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This document proposes a solution to improve the performance of TVWS sensing in cognitive spectrum access networks by employing distributed sensing and soft information fusion. The current 1-bit feedback approach is shown to be insufficient and may not satisfy regulatory requirements. The proposed solution introduces a new sensing measurement with flexible content and a container for measurement results, allowing for more accurate and reliable sensing.
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Sensing Support Comments Date: 2010-05-13 Authors: Notice:This document has been prepared to assist IEEE 802.19. It is offered as a basis for discussion and is not binding on the contributing individual(s) or organization(s). The material in this document is subject to change in form and content after further study. The contributor(s) reserve(s) the right to add, amend or withdraw material contained herein. Alex Reznik(InterDigital)
Abstract • Highlight a limitation in the current 802.11af draft • Extensive existing literature shows that this may have significant impact on eventual system performance • A simple approach to mitigate this issue is proposed Alex Reznik (InterDigital)
Problem Statement • TVWS sensing may be required to satisfy regulatory requirement • Distributed sensing is widely recognized and desirable for cognitive spectrum sensing • In the case of enabler/dependent(s) configuration, sensing fusion should occur at the enabling node and drive enabling beacons • Current proposal (802.11af/D0.02) calls for 1-bit feedback from dependents to the enabler • Re-use signaling introduces as part of 802.11h amendment • Unfortunately, 1-bit signaling is widely known to be insufficient • Limits the detection performance of the system • May significantly impact our ability to satisfy (as yet unclear) regulatory requirements Alex Reznik (InterDigital)
Distributed Sensing • Benefits of soft information in distributed sensing well known • Large body of work, well studied • Make intuitive sense • Examples of results here, longer list of references at the end • Current proposal limits us to 1-bit feedback • Main reason is the ability to re-use existing signaling • This leaves us at risk against future regulatory requirements • Precisely what this group is trying to avoid • It is not necessary • We can do much better while still re-using mechanisms already defined in 802.11 Source: Visotsky/Kuffner/ Peterson Source: Unnikrishnan/Veeravalli Alex Reznik (InterDigital)
Proposal • Add a new sensing measurement with flexible content • Provide sensing measurement report with a container for measurement results. • Container may be used for "soft" results for distributed sensing or for descriptive hard decision results. • Nature of sensing measurement • Not defined in the specification. • Could be implementation dependent • Designed to address specific regulatory needs • Operation of the enabler • The enabler would be required to do “information fusion” • How it is to do so is open to implementation • If result of fusion is that a channel is occupied, the enabling beacon for the channel is modified accordingly. Alex Reznik (InterDigital)
References • Used in the presentations • E. Visotsky, S. Kuffner, and R. Peterson, “On collaborative detection of TV transmissions in support of dynamic spectrum sharing,” in Proc. IEEE Int. Symposium on New Frontiers in Dynamic Spectrum Access Networks, Baltimore, Maryland, USA, Nov. 2005, pp. 338–345. • J. Unnikrishnan and V. Veeravalli, “Cooperative spectrum sensing and detection for cognitive radio,” GlobeCom 2007. • A few additional references on distributed sensing • E. Peh and Y.-C. Liang, “Optimization for cooperative sensing in cognitive radio networks,” in Proc. IEEE Wireless Commun. Networking Conf., Hong Kong, Mar. 2007, pp. 27–32. • F. Digham, M. Alouini, and M. Simon, “On the energy detection of unknown signals over fading channels,” in Proc. IEEE Int. Conf. Commun., vol. 5, Seattle, Washington, USA, pp. 3575–3579, May 2003. • Z. Chair and P. K. Varshney, “Optimal data fusion in multiple sensor detection systems,” IEEE Trans. Aerosp. Electron. Syst., vol. 22, no. 1, pp. 98–101, Jan. 1986. • J. Ma and Y. Li, “Soft combination and detection for cooperative spectrum sensing in cognitive radio networks,” in Proc. IEEE GLOBECOM 2007. • S. Mishra, A. Sahai, and R. Brodersen, “Cooperative sensing among cognitive radios,” in Proc. IEEE Int. Conf. Commun., vol. 2, Istanbul, Turkey, pp. 1658–1663, May 2006. • Q. Peng, K. Zeng, J. Wang and S. Li, “A distributed spectrum sensing scheme based on credibility and evidence theory in cognitive radio context,” in Proc. IEEE Int. Symposium on Personal, Indoor and Mobile Radio Commun., Helsinki, Finland, Sept. 2006, pp. 1–5. • X. Zheng, L. Cui, J. Chen Q. Wu and J. Wang, “Cooperative spectrum sensing in cognitive radio systems,” IEEE Congress on Image and Signal Processing, 2008. • Z. Tang, K. Pattipati and D. Kleinman, “An algorithm for determining the decision threshold in a distributed detection problem,” IEEE Trans. Syst. Sci. Cybern, vol. 21, pp. 231-237, Jan./Feb. 1991. • R. Viswanathan and P. K Varshney, “Distributed detection with multiple sensors: Part I: Fundamentals,” Proceedings of IEEE, vol. 85, pp. 54-63, Jan. 1997. • J. Meng, W. Yin, H. Li, E. Houssain and Z. Han, “Collaborative spectrum sensing from sparse observations using matrix completion for cognitive radio networks,” arXiv: 1001.2038v1. cs.IT, Jan. 2010. Alex Reznik (InterDigital)
