Resource allocation for spectrum-leasing based CRN with delay-sensitive traffic

Abstract

In this paper, cooperative resource allocation strategies are characterized for a spectrum-leasing based cognitive radio network (CRN), where the primary system leases the licensed band to the secondary system for a fraction of time in exchange for the secondary user (SU) acting as relay. Here, both amplify-and-forward (AF) and decode-and-forward (DF) relay protocols are considered. Considering the delay-sensitive traffic in CRN, the proposed strategies ensure delay provisioning for both primary user (PU) and SU with multiple system design objectives. In particular, we propose a multi-objective optimization framework, which incorporates two important system design objectives: the average sum power minimization and the leased time minimization. By integrating information theory with the concept of effective capacity, the adopted multi-objective optimization problem is recast as a convex optimization one via employing weighting method and sequentially solved by applying the Lagrangian dual method. It is shown that the global optimal solution of the original problem is characterized by a Pareto set which provides a quantitative insight into the tradeoff between the transmit power and leased time. Moreover, to learn the statistics of the wireless channels on the fly, we also put forward a stochastic iterative algorithm to achieve the optimal power and time allocation by employing the stochastic optimization theory. Numerical results not only reveal the nontrivial tradeoff among the considered conflicting system design objectives but also demonstrate that the proposed strategies perform better in saving wireless resources than existing resource allocation policies for different Quality-of-Service (QoS) exponent sets, especially when the delay requirement is strict.

Spectrum Estimation and Optimal Secondary User Selection in Cognitive Radio Networks

“…However, quality of service was not focused. To address this issue, a multi-objective optimization framework that embodies two objectives, i.e., power minimization and the leased time minimization was proposed in [6]. This objective was achieved by employing convex optimization and by applying the Lagrangian dual method, therefore obtaining tradeoff between the transmit power and leased time.…”

“…Step 5: Estimate the skewness of the reference signal as in equation (6) Step 6: Estimate the most significant relevant dimension using Chebyshev distance as in Eq. (7) Step 7: Evaluate probability of detection, probability of missed detection and probability of false alarm as in Eqs.…”

Enhanced fuzzy C‐means clustering based cooperative spectrum sensing combined with multi‐objective resource allocation approach for delay‐aware CRNs

“…The problem of this method is complicated due to the fact that it involves totally two different types of optimisation variables with intricate constraint conditions. Yanbo Ma et al [18] characterised cooperative RA strategies for spectrum-leasing based CRN. In their work, for a small amount of time, the primary system leases the licensed band to the secondary system in return of SU act as a relay.…”

An Energy-Efficient Unselfish Spectrum Leasing Scheme for Cognitive Radio Networks

“…The branch selection and spectrum allocation are jointly optimized such that the sum-rate of the SUs is maximized. A multi-objective optimization framework to incorporate average sum power minimization and the leased time minimization is proposed in Reference [22]. In Reference [23], a cooperative sharing model for cognitive wireless powered networks is proposed, to accomplish PU's transmission early and vacate opportunity for SU's transmission.…”