We formulate throughput maximizing, max-min fair, weighted max-min fair, and proportionally fair scheduling problems for cognitive radio networks managed by a centralized cognitive base station. We propose a very general scheduling model accomplishing goals such as making frequency, time slot, and data rate allocation to secondary users with possibly multiple antennas, in a heterogenous multi-channel and multi-user scenario. Moreover, our schedulers ensure that reliable communication between the cognitive base station and secondary users are maintained, no collisions occur among secondary users, and primary users in the service area of the cognitive base station are not disturbed. Two distinctive features of our fair schedulers are that they provide joint temporal and throughput fairness, and take throughput values experienced by secondary users in the recent past, referred to as window size, into account and use this information in the current scheduling decision. We also propose a heuristic algorithm for our fair schedulers and demonstrate through simulations that our proposed heuristic yields very close solutions to the values obtained from the optimization softwares. Furthermore, we make extensive simulations to evaluate our schedulers' performance in terms of both total throughput and fairness for varying number of secondary users, frequencies, antennas, and window size.
The work in @cite_22 , for instance, concentrated on the spectrum overlay paradigm by modeling the interference as a multi-channel contention graph (MCCG). Authors in @cite_19 proposed a spectrum decision framework for centralized CRNs by considering application requirements and current spectrum conditions. Unlike our work, the work in @cite_8 focused on inter-cell spectrum sharing and proposed a joint spectrum and power allocation framework. Both @cite_19 and @cite_8 are based on the spectrum overlay paradigm since they handle spectrum availabilities as a binary decision, i.e., a spectrum band is either available or not. Our work is distinct in principle from all works in the literature about overlay spectrum sharing because we take into account the maximum allowed interference power at PUs.
@cite_19 @cite_22 @cite_8
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Cognitive radio (CR) networking achieves high utilization of the scarce spectrum resources without causing any performance degradation to the licensed users. Since the spectrum availability varies over time and space, the infrastructure-based CR networks are required to have a dynamic inter-cell spectrum sharing capability. This allows fair resource allocation as well as capacity maximization and avoids the starvation problems seen in the classical spectrum sharing approaches. In this paper, a joint spectrum and power allocation framework is proposed that addresses these concerns by (i) opportunistically negotiating additional spectrum based on the licensed user activity (exclusive allocation), and (ii) having a share of reserved spectrum for each cell (common use sharing). Our algorithm accounts for the maximum cell capacity, minimizes the interference caused to neighboring cells, and protects the licensed users through a sophisticated power allocation method. Simulation results reveal that the proposed inter-cell spectrum sharing framework achieves better fairness and higher network capacity than the conventional spectrum sharing methods. In this paper, we investigate a joint scheduling and power control for an infrastructure-based cognitive radio network (CRN) in coexistence with a cellular primary radio network (PRN). The PRN uses a set of licensed nonoverlapping orthogonal frequency channels for transmission. This set of channels is also accessed in an opportunistic manner by a set of cognitive radio base stations (CR-BSs) to support secondary users (SUs). The problem is formulated to maximize the spectrum utilization of SUs without causing excessive interference to active primary users (PUs) of the PRN. In addition, all the serviced SUs must meet a certain Quality of Service (QoS), such as satisfying a predefined signal to interference noise ratio (SINR). A centralized solution for joint scheduling and power control is derived to make the global accessing decision for all unserved SUs. With the assumption that the knowledge of all subscribers is available, a coordinator of the CRN can use the joint scheduling and power control algorithm to maximize the spectrum utilization of serviced SUs by solving a mixed-integer linear programming (MILP) with an NP-hard complexity. To avoid the NP-hard complexity, we propose a suboptimal heuristic greedy algorithm that can be obtained at a much lower complexity based on the coloring interference graph among unserved SUs effected by serviced SUs and active PUs. Its superior performance over the existing algorithms is demonstrated through simulations. In this paper, we study resource allocation for a multicarrier-based cognitive radio (CR) network. More specifically, we investigate the problem of secondary users’ energy-efficiency (EE) maximization problem under secondary total power and primary interference constraints. First, assuming cooperation among the secondary base stations (BSs), a centralized approach is considered to solve the EE optimization problem for the CR network where the primary and secondary users are using either orthogonal frequency-division multiplexing (OFDM) or filter bank based multicarrier (FBMC) modulations. We propose an alternating-based approach to solve the joint power-subcarrier allocation problem. More importantly, in the first place, subcarriers are allocated using a heuristic method for a given feasible power allocation. Then, we conservatively approximate the nonconvex power control problem and propose a joint successive convex approximation-Dinkelbach algorithm (SCADA) to efficiently obtain a solution to the nonconvex power control problem. The proposed algorithm is shown to converge to a solution that coincides with the stationary point of the original nonconvex power control subproblem. Moreover, we propose a dual decomposition-based decentralized version of the SCADA. Second, under the assumption of no cooperation among the secondary BSs, we propose a fully distributed power control algorithm from the perspective of game theory. The proposed algorithm is shown to converge to a Nash-equilibrium (NE) point. Moreover, we propose a sufficient condition that guarantees the uniqueness of the achieved NE. Extensive simulation analyses are further provided to highlight the advantages and demonstrate the efficiency of our proposed schemes. Motivated by the Federal Communications Commission's recent approval of commercial unlicensed operations of some television (TV) spectrum, we propose to integrate cognitive radios (CRs) that operate on unoccupied TV bands with an existing cellular network to increase bandwidth for mobile users. The existing cellular infrastructure is used to enable the operation of such CRs. Because base stations (BSs) can sense spectrum and exchange the sensed information for the reliable detection of primary users (PUs) and white spaces, we propose a collaborative sensing mechanism based on cell topology, where the BS declares its cell to be PU-free when neither the BS nor its neighboring BSs detect any PU. This way, in a PU-free cell, the following two types of channels are available: 1) channels that are originally licensed for the cellular system and 2) CR channels that are discovered through spectrum sensing. Because the CR channels that operate on TV bands usually suffer less path loss than the cellular channels, we derive two important results. First, each user gains more capacity when accessing a cellular channel than an empty TV channel, as long as intercell interferences are caused by the same sources. Second, assigning TV bands to cell-edge users is better in maximizing cell capacity. These two effects and the performance of the proposed sensing mechanism are verified through numerical evaluation.