Efficient design of cognitive radios (CRs) calls for secondary users implementing adaptive resource allocation schemes that exploit knowledge of the channel state information (CSI), while at the same time limiting interference to the primary system. This paper introduces stochastic resource allocation algorithms for both interweave (also known as overlay) and underlay cognitive radio paradigms. The algorithms are designed to maximize the weighted sum-rate of orthogonally transmitting secondary users under average-power and probabilistic interference constraints. The latter are formulated either as short-or as long-term constraints, and guarantee that the probability of secondary transmissions interfering with primary receivers stays below a certain pre-specified level. When the resultant optimization problem is non-convex, it exhibits zero-duality gap and thus, due to a favorable structure in the dual domain, it can be solved efficiently. The optimal schemes leverage CSI of the primary and secondary networks, as well as the Lagrange multipliers associated with the constraints. Analysis and simulated tests confirm the merits of the novel algorithms in: i) accommodating time-varying settings through stochastic approximation iterations; and ii) coping with imperfect CSI.
Bibliographical noteFunding Information:
Manuscript submitted on 5 January 2012; revised 16 May 2012. The work in this paper was partially supported by the Spanish MCIN grant No. TEC2009-12098, the Spanish FPU grant No. AP2010-1050, and the QNRF grant NPRP 09-341-2-128. Parts of this paper were presented at IEEE ICASSP’11 and IEEE CAMSAP’11.
- Cognitive radios
- imperfect channel state information
- resource management
- stochastic approximation