07-14" @default.
• W4285289110 creator A5016934590 @default.
• W4285289110 creator A5031108116 @default.
• W4285289110 creator A5041760318 @default.
• W4285289110 creator A5071395661 @default.
• W4285289110 creator A5076712082 @default.
• W4285289110 date "2022-09-01" @default.
• W4285289110 modified "2023-10-01" @default.
• W4285289110 title "Deep Learning Assisted Adaptive Index Modulation for mmWave Communications With Channel Estimation" @default.
• W4285289110 cites W1980469326 @default.
• W4285289110 cites W1984114931 @default.
• W4285289110 cites W2014933333 @default.
• W4285289110 cites W2033673467 @default.
• W4285289110 cites W2037995333 @default.
• W4285289110 cites W2053521124 @default.
• W4285289110 cites W2067605736 @default.
• W4285289110 cites W2068243911 @default.
• W4285289110 cites W2079114205 @default.
• W4285289110 cites W2085814144 @default.
• W4285289110 cites W2111953900 @default.
• W4285289110 cites W2116148865 @default.
• W4285289110 cites W2123686838 @default.
• W4285289110 cites W2126073021 @default.
• W4285289110 cites W2127271355 @default.
• W4285289110 cites W2153603787 @default.
• W4285289110 cites W2161200040 @default.
• W4285289110 cites W2166670884 @default.
• W4285289110 cites W2272804037 @default.
• W4285289110 cites W2339667469 @default.
• W4285289110 cites W2391003 @default.
• W4285289110 cites W2402526535 @default.
• W4285289110 cites W2527745928 @default.
• W4285289110 cites W2540924152 @default.
• W4285289110 cites W2559695533 @default.
• W4285289110 cites W2577986608 @default.
• W4285289110 cites W2596873572 @default.
• W4285289110 cites W2615872748 @default.
• W4285289110 cites W2626006124 @default.
• W4285289110 cites W2771579582 @default.
• W4285289110 cites W2778670052 @default.
• W4285289110 cites W2792937383 @default.
• W4285289110 cites W2887934609 @default.
• W4285289110 cites W2916254409 @default.
• W4285289110 cites W2950738210 @default.
• W4285289110 cites W2963206527 @default.
• W4285289110 cites W2963537617 @default.
• W4285289110 cites W2963666666 @default.
• W4285289110 cites W2964218543 @default.
• W4285289110 cites W3083335990 @default.
• W4285289110 cites W3119514563 @default.
• W4285289110 cites W3152290665 @default.
• W4285289110 cites W4249046241 @default.
• W4285289110 cites W4256217385 @default.
• W4285289110 cites W4320800818 @default.
• W4285289110 cites W2883246492 @default.
• W4285289110 doi "https://doi.org/10.1109/tvt.2022.3181825" @default.
• W4285289110 hasPublicationYear "2022" @default.
• W4285289110 type Work @default.
• W4285289110 citedByCount "2" @default.
• W4285289110 countsByYear W42852891102023 @default.
• W4285289110 crossrefType "journal-article" @default.
• W4285289110 hasAuthorship W4285289110A5016934590 @default.
• W4285289110 hasAuthorship W4285289110A5031108116 @default.
• W4285289110 hasAuthorship W4285289110A5041760318 @default.
• W4285289110 hasAuthorship W4285289110A5071395661 @default.
• W4285289110 hasAuthorship W4285289110A5076712082 @default.
• W4285289110 hasBestOaLocation W42852891102 @default.
• W4285289110 hasConcept C107038049 @default.
• W4285289110 hasConcept C11413529 @default.
• W4285289110 hasConcept C123079801 @default.
• W4285289110 hasConcept C127162648 @default.
• W4285289110 hasConcept C127413603 @default.
• W4285289110 hasConcept C138885662 @default.
• W4285289110 hasConcept C138916503 @default.
• W4285289110 hasConcept C148063708 @default.
• W4285289110 hasConcept C154945302 @default.
• W4285289110 hasConcept C157764524 @default.
• W4285289110 hasConcept C24326235 @default.
• W4285289110 hasConcept C40409654 @default.
• W4285289110 hasConcept C41008148 @default.
• W4285289110 hasConcept C555944384 @default.
• W4285289110 hasConcept C56296756 @default.
• W4285289110 hasConcept C761482 @default.
• W4285289110 hasConcept C76155785 @default.
• W4285289110 hasConcept C81978471 @default.
• W4285289110 hasConceptScore W4285289110C107038049 @default.
• W4285289110 hasConceptScore W4285289110C11413529 @default.
• W4285289110 hasConceptScore W4285289110C123079801 @default.
• W4285289110 hasConceptScore W4285289110C127162648 @default.
• W4285289110 hasConceptScore W4285289110C127413603 @default.
• W4285289110 hasConceptScore W4285289110C138885662 @default.
• W4285289110 hasConceptScore W4285289110C138916503 @default.
• W4285289110 hasConceptScore W4285289110C148063708 @default.
• W4285289110 hasConceptScore W4285289110C154945302 @default.
• W4285289110 hasConceptScore W4285289110C157764524 @default.
• W4285289110 hasConceptScore W4285289110C24326235 @default.
• W4285289110 hasConceptScore W4285289110C40409654 @default.

• next