Database-assisted Coordinator-based Spectrum ...

Database-assisted Coordinator-based Spectrum Mobility in Cognitive Radio Ad-hoc Networks Andr´e Puschmann, Shah Nawaz Khan, Mohamed A. Kalil, Andreas Mitschele-Thiel Integrated Communication Systems Group, Ilmenau University of Technology, Ilmenau, Germany Email: [andre.puschmann, shah-nawaz.khan, mohamed.abdrabou, mitsch]@tu-ilmenau.de

Abstract—In this paper, we present a prototype Cognitive Radio (CR) ad-hoc network exploiting available radio spectrum opportunities while ensuring primary user protection. We present a flexible link-layer protocol that consists of a channel-hoppingbased rendezvous component, a CSMA-based MAC protocol and a coordinator-based spectrum mobility block. We also show a prototype implementation of a database-driven knowledge aggregation component called Resource Map which assists the CR network in its channel selection process. The demonstration shows a video stream originating from one CR node destined to another over the Primary User (PU) radio spectrum band. The demonstration also shows a cognitive channel selection process (instead of random free channel selection) where the CR network quantifies the radio channels based on the observed PU activity and reduces the overall channel handover count. These features are observable through a visualization of the spectrum sensing and aggregation process. Index Terms—Cognitive radio, software defined radio, spectrum mobility, spectrum sensing, resource map

I. I NTRODUCTION Prototype implementation of new concepts on specific testbeds is a very important part of conducting research for observing and validating new ideas. Cognitive Radio (CR) adhoc networks lend themselves very well for such prototype implementations as most of the related concepts such as runtime link and physical layer adaptations, are relatively new and subject to research and validation. The core cognitive functionality in CR networks is generally assumed to reside in the lower layers of the communication protocol stack i.e. link layer and below. For example, identifying radio spectrum opportunities, exploiting those radio resources for secondary communication and ensuring primary user protections are some tasks that have to be robustly addressed at these lower layers. However, obtaining awareness of the external radio environment and its characteristics is equally important for CR networks efficient operation. Environment awareness can be obtained at higher layer entities such as a Resource Map which can aggregate the results of spectrum sensing over time and characterize the PU channels according to spectrum opportunities they provide. Related work on CR ad-hoc networks have generally addressed most of these issues and suggested possible solutions, yet the practical realization of these proposals is very limited. We can argue in favour of prototype implementation that they tend to prove or disprove the validity of such possible solutions and associated assumptions.

In this paper, we present a prototype implementation of CR ad-hoc network [1] that features a flexible link-layer protocol [2] that establishes autonomous communication links among its peers through a rendezvous process, allows to opportunistically access the channel for secondary communication and also protects the primary user (PU) communication through intelligent channel selection among a list of available options. A energy detection based spectrum sensing is implemented for identifying spectrum opportunities. Based on the results gathered through the sensing process, a database-driven resource map [3] component is implemented to characterize the available radio spectrum and to facilitate intelligent channel selection and mobility in the events of PU interruptions. During the demonstration, the audience will be able to observe how the network successfully reacts to the sudden appearance of the PU transmission with only a limited impact on the experienced quality of service. Furthermore, the conference attendees will also be able to control the PU activity and observe how the channel selection process is influenced by that through a graphical user interface. II. S ETUP The experiment consists of two CR nodes operating in the 5 GHz ISM band. Both nodes are running a prototype implementation of the architecture presented in [1]. The rendezvous, MAC and mobility components are implemented inside the reconfigurable SDR framework Iris [4]. The database-driven radio resource map only runs on the transmitting CR node i.e. CR1, which serves as a Master and is responsible for spectrum sensing. Each node is equipped with one USRP2 device which is used as a radio transceiver. The first CR is equipped with a second USRP2 device which is used for spectrum sensing only. The spectrum is divided into 3 adjacent channels with a bandwidth of 4 MHz each (5180+i · 4 MHz with i ∈ [0..2]). A third node acts as a PU broadcasting a pseudo-random OFDM signal and arbitrarily switching between one of the available channels. A sketch of the demonstration setup can be seen in figure 1. III. D EMONSTRATION F LOW In this section, a step-wise illustration of what the demonstration presents and how the conference attendees will be able to interact with it is given. The demonstration flow consists of five main phases:

PU USRP2

2m

SDR, FLL, RM

SDR, FLL

USRP2 CR 1

Video stream USRP2

CR 2 USRP2

2m

Fig. 2. Screenshot of the GUI of the radio resource map. The right figure displays the average availability per channel.

