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Automated spectrum trading mechanisms: understanding the big picture

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Abstract

Public regulatory agencies have traditionally assigned radio-electric spectrum in a static way. This has led to an almost fully assigned but sparsely and unevenly used spectrum, in which it is becoming more difficult to accommodate the increasing demand of wireless communication. This work presents a general view of automated spectrum trading, one of the mechanisms proposed to improve spectrum efficiency. Licensed operators would be able to lease their unused bandwidth to unlicensed ones in secondary markets, satisfying real time demands from users. This results in a higher and more dynamic use of spectrum while providing incentives to spectrum owners for allowing secondary users to access their unused spectrum. Several approaches can be found in this research area combining game theory, economic models and auction design, among others. We describe and organize the main objectives and challenges of spectrum trading, and present a comprehensive classification and explanation of the existing research lines, showing how different works addressed each relevant issue, discussing the benefits and drawbacks of each approach. Finally, we highlight future research trends in this topic and identify critical but possibly overlooked problems.

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Notes

  1. Most papers outside this category also consider the time dimension, since channels are not leased forever. However, the difference is that they consider a fixed amount of time and do not charge a price per timeshare unit.

  2. “Bargaining games” term is used here in a general sense and the improvement in efficiency they bring is compared to the efficiency of other games with the same number of players. That is to say, comparing multi-player games with no communication between entities to many-to-many bargaining games or comparing any other two player game with no communication to a one-on-one bargaining game. Multi-player markets as decomposition of multiple one-on-one bargaining games are less efficient than other multi-player games.

  3. It could also be carried out by a third party, a regulator authority, although no examples have been found of that, probably because that would not be accepted by the entities involved as they would not have any way to influence it.

  4. “Virtual” as they have no spectrum license and may not even have infrastructure as a Mobile Virtual Network Operator “MVNO” for cellular networks.

  5. Works [33, 70] do not really study sellers’ competition but they are closely related to other works featured in this section, showing the same structure and dealing with investment as if they were on a competitive environment.

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Acknowledgments

This work was supported by project Grant MINECO/FEDER COINS TEC2013-47016-C2-2-R and it was also developed in the framework of “Programa de Ayudas a Grupos de Excelencia de la Región de Murcia, Fundación Séneca”. Mario López Martínez also acknowledges personal Grant BES-2011-051051.

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  1. Department of Information and Communications Technologies, Technical University of Cartagena (UPCT), Cartagena, Spain

    Mario López-Martínez, Juan J. Alcaraz, Javier Vales-Alonso & Joan Garcia-Haro

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  1. Mario López-Martínez
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Correspondence to Mario López-Martínez.

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López-Martínez, M., Alcaraz, J.J., Vales-Alonso, J. et al. Automated spectrum trading mechanisms: understanding the big picture. Wireless Netw 21, 685–708 (2015). https://doi.org/10.1007/s11276-014-0812-0

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