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Published in:
The Network Architecture for Spectrum Trading Read chapter Read first chapter

2015 | OriginalPaper | Chapter

3. A Session Based Spectrum Trading System Under Uncertain Spectrum Supply

Authors : Miao Pan, Ming Li, Pan Li, Yuguang Fang

Published in: Spectrum Trading in Multi-Hop Cognitive Radio Networks

Publisher: Springer International Publishing

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Abstract

Under the same network architecture, in this chapter, we introduce a session based spectrum trading system beyond transmission opportunity based spectrum trading in multi-hop CRNs. As illustrated in Chap. 1, we employ SSP to facilitate the accessing of SUs without CR capability and harvest uncertain spectrum supply. Besides, we also allow the SSP to conduct spectrum trading among CR sessions w.r.t. their conflicts and competitions. Leveraging a three-dimensional (3-D) conflict graph, we mathematically describe the conflicts and competitions among the candidate sessions for spectrum trading. Given the rate requirements and bidding values of candidate trading sessions, we formulate the optimal spectrum trading into the SSP’s revenue maximization problem under multiple cross-layer constraints. In view of the NP-hardness of the problem, we develop heuristic algorithms to pursue feasible solutions. Simulation results show the effectiveness and optimality of the proposed algorithms.

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previous chapter Economic-Robust Transmission Opportunity Based Spectrum Trading
next chapter Economic-Robust Session Based Spectrum Trading
Footnotes
1
Taking the least-utilized spectrum bands introduced in [9], for example, we found that the bandwidth between [1240, 1300] MHz (allocated to amateur radio) is 60 MHz, while bandwidth between [1525, 1710] MHz (allocated to mobile satellites, GPS systems, and meteorological applications) is 185 MHz.
 
2
Chen et al. in [3] carried out a set of spectrum measurements in the 20 MHz to 3 GHz spectrum bands at four locations concurrently in Guangdong province of China. They used these data sets to conduct a set of detailed analysis on statistics of the collected data, including channel occupancy/vacancy statistics, channel utilization, also spectral and spatial correlation of these measures.
 
3
Note that the denominator inside the log function contains only η. This is because of one of our interference constraints, i.e., when CR router i is transmitting to CR router j on band m, then all the other neighbors of router j within its interference range are prohibited from using this band. We will address the interference constraints in detail in the following section.
 
4
It is a NP-complete problem to find all maximal independent sets in \(\mathcal{G}\) [4, 5, 10], which will be further addressed later in this paper. In this section, we make the assumption we could find all the maximal independent sets just for the convenience of our theoretical analysis.
 
5
The multiple radios of CR routers allow for multi-path routing.
 
6
That is a general assumption used in existing literature [10, 15, 16] for obtaining throughput bounds or performance comparison.
 
7
We exploit the proposed BVR3 based relax-and-fix algorithm to derive these results in both the grid topology and the random topology.
 
Literature
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3.
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A. Goldsmith. Wireless Communications. Cambridge University Press, Cambridge, NY, 2005.
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P. Gupta and P. R. Kumar. The capacity of wireless networks. IEEE Transactions on Information Theory, 46(2):388–404, March 2000.
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Y. T. Hou, Y. Shi, and H. D. Sherali. Spectrum sharing for multi-hop networking with cognitive radios. IEEE Journal on Selected Areas in Communications, 26(1):146–155, January 2008.
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M. Pan, H. Yue, Y. Fang, and H. Li. The x loss: Band-mix selection for opportunistic spectrum accessing with uncertain supply from primary service providers. IEEE Transactions on Mobile Computing, 11(12):2133–2144, December 2012.
12.
M. Pan, C. Zhang, P. Li, and Y. Fang. Joint routing and scheduling for cognitive radio networks under uncertain spectrum supply. In Proc. of IEEE Conference on Computer Communications, INFOCOM 2011, Shanghai, China, April 2011.
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Y. Shi, Y. T. Hou, and S. Kompella. How to correctly use the protocol interference model for multi-hop wireless networks. In Proc. of ACM International Symposium on Mobile Ad Hoc Networking and Computing, ACM MobiHoc, 2009, New Orleans, LA, May 2009.
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J. Tang, S. Misra, and G. Xue. Joint spectrum allocation and scheduling for fair spectrum sharing in cognitive radio wireless networks. Computer Networks (Elsevier) Journal, 52(11):2148–2158, August 2008.
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H. Zhai and Y. Fang. Impact of routing metrics on path capacity in multirate and multihop wireless ad hoc networks. In Proc. of the IEEE International Conference on Network Protocols, ICNP 2006, Santa Barbara, CA, November 2006.
Metadata
Title
A Session Based Spectrum Trading System Under Uncertain Spectrum Supply
Authors
Miao Pan
Ming Li
Pan Li
Yuguang Fang
Copyright Year
2015
Book
Spectrum Trading in Multi-Hop Cognitive Radio Networks

Print ISBN: 978-3-319-25629-0

Electronic ISBN: 978-3-319-25631-3

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-25631-3_3

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