Dynamic spectrum access (DSA) is a paradigm proposed by the Federal Communications
Commission aiming at efficient management of the available wireless network
resources. The present thesis deals with resource allocation in cooperative DSA networks.
Two models are considered: (a) open sharing networks (spectrum commons),
possibly deployed over unlicensed bands; and (b) networks with primary users, and secondary
users who access the spectrum upon paying a fee to the primary. In both types
of DSA networks, collaborating terminals adhere to diverse (maximum and minimum)
quality-of-service (QoS) constraints in order to effect hierarchies between primary and
secondary users or to prevent abusive utilization of the available spectrum in an open
sharing model. The focus is on peer-to-peer networks with co-channel interference in
both single- and multi-channel settings. Utilities that are functions of the signal-tointerference-
plus-noise-ratio (SINR) are employed as QoS metrics. By adjusting their
transmit power, users can mitigate the generated interference and also meet the QoS requirements.
A novel formulation accounting for heterogeneous QoS requirements as well
as maximum interference constraints is obtained after introducing a suitable relaxation
and recasting a constrained sum-utility maximization as a convex optimization problem.
The optimality of the relaxation is established under general conditions. Based on
this relaxation, an algorithm for optimal power control that is amenable to distributed
implementation is developed, and its convergence is established. The algorithm relies
on gradient-based iterations to find saddle points of the Lagrangian function associated
with the constrained convex optimization problem. In the context of power control,
errors may be introduced in the gradient vectors as a result of the distributed implementation
of the algorithm. The effects of these errors are studied in a general setting.
To this end, two running averages (ergodic sequences) of the iterates generated by the
algorithm are formed, each with complementary strengths. Under the main assumptions
of problem convexity and error boundedness, bounds on the constraint violation and
the suboptimality per iteration index are derived. Numerical tests verify the analytical
claims and demonstrate performance gains relative to existing schemes.
University of Minnesota M.S. thesis. July 2010. Major: Electrical Engineering. Advisor: Georgios B. Giannakis. 1 computer file (PDF) v, 78 pages, appendix A.
Utility-based power control for cooperative dynamic spectrum access networks..
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