TY - GEN
T1 - Optimizing flow control in multi-interface wireless cognitive radio networks
AU - Louni, Alireza
AU - Subbalakshmi, K. P.
PY - 2013
Y1 - 2013
N2 - This paper solves the optimal flow management problem in cognitive radio (CR) networks with multiple self-interested CRs and multiple self interested servers with multiple radio interfaces. We formulate a novel flow management problem in which the cognitive nodes compete to minimize the total delay over all interfaces while at the same time the servers compete to maximize their individual profit. We model this problem as a leader-follower game and propose a dynamic linear pricing scheme designed to achieve optimal flow allocation. We propose an iterative algorithm to solve the game and analyze the criteria for convergence to the unique Nash Equilibrium. The messaging required to implement this algorithm is minimal thereby making it suitable for distributed implementations. Numerical simulations demonstrate significant improvement in terms of average total delay for cognitive nodes in comparison with alternative algorithms. Simulation results show that when quality of service in terms of average total delay is fixed, our algorithm improves the capacity of the network by 40% for the maximum allowable throughput demand.
AB - This paper solves the optimal flow management problem in cognitive radio (CR) networks with multiple self-interested CRs and multiple self interested servers with multiple radio interfaces. We formulate a novel flow management problem in which the cognitive nodes compete to minimize the total delay over all interfaces while at the same time the servers compete to maximize their individual profit. We model this problem as a leader-follower game and propose a dynamic linear pricing scheme designed to achieve optimal flow allocation. We propose an iterative algorithm to solve the game and analyze the criteria for convergence to the unique Nash Equilibrium. The messaging required to implement this algorithm is minimal thereby making it suitable for distributed implementations. Numerical simulations demonstrate significant improvement in terms of average total delay for cognitive nodes in comparison with alternative algorithms. Simulation results show that when quality of service in terms of average total delay is fixed, our algorithm improves the capacity of the network by 40% for the maximum allowable throughput demand.
UR - http://www.scopus.com/inward/record.url?scp=84904110418&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84904110418&partnerID=8YFLogxK
U2 - 10.1109/GLOCOM.2013.6831242
DO - 10.1109/GLOCOM.2013.6831242
M3 - Conference contribution
AN - SCOPUS:84904110418
SN - 9781479913534
SN - 9781479913534
T3 - Proceedings - IEEE Global Communications Conference, GLOBECOM
SP - 1227
EP - 1232
BT - 2013 IEEE Global Communications Conference, GLOBECOM 2013
T2 - 2013 IEEE Global Communications Conference, GLOBECOM 2013
Y2 - 9 December 2013 through 13 December 2013
ER -