Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Nash Bargaining Game Theoretic Scheduling for Joint Channel and Power Allocation in Cognitive Radio Systems
AU - Ni, Qiang
AU - Zarakovitis, Charilaos C.
PY - 2012/1
Y1 - 2012/1
N2 - This paper proposes a new Nash bargaining solution (NBS) based cooperative game-theoretic scheduling framework for joint channel and power allocation in orthogonal frequency division multiple access cognitive radio (CR) systems. Our objectives are to maximize the overall throughput of the CR system with the protection of primary users' transmission, while guaranteeing each CR user's minimum rate requirement and the proportional fairness and efficient power distribution among CR users. Using time-sharing variable transformation, we introduce a novel method that involves Lambert-W function properties and obtain closed-form analytical solutions. A low-complexity algorithm is also developed which does not require iterative processes as usual to search the optimal solution numerically. Simulation results demonstrate that our optimal policies outperform the existing maximal rate, fixed assignment and max-min fairness, while achieving the 99.985% in average of the optimal capacity.
AB - This paper proposes a new Nash bargaining solution (NBS) based cooperative game-theoretic scheduling framework for joint channel and power allocation in orthogonal frequency division multiple access cognitive radio (CR) systems. Our objectives are to maximize the overall throughput of the CR system with the protection of primary users' transmission, while guaranteeing each CR user's minimum rate requirement and the proportional fairness and efficient power distribution among CR users. Using time-sharing variable transformation, we introduce a novel method that involves Lambert-W function properties and obtain closed-form analytical solutions. A low-complexity algorithm is also developed which does not require iterative processes as usual to search the optimal solution numerically. Simulation results demonstrate that our optimal policies outperform the existing maximal rate, fixed assignment and max-min fairness, while achieving the 99.985% in average of the optimal capacity.
UR - http://www.scopus.com/inward/record.url?scp=84855430904&partnerID=8YFLogxK
U2 - 10.1109/JSAC.2012.120107
DO - 10.1109/JSAC.2012.120107
M3 - Journal article
VL - 30
SP - 70
EP - 81
JO - IEEE Journal on Selected Areas in Communications
JF - IEEE Journal on Selected Areas in Communications
SN - 0733-8716
IS - 1
ER -