TY - JOUR
T1 - Energy-efficient resource allocation in wireless networks
AU - Meshkati, Farhad
AU - Poor, H. Vincent
AU - Schwartz, Stuart C.
N1 - Funding Information:
This research was supported by the National Science Foundation under Grant ANI-03-38807.
PY - 2007/5
Y1 - 2007/5
N2 - Game-theoretic approaches to radio resource allocation has the potential for wireless networks. In such an approach, the users' interaction in a wireless network can be modeled as a game in which the users' terminals are the players in the game competing for network resources such as bandwidth and energy. However, non-cooperation is the main feature that is being taken from game theory approach. In non-cooperation, depending on the situation, users are not limited to the choice of power, but can also choose their transmission rates, modulation schemes, packet sizes, multiuser receivers, multiantenna processing algorithms or carrier allocation strategies. Cross-layer resource allocation can be achieved by expanding the strategy sets of the users over multiple layers in the OCI protocol stack or by defining the users' utility functions such that performance measures across multiple layers are included. The utility function considered measures the number of reliable bits transmitted per joule of energy consumed and is particularly useful for energy-constrained networks. Game-theoretic framework is also very suitable for studying resource allocation in wireless ad hoc networks and wireless local area networks.
AB - Game-theoretic approaches to radio resource allocation has the potential for wireless networks. In such an approach, the users' interaction in a wireless network can be modeled as a game in which the users' terminals are the players in the game competing for network resources such as bandwidth and energy. However, non-cooperation is the main feature that is being taken from game theory approach. In non-cooperation, depending on the situation, users are not limited to the choice of power, but can also choose their transmission rates, modulation schemes, packet sizes, multiuser receivers, multiantenna processing algorithms or carrier allocation strategies. Cross-layer resource allocation can be achieved by expanding the strategy sets of the users over multiple layers in the OCI protocol stack or by defining the users' utility functions such that performance measures across multiple layers are included. The utility function considered measures the number of reliable bits transmitted per joule of energy consumed and is particularly useful for energy-constrained networks. Game-theoretic framework is also very suitable for studying resource allocation in wireless ad hoc networks and wireless local area networks.
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U2 - 10.1109/MSP.2007.361602
DO - 10.1109/MSP.2007.361602
M3 - Article
AN - SCOPUS:85032751549
SN - 1053-5888
VL - 24
SP - 58
EP - 68
JO - IEEE Signal Processing Magazine
JF - IEEE Signal Processing Magazine
IS - 3
ER -