Trading Wireless Capacity Through Spectrum Virtualization Using LTE-A

35 Pages Posted: 30 Mar 2014 Last revised: 30 Mar 2015

See all articles by Marcela Gomez

Marcela Gomez

University of Pittsburgh - School of Information Sciences

Liu Cui

West Chester University Computer Science Department

Martin B. H. Weiss

University of Pittsburgh - School of Computing and Information

Date Written: March 29, 2014

Abstract

Increasing interest in developing spectrum sharing mechanisms has proven that primary markets for spectrum alone do not provide an efficient ongoing allocation of this resource. In this paper, we explore the advantages of wireless virtualization in order to enhance the viability and liquidity requirements of secondary markets for spectrum trading.

Many economists agree that markets, not regulation, should be the preferred method for allocating scarce resources. From a technical point of view, the multidimensionality of electromagnetic spectrum, increases the complexity of the market design process. In previous work, the authors analyzed markets for “naked spectrum” (i.e., markets in frequency bands alone) and examined their liquidity. In the authors relaxed the perfect spectrum substitutability assumptions of and incorporated the realistic attributes of spectrum into the market that lead to constraints on fungibility. Even when spectrum markets are liquid, we assert that the aforementioned models remain rather difficult to conceive in practice as the technical challenges surrounding these approaches are considerable (e.g., finding radios capable of tuning to a wide range of frequencies at the same time).

The prior studies suggest that trading in naked spectrum is not viable. In this paper, we consider the viability of markets in wireless capacity. When wireless resources are virtualized, then the tradeable commodity becomes capacity that is less constrained by the physical attributes of spectrum. Virtualization has been explored as infrastructure virtualization and air interface virtualization, resulting, in each case, in high levels of spectrum efficiency. In more recent work, we have observed an interest to shift spectrum sharing to higher network layers by means of virtualization. In this light, virtualization would imply an “elimination of spectrum bounds”, thus permitting us to envision service-driven networks in which Service Providers could request different types of connectivity, capacity and coverage capabilities from Virtual Network Operators, without being concerned about the underlying electromagnetic frequency.

Papers such as articulate a vision for the future without considering the technical mechanisms. To study how this would impact spectrum trading, we must be more specific. In particular, we will study how markets in virtual wireless capacity would work when implemented in LTE-Advanced. This will allow us to study the virtualization of resources available to this technology, taking advantage of its unique characteristics. Our approach is to map the LTE Physical Resource Blocks (PRBs) to a virtual component such as bandwidth. Thus, we can consider a scenario in which service providers acquire capacity from Virtual Network Operators according to the service they need to fulfill. In turn, when Virtual Network Operators seek for spectrum resources they can also opt for the number of PRBs that correspond to the capacity they would like to offer. In both cases, service providers and Virtual Network Operators do not take into consideration the specific frequency band that the capacity/PRBs correspond to. The resource descriptors of PRBs would not be determined until “run time”, i.e., the point at which they must be transmitted.

We will adapt the existing ACE-based trading model, SPECTRAD [2,3] to accommodate this new market formulation. Here, the available commodity is a specific amount of capacity (given by LTE PRBs and cell-aggregation capabilities). Virtual Network Operators can compete amongst them and place bids for the amount of capacity they consider suitable for fulfilling their requirements. Under these considerations, we will investigate whether the incorporation of a virtualized spectrum commodity influences the market liquidity outcome, and how this compares to previous scenarios in which the traded commodity was the physical spectrum resource or “naked spectrum”. Adapting SPECTRAD will make comparability with previous results more feasible.

Spectrum markets, generally conceived, allow stakeholders to efficiently value and use the critical resource. However, lack of liquidity impedes markets from achieving this outcome. The ultimate goal of this research program is to find a way to implement viable and efficient spectrum markets. Among them, the first step is determining the appropriate trade-able commodity that will increase the market’s viability in scenarios that are likely to occur in practice. The outcome of this work will assist spectrum trading and then lead wireless services to the era of “spectrum without bounds”.

Suggested Citation

Gomez, Marcela and Cui, Liu and Weiss, Martin B. H., Trading Wireless Capacity Through Spectrum Virtualization Using LTE-A (March 29, 2014). 2014 TPRC Conference Paper, Available at SSRN: https://ssrn.com/abstract=2417639 or http://dx.doi.org/10.2139/ssrn.2417639

Marcela Gomez (Contact Author)

University of Pittsburgh - School of Information Sciences ( email )

United States

Liu Cui

West Chester University Computer Science Department ( email )

United States

Martin B. H. Weiss

University of Pittsburgh - School of Computing and Information ( email )

135 N Bellefield Ave
Pittsburgh, PA 15260
United States

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