Spectrum regulators are pursuing centralized, dynamic sharing systems that will enable spectrum access for new wireless technologies. These sharing systems will leverage cognitive radio concepts to automatically identify suitable spectrum for users. Collected user information may be considered sensitive, and some incumbents are hesitant about spectrum sharing, citing privacy concerns. Privacy preserving strategies are needed to promote widespread spectrum sharing. However, privacy preserving techniques typically come at the expense of spectrum efficiency, resulting in reduced utility for the users. In this work we study this privacy-performance tradeoff. We develop a generalized spectrum sharing system architecture and formulate the multi-utility, user privacy optimization problem, where privacy is measured by exposure to potential adversary inference attacks. We derive the optimal solution for this spectrum sharing privacy problem and then formulate an efficient heuristic strategy that exploits the problem structure. Via numerical analysis, we demonstrate substantial improvement over the prevailing obfuscation strategies applied in the literature, with up to a 50% increase in privacy and negligible impact on spectrum efficiency for a real-world use case. To our knowledge, this is the first work to formally derive the optimal solution to the user privacy problem in a generalized spectrum sharing framework.

To satisfy the increasing demand for additional bandwidth from the wireless sector, regulatory bodies are considering to allow commercial wireless systems to operate on spectrum bands that until recently were reserved exclusively for military radar. Such co-existence would require mechanisms for controlling interference. One such mechanism is to assign a precoder to the communication system, which is designed to minimize the communication system’s interference to the radar. This paper looks into whether the implicit radar information contained in such a precoder can be exploited by an adversary to infer the radar’s location. For two specific precoder schemes, we simulate a machine learning based location inference attack. We show that the system information leaked through the precoder can indeed pose various degrees of risk to the radar’s privacy, and further confirm this by computing the mutual information between the respective precoder and the radar location.

In an effort to meet growing demands on the radio frequency spectrum, regulators are exploring methods to enable band sharing among a diverse set of user devices. Proposed spectrum access systems would dynamically assign spectrum resources to users, maintaining databases of spectrum use information. While these systems are anticipated to increase the efficiency of spectrum sharing, incumbent users have raised concerns about exposing details of their operations and have questioned whether their privacy can be protected. In this paper, we explore whether primary users can retain a critical level of privacy in a spectrum access system setting, where they must reveal some information to enable dynamic access to the spectrum by other users. Under a variety of operational scenarios and user models, we examine adversary techniques to exploit the spectrum access system and obfuscation strategies to protect user privacy. We develop analytical methods to quantify the resulting privacy and validate our results through simulation. To the best of our knowledge, this is the first paper that considers inference attacks on primary users in the setting of a highly dynamic spectrum access system. Privacy analysis of this kind will help to enable the adoption of shared spectrum access systems by allowing incumbent users to quantify and mitigate risks to their privacy.

Effective radio frequency spectrum sharing methods are crucial for sustaining growth and development in mobile wireless services. In this paper, we consider a real-world scenario involving spectrum sharing between mobile wireless and meteorological satellite services as motivation for examining the general problem of efficient resource scheduling in a shared spectrum environment. We formulate an optimization framework for maximizing network utility subject to stochastic interference protection constraints. We design and propose a novel solution inspired by analysis of the optimization problem, where the primary contribution is an efficient power allocation algorithm to manage interference between systems. Using theory and simulations, we show that our algorithm significantly outperforms alternative approaches by well approximating the optimal solution with low enough complexity for practical, real-time application to large networks.

In an effort to meet growing demands on the radio frequency spectrum, regulators are exploring methods to enable band sharing among a diverse set of user devices. Proposed spectrum access systems would dynamically assign spectrum resources to users, maintaining databases of spectrum use information. While these systems are anticipated to increase the efficiency of spectrum sharing, incumbent users have raised concerns about exposing details of their operations and have questioned whether their privacy can be protected. In this paper, we explore whether primary users can retain a critical level of privacy when a system uses their information to enable dynamic access to the spectrum by other users. Under a variety of operational scenarios and user models, we examine adversary techniques to exploit the spectrum access system and obfuscation strategies to protect user privacy. We also develop analytical methods to quantify the performance of both the adversary and obfuscation strategies. To our knowledge, this is the first work that considers the privacy of a primary user in the setting of a highly dynamic spectrum access system. Privacy analysis of this kind will help to enable adoption of shared spectrum access systems by allowing incumbent users to quantify and mitigate risks to their privacy.

With limited opportunities to open up new unencumbered bands to mobile wireless services, interest in enhancing methods for sharing of spectrum between services is high. For example, the band 1695-1710 MHz is expected to be made available to 3GPP Long-Term Evolution cellular network uplinks by sharing with incumbent meteorological satellite services already in the band. The LTE networks are to be operated in a manner that ensures no loss of incumbent capability by adhering to protection requirements such as a limit on the aggregate interference power at fixed incumbent earth station locations. In this paper, we consider this specific spectrum sharing scenario as motivation and formulate an optimization framework for power control and time-frequency resource scheduling on the LTE uplink with an aggregate interference constraint. We design and propose a novel algorithm inspired by numerical solution and analysis of the optimization problem. Using theory and simulation, we show that our algorithm significantly outperforms more simplistic approaches, well approximates the optimal solution, and is of sufficient scope and complexity for practical implementation, even in relatively large LTE networks. Algorithms of this kind are necessary for mobile wireless networks to make the most of constrained spectrum resources in shared bands.