The problem of noncooperative resource allocation in multicell uplink orthogonal frequency division multiple access (OFDMA) systems is considered in this paper. Noncooperative games for subcarrier allocation and transmit power control are considered, aiming at maximizing the users’ SINRs and, most notably, the users’ energy efficiency, measured in bit/Joule and representing the number of error-free delivered bits for each Joule of energy used for transmission. The theory of potential games is used to come up with several noncooperative games admitting Nash equilibrium points. Since the proposed resource allocation games exhibit a computational complexity that may be in some cases prohibitive, approximate, reduced-complexity, implementations are also considered. For comparison purposes, some considerations on social-optimum solutions are also discussed. Numerical results confirm that the proposed resource allocation schemes are effective in increasing the network energy efficiency (as compared to rate-maximizing schemes), thus permitting to optimize the use of the energy stored in the battery. Moreover, the proposed approximate implementations exhibit a performance very close to that of the exact procedures.

Potential games for energy-efficient power control and subcarrier allocation in uplink multicell OFDMA systems

BUZZI, Stefano;ZAPPONE, Alessio
2012

Abstract

The problem of noncooperative resource allocation in multicell uplink orthogonal frequency division multiple access (OFDMA) systems is considered in this paper. Noncooperative games for subcarrier allocation and transmit power control are considered, aiming at maximizing the users’ SINRs and, most notably, the users’ energy efficiency, measured in bit/Joule and representing the number of error-free delivered bits for each Joule of energy used for transmission. The theory of potential games is used to come up with several noncooperative games admitting Nash equilibrium points. Since the proposed resource allocation games exhibit a computational complexity that may be in some cases prohibitive, approximate, reduced-complexity, implementations are also considered. For comparison purposes, some considerations on social-optimum solutions are also discussed. Numerical results confirm that the proposed resource allocation schemes are effective in increasing the network energy efficiency (as compared to rate-maximizing schemes), thus permitting to optimize the use of the energy stored in the battery. Moreover, the proposed approximate implementations exhibit a performance very close to that of the exact procedures.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11580/20988
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