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A Network-Assisted Game-Theoretic Design to Power Control in Autoregressive Fading Channels
Univ Fed Ceara, Wireless Telecom Res Grp GTEL, BR-60455760 Fortaleza, Ceara, Brazil..
Univ Fed Ceara, Wireless Telecom Res Grp GTEL, BR-60455760 Fortaleza, Ceara, Brazil..
KTH, Skolan för elektroteknik och datavetenskap (EECS), Intelligenta system, Reglerteknik. Ericsson Res, S-16480 Stockholm, Sweden..ORCID-id: 0000-0002-2289-3159
Univ Fed Ceara, Wireless Telecom Res Grp GTEL, BR-60455760 Fortaleza, Ceara, Brazil..
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2022 (Engelska)Ingår i: IEEE Communications Letters, ISSN 1089-7798, E-ISSN 1558-2558, Vol. 26, nr 7, s. 1663-1667Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Several previous works have proposed game-theoretic approaches to controlling the pilot and data power levels in the uplink of both single and multi-cell multi-user multiple input multiple output (MU-MIMO) systems. Unfortunately, the vast majority of existing works design these power control schemes under the assumption that the wireless channels between the mobile terminals and the serving base station are block fading. Meanwhile, several letters have shown that modeling fast fading channels as autoregressive (AR) processes with known or estimated state transition matrices give much more accurate results than those suggested by block fading models. Thus, this letter proposes a game-theoretic approach to controlling the uplink pilot and data power levels in a MU-MIMO system, in which the wireless channels are AR processes with mobile terminal-specific state transition matrices. We find that the proposed approach outperforms a classical cellular path-loss compensating fractional power control scheme and a game-theoretic power control scheme designed for block fading channels.

Ort, förlag, år, upplaga, sidor
Institute of Electrical and Electronics Engineers (IEEE) , 2022. Vol. 26, nr 7, s. 1663-1667
Nyckelord [en]
Power control, Fading channels, Channel estimation, Uplink, Symbols, Long Term Evolution, Wireless communication, MU-MIMO, game theory, autoregressive processes, nonconvex optimization
Nationell ämneskategori
Signalbehandling
Identifikatorer
URN: urn:nbn:se:kth:diva-316926DOI: 10.1109/LCOMM.2022.3167367ISI: 000838550100047Scopus ID: 2-s2.0-85128658104OAI: oai:DiVA.org:kth-316926DiVA, id: diva2:1693620
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QC 20220907

Tillgänglig från: 2022-09-07 Skapad: 2022-09-07 Senast uppdaterad: 2022-09-07Bibliografiskt granskad

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Fodor, Gabor

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