Matches in SemOpenAlex for { <https://semopenalex.org/work/W3189586824> ?p ?o ?g. }
Showing items 1 to 93 of
93
with 100 items per page.
- W3189586824 endingPage "793" @default.
- W3189586824 startingPage "781" @default.
- W3189586824 abstract "In this paper, we design a deep learning based resource allocation framework, in the form of an auction, for simultaneous information and power transfer from a hybrid access point (AP) to information devices and energy harvesting devices, respectively. Using Myerson’s lemma and the concept of virtual welfare maximization, we develop an optimal dominant-strategy incentive-compatible mechanism for the AP to maximize its expected revenue, based on the devices’ bid profiles, valuation distributions, demand profiles, and channel state information. In so doing, we formulate the revenue maximization problem, which is a mixed-integer non-linear program, and propose an efficient Branch-and-Bound (BnB) algorithm to solve the problem using semidefinite relaxation technique in each branch. Since the problem has exponential time complexity, using BnB algorithms can be impractical for real-time applications. To circumvent this, a deep neural network (DNN) is proposed, and trained to predict the optimal mechanism for beamforming the data and the energy towards the information and energy devices, respectively. We use the BnB algorithm to solve the problem offline and populate the training dataset. The proposed DNN architecture is indeed a multi-layer perceptron, which is trained well to map the heterogeneous input to the desired output with high accuracy. Furthermore, we propose a heuristic iterative solution whose accuracy performance is comparable to that of the DNN-based solution. The heuristic solution has polynomial time complexity whereas the DNN-based solution has linear time complexity." @default.
- W3189586824 created "2021-08-16" @default.
- W3189586824 creator A5001604978 @default.
- W3189586824 creator A5082033372 @default.
- W3189586824 date "2022-02-01" @default.
- W3189586824 modified "2023-10-16" @default.
- W3189586824 title "Deep Learning Based Auction-Driven Beamforming for Wireless Information and Power Transfer" @default.
- W3189586824 cites W123338590 @default.
- W3189586824 cites W1549332294 @default.
- W3189586824 cites W1981499715 @default.
- W3189586824 cites W1990961611 @default.
- W3189586824 cites W1996215314 @default.
- W3189586824 cites W1997770298 @default.
- W3189586824 cites W1997834106 @default.
- W3189586824 cites W2009928248 @default.
- W3189586824 cites W2064036620 @default.
- W3189586824 cites W2111491350 @default.
- W3189586824 cites W2134901427 @default.
- W3189586824 cites W2137906183 @default.
- W3189586824 cites W2145486800 @default.
- W3189586824 cites W2161473225 @default.
- W3189586824 cites W2549354855 @default.
- W3189586824 cites W2764170017 @default.
- W3189586824 cites W2787468990 @default.
- W3189586824 cites W2794049616 @default.
- W3189586824 cites W2892092358 @default.
- W3189586824 cites W2896051417 @default.
- W3189586824 cites W2900568937 @default.
- W3189586824 cites W2963061380 @default.
- W3189586824 cites W2970475350 @default.
- W3189586824 cites W3100394505 @default.
- W3189586824 cites W3100619529 @default.
- W3189586824 cites W3112324757 @default.
- W3189586824 cites W3122429393 @default.
- W3189586824 cites W3131527684 @default.
- W3189586824 cites W3158651285 @default.
- W3189586824 doi "https://doi.org/10.1109/twc.2021.3099372" @default.
- W3189586824 hasPublicationYear "2022" @default.
- W3189586824 type Work @default.
- W3189586824 sameAs 3189586824 @default.
- W3189586824 citedByCount "2" @default.
- W3189586824 countsByYear W31895868242023 @default.
- W3189586824 crossrefType "journal-article" @default.
- W3189586824 hasAuthorship W3189586824A5001604978 @default.
- W3189586824 hasAuthorship W3189586824A5082033372 @default.
- W3189586824 hasBestOaLocation W31895868242 @default.
- W3189586824 hasConcept C11413529 @default.
- W3189586824 hasConcept C126255220 @default.
- W3189586824 hasConcept C144133560 @default.
- W3189586824 hasConcept C154945302 @default.
- W3189586824 hasConcept C159694833 @default.
- W3189586824 hasConcept C162853370 @default.
- W3189586824 hasConcept C173801870 @default.
- W3189586824 hasConcept C33923547 @default.
- W3189586824 hasConcept C41008148 @default.
- W3189586824 hasConcept C54197355 @default.
- W3189586824 hasConcept C76155785 @default.
- W3189586824 hasConcept C9233905 @default.
- W3189586824 hasConceptScore W3189586824C11413529 @default.
- W3189586824 hasConceptScore W3189586824C126255220 @default.
- W3189586824 hasConceptScore W3189586824C144133560 @default.
- W3189586824 hasConceptScore W3189586824C154945302 @default.
- W3189586824 hasConceptScore W3189586824C159694833 @default.
- W3189586824 hasConceptScore W3189586824C162853370 @default.
- W3189586824 hasConceptScore W3189586824C173801870 @default.
- W3189586824 hasConceptScore W3189586824C33923547 @default.
- W3189586824 hasConceptScore W3189586824C41008148 @default.
- W3189586824 hasConceptScore W3189586824C54197355 @default.
- W3189586824 hasConceptScore W3189586824C76155785 @default.
- W3189586824 hasConceptScore W3189586824C9233905 @default.
- W3189586824 hasFunder F4320334593 @default.
- W3189586824 hasIssue "2" @default.
- W3189586824 hasLocation W31895868241 @default.
- W3189586824 hasLocation W31895868242 @default.
- W3189586824 hasOpenAccess W3189586824 @default.
- W3189586824 hasPrimaryLocation W31895868241 @default.
- W3189586824 hasRelatedWork W2355326491 @default.
- W3189586824 hasRelatedWork W2355561715 @default.
- W3189586824 hasRelatedWork W2360290312 @default.
- W3189586824 hasRelatedWork W2360751371 @default.
- W3189586824 hasRelatedWork W2369836678 @default.
- W3189586824 hasRelatedWork W2373538886 @default.
- W3189586824 hasRelatedWork W2382224273 @default.
- W3189586824 hasRelatedWork W2387920521 @default.
- W3189586824 hasRelatedWork W2389286292 @default.
- W3189586824 hasRelatedWork W2389754756 @default.
- W3189586824 hasVolume "21" @default.
- W3189586824 isParatext "false" @default.
- W3189586824 isRetracted "false" @default.
- W3189586824 magId "3189586824" @default.
- W3189586824 workType "article" @default.