Power control in cognitive radio networks: how to cross a multi-lane highway

With the rapid development of wireless communications technologies, radio spectrum has become a type of extremely scarce resources in meeting the increasing demands for broadband wireless services. However, the traditional static spectrum allocation policy leads to severe spectrum underutilization and spectrum shortage problems. The cognitive radio (CR) technology can detect the occupancy of the spectrum and enable the dynamic spectrum access (DSA) to fill the spectrum hole caused by the static allocation policy, and thus has been widely recognized as an efficient approach to solve the above problems. The distributed cognitive wireless network (CWN), which does not have central entities, is one of the major networking architectures applying the CR technology. Correspondingly, the design of DSA in distributed CWNs is crucial, yet challenging, to increasing the utilization efficiency of the wireless spectrum with dynamically-varying occupancy statuses. In this article, we present a survey on DSA protocols for distributed CWNs. In particular, we first address the challenges in the design and implementation of distributed DSA protocols. Then, we categorize the existing distributed DSA protocols based on different criteria, such as spectrum sharing modes, spectrum allocation behaviors, spectrum access modes, the usage of common control channel, spectrum usage strategies, the number of radios, and spectrum sensing techniques. We also discuss the advantages and disadvantages of each category under diverse classification criterion. Moreover, we make a comprehensive survey of the state-of-the-art distributed DSA protocols using different spectrum access modes, which can be categorized into contention-based, time-slotted, and hybrid protocols. Through the study, we find out that most of distributed DSA protocols fall into the contention-based and hybrid protocols. In addition, the ongoing standardization efforts are also reviewed. Finally, several open research issues for the distributed DSA protocols are presented, such as spectrum handoff based protocols, spectrum prediction based protocols, adaptation of the spectrum-sharing modes, protocols with cooperative spectrum sensing, as well as distributed collision avoidance mechanisms.

Section: Power Control Mechanismmentioning

confidence: 99%

A survey on dynamic spectrum access protocols for distributed cognitive wireless networks

Ren

Wang

et al. 2012

“…With this aim, the amount of power transmitted in these resources must be dynamically controlled by the non-licensed system. This philosophy is generally known in literature as power control (PC) [37].…”

Section: Resource Allocation For Interference Minimizationmentioning

confidence: 99%

Implementing opportunistic spectrum access in LTE-advanced

Osa

Herranz

Monserrat

et al. 2012

Long term evolution advanced (LTE-A) has emerged as a promising mobile broadband access technology aiming to cope with the increasing traffic demand in wireless networks. However, the enhanced spectral efficiency offered by LTE-A may become futile without a better management of scarce and overcrowded electromagnetic spectrum. In this sense, cognitive radio (CR) has been proposed as a potential solution to the problem of spectrum scarcity. Among all the mechanisms provided by CR, opportunistic spectrum access (OSA) aims at a dynamic and seamless use of certain licensed bands provided the licensee is not harmfully affected. This operation requires spectral awareness in order to avoid interferences with licensed systems. In spite of implementing some spectrum sensing mechanisms, LTE-A technology lacks other tools that are needed in order to improve the knowledge of the radio environment. This work studies the adoption of a Geo-located data base (Geo-DB) that cooperatively retrieves and maintains information regarding the location of unutilized portions of spectrum potentially available for OSA. Moreover, the potential benefit of this LTE-compliant OSA solution is evaluated using a calibrated simulation tool, by which numerical results allow us to optimally configure the system and show that the proposed opportunistic system is able to significantly improve its performance.

“…Inequality (11) indicates that the duration time slots from the CBS to SU i should be no larger than the delay of RT SUs d RT i . In (12), the packet length l RT i needs to be received by SU i within d RT i time slots, that is, Equation (12) is another form of (11). Equation (13) is the MAC-layer QoS constraint for NRT SUs, where, R j is the average rate of SU j from time Slot 1 to time slot T, and should be no smaller than R NRT j .…”

Section: Qos Constraints For Susmentioning

confidence: 99%

“…Then, the PBS broadcasts the interference limits on its occupied subbands and pilot signals for SU-to-PU interference channel estimation. According to the interference limits and geographic location of the CR system, a cognitive base station (CBS) decides available spectrum resources in the CR system and utilizes adaptive power control [12,13] to limit the SU-to-PU interference.…”

Section: Introductionmentioning

confidence: 99%

Joint cross-layer resource allocation and interference avoidance with QoS support for cognitive radio systems

Peng

Fujii

2012

In this article, we study the coexistence and optimization of a centralized orthogonal frequency-division multiple access-based multiuser cognitive radio (MCR) system which coexists with a cellular primary system (PS). Two different spectrum sharing methods, i.e., the spectrum underlay/overlay, are utilized for different coexistent frameworks, in which, the sharing method is adapted to one of them based on the distance between two base stations and the interference limit in the PS. We consider a PS-assistance-based coexistent architecture and propose a joint power control and interference management method to avoid unacceptable interference to primary users (PU). Firstly, the relationship between power limits at secondary users (SU) and interference margin at PUs can be obtained. Then, to provide the SUs with satisfactory quality of service (QoS), and optimize the sum rate of the MCR system as well, a constrained two-variable nonlinear optimization problem (OP) is formulated. We solve this OP by (i) simplifying the QoS constraints from medium access control-layer to physical-layer based on a crosslayer approximation; and (ii) using the Lagrangian duality based technique to solve the simplified OP, and iterative water-filling is implemented to find the optimal power and subcarrier allocation. Simulation results show that, compared to the conventional designs, our algorithm achieves significant higher throughput and can guarantee the required signal to interference plus noise ratio of the PUs and the QoS of the SUs well. Moreover, compared to the spectrum overlay sharing method, the spectrum underlay & overlay can provide substantial higher spectrum efficiency.