A Channel Portfolio Optimization Framework for Trading in a Spectrum Secondary Market

State-of-the-art spectrum auctions are designed under a primary market paradigm to conduct spectrum trading between legacy owners and large cognitive service providers. In our previous work, we established a spectrum secondary market based on double auctions, and showed that it significantly improves spectrum utilization and user performance by allowing secondary users to dynamically trade among themselves their channel holdings obtained in the primary market. In this paper, we devise a channel portfolio optimization framework in order for users to make intelligent trading decisions without burdensome overhead. By viewing each channel in the secondary market as a stock, users assess its characteristics, and derive which channels to buy or sell at what price and quantity as a portfolio optimization problem to maximize the expected utility. Coupled with the robust secondary market design, the channel portfolio optimization framework offers salient performance with low complexity as corroborated in our simulations.

[1]  Walter Willinger,et al.  On the Self-Similar Nature of Ethernet Traffic ( extended version ) , 1995 .

[2]  James K. Cavers,et al.  Mobile Channel Characteristics , 2000 .

[3]  Sai Shankar Nandagopalan,et al.  IEEE 802.22: An Introduction to the First Wireless Standard based on Cognitive Radios , 2006, J. Commun..

[4]  Walter Willinger,et al.  On the self-similar nature of Ethernet traffic , 1995, CCRV.

[5]  M. Buddhikot,et al.  Spectrum management in coordinated dynamic spectrum access based cellular networks , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[6]  Xia Zhou,et al.  TRUST: A General Framework for Truthful Double Spectrum Auctions , 2009, IEEE INFOCOM 2009.

[7]  Xia Zhou,et al.  eBay in the Sky: strategy-proof wireless spectrum auctions , 2008, MobiCom '08.

[8]  Elias Aravantinos,et al.  A new pricing model for next generation spectrum access , 2005, TAPAS '06.

[9]  Vaduvur Bharghavan,et al.  Robust rate adaptation for 802.11 wireless networks , 2006, MobiCom '06.

[10]  M. Chatterjee,et al.  An Economic Framework for Spectrum Allocation and Service Pricing with Competitive Wireless Service Providers , 2007, 2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.

[11]  Baochun Li,et al.  A Secondary Market for Spectrum , 2010, 2010 Proceedings IEEE INFOCOM.

[12]  Hari Balakrishnan,et al.  Cross-layer wireless bit rate adaptation , 2009, SIGCOMM '09.

[13]  Vinko Erceg,et al.  Channel Models for Fixed Wireless Applications , 2001 .

[14]  P. Williamson,et al.  The Economics Of Financial Markets , 1996 .

[15]  Walter Willinger,et al.  On the self-similar nature of Ethernet traffic , 1993, SIGCOMM '93.