Cognitive Radio Networking

INTRODUCTION:

The main objective of cognitive radio networking is to develop radios that can sense the existing spectrum and identify and use free frequency bands. The motivation for these radios comes from the apparent scarcity of spectrum as indicated by the multiple allocation of most bands by the FCC. On the other hand, studies by the FCC show that 70% of the allocated spectrum is not utilized. This discrepancy between allocation and use provides the motivation for opportunistic use of the spectrum.

We aim to address the technology issues that are needed for the deployment of intelligent radios. Fig.1 shows the spectrum allocation chart for the United States which resembles a patch work quilt. It is worthy to note that frequencies between 1 and 5GHz have been allocated multiple times.

RESEARCH:

Spectrum sensing and Spectrum management are key issues in cognitive networking. Specific to these two issues, our research areas are Opportunistic Spectrum Access and Robust Distributed Spectrum Sensing.

OPPURTUNISTIC SPECTRUM ACCESS:

With the advent of cognitive radio technology, opportunistic spectrum access has the potential to mitigate spectrum scarcity and meet the increasing demand for spectrum.We address the problem of how multiple secondary users achieve maximal throughput in an opportunistic spectrum access (OSA) network. The secondary users adopt a slotted transmission scheme to exploit spectrum opportunities in a multi-channel unslotted primary network. We develop a non-cooperative based OSA approach: learning-based approach. In this approach, collisions among secondary users are taken into consideration while making channel sensing decisions. Spectrum maps for secondary users are estimated based on occurrence of collisions. There is no exchange of spectrum maps among secondary users. Compared with the co-operative based OSA approaches, our learning-based approach has minimal communication overhead. Our approach allows the secondary users to achieve maximal throughput by seeking independent spectrum opportunities without exchanging any control information among secondary users. Numerical results show that the learning-based approach obtains near optimal performance in most of the scenarios.

DISTRIBUTED SPECTRUM SENSING:

We focus on an important security threat: spectrum sensing data falsification (SSDF) which poses a serious threat to distributed spectrum sensing in CR based networks. SSDF threat is the transmission of false spectrum sensing data by malicious or unauthorized CRNs to a BS, causing the BS to make a wrong spectrum sensing decision. To address the threat of SSDF attacks we use a data fusion scheme: Weighted Bayesian Detection (WBD). WBD allows access to a CR network based on the reliability of CRN’s local spectrum sensing results. WBD improves the spectrum sensing decision of BS by detecting malfunctioning CRNs which send incorrect spectrum sensing results.

TESTBED:

A cognitive networking testbed based on COTS SDR has been developed. The Wireless Communications Networking lab at Old Dominion University has the following hardware components to implement a cognitive networking testbed.

•USRP Motherboard
•RFX900 -- 800-1000MHz Transceiver
•RFX1200 -- 1150 MHz - 1450 MHz Transceiver
•RFX1800 -- 1.5-2.1 GHz Transceiver
•RFX2400 -- 2.4-2.5 GHz Transceiver, 20+mW output
•Antennas

Test bed

We have studied the performance of a wireless test bed based on a specific SDR, the GNU Software Radio (GSR). We implemented a simple spectrum sensing application which can tune the transceiver to a range of frequencies in a dynamic fashion. We found that the GSR platform supports the programmer with a sophisticated SDR programming environment, resulting in low implementation cost. We are currently investigating an effective spectrum management scheme to be implemented on the testbed.

PUBLICATIONS:

Sachin Shetty, Min Song, Chunsheng Xin, "A Learning-based Multiuser Opportunistic Spectrum Access Approach in Unslotted Primary Networks", IEEE INFOCOM 2009.

Min Song, Sachin Shetty, Robert Ash , “Cognitive Networking for Spacecraft Wireless Communications" -- MIST project December 2007 report

LITERATURE:

1. F. Akyildiz, W. Y. Lee, M.C. Vuran and S. Mohanty, ``NeXt Generation / Dynamic Spectrum Access / Cognitive Radio Wireless Networks: A Survey," Computer Networks Journal (Elsevier), Vol. 50, pp. 2127-2159, September 2006.

2. FCC, ET Docket No 03-222 Notice of proposed rule making and order, December 2003.

3. DARPA XG WG, The XG Architectural Framework V1.0,2003.

4. BDARPA XG WG, The XG Vision RFC V1.0, 2003.

5. I.F. Akyildiz, Y. Altunbasak, F. Fekri, R. Sivakumar, AdaptNet: adaptive protocol suite for next generation wireless internet, IEEE Communications Magazine (2004).

6. “GNU Radio – GNU FSF project,” Retrieved Feb. 2, 2006 from http://gnuradio.org/trac/

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