Risk Portfolio of Spectrum Usage

28 Pages Posted: 25 Mar 2015 Last revised: 6 Aug 2015

See all articles by Liu Cui

Liu Cui

West Chester University Computer Science Department

Martin B. H. Weiss

University of Pittsburgh - School of Information Sciences

Date Written: March 24, 2015


Spectrum sharing has been adopted slowly, even if the literature demonstrates that it provides the flexibility needed to respond to temporal and spatial variations in the traffic and bandwidth demand of different services. Several factors impede the adoption of spectrum sharing: (1) the quantity of shareable spectrum; (2) cost of spectrum sharing, including both monetary cost and processing time; (3) uncertainties and risks in spectrum sharing. The FCC and NTIA have made noteworthy efforts to enlarge the amount of shareable spectrum. For example, the TVWS is free for unlicensed access, and federal frequency bands, such as 1670 MHz and 3.5 GMz, are under consideration for federal-commercial sharing. Moreover, with the database assisted approach, the processing time of authorization is significantly shortened. Additionally, spectrum may be traded in the secondary spectrum market. When requirements are met, the trade can be approved within 24 hours.

Although more spectrum has been made available for sharing and the cost are decreasing, uncertainties and risks that are embedded in spectrum sharing still exist. Moreover, there are many spectrum sharing methods, such as cooperative sharing through trading, Authorized Spectrum Access, TV White Space, etc. Each spectrum sharing method leads to different risk portfolio. In addition, different frequency bands, coverage, and location brings more uncertainties and risks. We claim that these uncertainties and risks are significant barriers that hinder spectrum sharing from proliferating, in part because spectrum entrants and incumbents will not share spectrum when future conditions are difficult to foresee.

Consequently, minimizing risks for PUs and SUs is a key strategy to promote spectrum sharing. This paper seeks to outline the key risks and show how they can be managed. To this end, the first task is to analyze the risk portfolio for each spectrum usage model qualitatively and quantitatively. We focus on the following usage spectrum usage types: primary usage, cooperative sharing through trading, ASA, TVWS, sensing based Dynamic Spectrum Access (DSA), and unlicensed usage in ISM bands. These spectrum risks can be divided into three categories: (1) Monetary risk: every SU faces the risk that the firm cannot afford the project and the expected costs are not in line with the projected profits. (2) Competition risk: the competition in cooperative sharing comes from obtaining contracts. On the other hand, the competition in spectrum commons and sensing stems from identifying and accessing available spectrum. SUs may adopt advanced technology in order to increase the chances of success. (3) Environment risk: regulatory actions and secondary spectrum market liquidity may pose external risks for SUs. The spectrum risks will be quantified using a queueing model and computer simulations. Two types of risk metrics will be determined: (1) on average what is the percentage of the time that the service level agreement (SLA) can be met; (2) what is the probability that the SLA can be met at each point of time. The reason why we choose these two risk metrics is because (1) the satisfaction of the SLA is an important factor in determining the profits that service providers may gain, so we can determine the monetary risks from the first risk metrics; (2) the distribution of spectrum access risks can be applied in risk-informed regulation, which helps regulators and spectrum users determine the best practice for spectrum sharing in different environment.

The second task is to determine suitable strategies to mitigate these risks. In this paper, we focus on reducing risks for PUs and SUs by financial means. We begin with cooperative sharing through trading. The risk for this sharing method is that it is difficult if not impossible for PUs and SUs to predict their future usage. Two results emerge from this. First, spectrum users will be conservative so that PUs will only lease the minimum amount of spectrum to ensure capacity should their future service demand increase. SUs may choose lease the minimum amount of spectrum in case demand will decrease. Second, spectrum users may lease the maximum amount of spectrum, assuming the risks of service degradation or financial failure. Neither outcome is desirable. Trading spectrum as financial options can reduce these risks. Options give the buyer the right but not obligation to share the spectrum. This asymmetry provides protection for both parties. On one hand, the buyer of the right can decide whether to share the spectrum or not depending on their circumstances. On the other hand, the seller of the right either gains the premium (spectrum leasing fee) when buyers exercise the right or the strike (price of the right) when buyers do not exercise the rights.

With this framework, we proceed by broadening our view to other spectrum sharing methods. In general, spectrum entrants entering the wireless market face the decision of selecting the most appropriate spectrum usage method for their circumstance. Each spectrum usage method has embedded risks and uncertainties, such as changing situations in spectrum utilization environment, regulatory rules, service demands, etc. that may occur throughout the investment life cycle. However, risks and uncertainties may not necessarily lead to failure. When they occur, instead of passively committing to the existing business strategy, corporations have the right to delay, expand, contract, or abandon a project with a given cost or salvage value at some future date. This management flexibility may be able to alleviate the risks. Hence, in order to reduce the possibility of business failure, a clear understanding of each spectrum usage method is essential. Therefore, we will identify potential risks and mitigation strategies for each spectrum usage method. Then, we will quantify the value of each spectrum sharing method considering both risks and mitigation strategies by real options. With this value, spectrum entrants can make an informed decision by explicitly considering risks and mitigation strategies.

The outcome of this paper will promote spectrum sharing by showing how these risks may be minimized. It will also help identify the potential challenge with each spectrum sharing method. Therefore, policy makers, operators, and the spectrum market could create interventions in order to obtain the favorable outcomes.

Suggested Citation

Cui, Liu and Weiss, Martin B. H., Risk Portfolio of Spectrum Usage (March 24, 2015). TPRC 43: The 43rd Research Conference on Communication, Information and Internet Policy Paper. Available at SSRN: https://ssrn.com/abstract=2584643 or http://dx.doi.org/10.2139/ssrn.2584643

Liu Cui (Contact Author)

West Chester University Computer Science Department ( email )

United States

Martin B. H. Weiss

University of Pittsburgh - School of Information Sciences ( email )

135 N Bellefield Ave
Pittsburgh, PA 15260
United States

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