TY - JOUR
T1 - Game theory in signal processing and communications [From the Guest Editors]
AU - Jorswieck, Eduard A.
AU - Larsson, Erik G.
AU - Luise, Marco
AU - Poor, H. Vincent
N1 - Funding Information:
This research is funded by NIH R01LM08696, R01LM009161, and R01AG028928.
PY - 2009
Y1 - 2009
N2 - Game theory is a branch of mathematics aimed at the modeling and understanding of resource conflict problems. Essentially, the theory splits into two branches: noncooperative and cooperative game theory. The distinction between the two is whether or not the players in the game can make joint decisions regarding the choice of strategy. Noncooperative game theory is closely connected to minimax optimization and typically results in the study of various equilibria, most notably the Nash equilibrium. Cooperative game theory examines how strictly rational (selfish) actors can benefit from voluntary cooperation by reaching bargaining agreements. Another distinction is between static and dynamic game theory, where the latter can be viewed as a combination of game theory and optimal control. In general, the theory provides a structured approach to many important problems arising in signal processing and communications, notably resource allocation and robust transceiver optimization. Recent applications also occur in other emerging fields, such as cognitive radio, spectrum sharing, and in multihop-sensor and adhoc networks.
AB - Game theory is a branch of mathematics aimed at the modeling and understanding of resource conflict problems. Essentially, the theory splits into two branches: noncooperative and cooperative game theory. The distinction between the two is whether or not the players in the game can make joint decisions regarding the choice of strategy. Noncooperative game theory is closely connected to minimax optimization and typically results in the study of various equilibria, most notably the Nash equilibrium. Cooperative game theory examines how strictly rational (selfish) actors can benefit from voluntary cooperation by reaching bargaining agreements. Another distinction is between static and dynamic game theory, where the latter can be viewed as a combination of game theory and optimal control. In general, the theory provides a structured approach to many important problems arising in signal processing and communications, notably resource allocation and robust transceiver optimization. Recent applications also occur in other emerging fields, such as cognitive radio, spectrum sharing, and in multihop-sensor and adhoc networks.
KW - Game theory
KW - Special issues and sections
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U2 - 10.1109/MSP.2009.933610
DO - 10.1109/MSP.2009.933610
M3 - Editorial
AN - SCOPUS:85032752175
SN - 1053-5888
VL - 26
SP - 17+132
JO - IEEE Signal Processing Magazine
JF - IEEE Signal Processing Magazine
IS - 5
ER -