System Utility Maximization With Interference Processing for Cognitive Radio Networks


In spectrum underlay cognitive radio networks, secondary users (SUs) are allowed to reuse the spectrum allotted to a primary system. The interference between SUs really carries info and will probably be exploited to improve the network performance through info-theoretic interference processing. During this paper, we style an optimal joint power and rate management algorithm that maximizes the secondary system utility subject to the interference temperature constraints of primary users primarily based on the capability-approaching interference processing scheme referred to as because the Han-Kobayashi theme. The optimal solution is tough to attain as a result of the optimization downside is generally non-convex. To form the optimization problem tractable, this paper first transforms the matter into a monotonic optimization drawback through exploiting its hidden monotonicity. We tend to then devise an effective algorithm to get the world optimal answer to the joint power and rate management problem in the Han-Kobayashi scheme. The key plan behind the proposed algorithm is to construct a sequence of shrinking polyblocks that approximate the higher boundary of the feasible region with increasing precision. Numerical results more show that the achieved utility of our scheme significantly outperforms the utility of conventional schemes which treat the interference between SUs because the noise.

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