Fig. 1. Demonstration setup: Two CR nodes, one PU and a spectrum analyser

Discovery and connection phase: When the CR nodes are initially powered on, they immediately attempt to rendezvous with one another in one of the available channels through a randomly generated channel-hopping sequence. • Data transmission phase: Once the network connectivity is established through the rendezvous process, the first CR node attempts to transmit a video captured through a webcam to the second CR node over a free channel. • Spectrum sensing and data aggregation phase: This phase runs in parallel with the data transmission phase. Using the second radio front-end, the master CR node continuously scans through all available radio channels, determines the state of the channel and writes the results into the database. The sensing radio is able to differentiate between its own and PU communication and therefore, does not provide wrong data to the resource map about its operating channel. • Coordinator-based intelligent channel selection phase: Based on the results that are aggregated over time inside the database, a backup channel is proposed based on the average channel occupancy of all channels. The coordinator, i.e. the master CR node, embeds its backup channel decision into the data transmission flow and informs the second (i.e. slave) CR about the common backup channel. • PU interruption and channel mobility phase: In case the nodes detect an active PU on the current operating channel, the MAC immediately suspends any active transmission in order to protect the licensed user from harmful interference. Both nodes now tune their radios to the negotiated backup channel. After that, the MAC protocol resumes its ongoing communication. During the demonstration the conference attendees will be able to observe the channel occupancy in real-time on a spectrum analyser (see Figure 3) as well as on a graphical user interface that visualizes the spectrum aggregation inside the resource map. Figure 2 shows a screenshot of the resource map. Furthermore, the audience will also be able to control the operating channel of the PU. •

Fig. 3. Screenshot of the spectrum analyzer implemented in GNU Radio. The orange/red coloured PU randomly occupies a channel while the light blue CR system adapts its operating frequency accordingly.

ACKNOWLEDGMENT This work is being carried out within the scope of the International Graduate School on Mobile Communications (Mobicom) at Ilmenau University of Technology, supported by the German Research Foundation (GRK1487) and the Carl Zeiss Foundation, Germany. We would also like to thank Omran Saleh for his positive collaboration. R EFERENCES [1] A. Puschmann, S. N. Khan, A. Haider Mahdi, M. A. Kalil, and A. Mitschele-Thiel, “An Architecture for Cognitive Radio Ad-Hoc Network Nodes,” in 12th International Symposium on Communications and Information Technologies (ISCIT), Gold Coast, Australia, Oct. 2012. [2] A. Puschmann, M. A. Kalil, and A. Mitschele-Thiel, “A Componentbased Approach for Constructing Flexible Link-Layer Protocols,” in 8th International Conference on Cognitive Radio Oriented Wireless Networks (CROWNCOM), Washington D.C., USA, Jul. 2013. [3] S. N. Khan, M. A. Kalil, and A. Mitschele-Thiel, “Distributed spectrum map for cognitive radio ad hoc networks,” in Proc. of the 4th International Conference on Cognitive Radio and Advanced Spectrum Management (CogART), Barcelona, Spain, 2011. [4] P. D. Sutton, J. Lotze, H. Lahlou, S. A. Fahmy, K. E. Nolan, B. zgl, T. W. Rondeau, J. Noguera, and L. E. Doyle, “Iris: An Architecture for Cognitive Radio Networking Testbeds,” in IEEE Communications Magazine, vol. 48, no. 9, Sep. 2010, pp. 114–122.