Database-driven cognitive radio has been well recognized as an efficient way to reduce interference between Primary Users (PUs) and Secondary Users (SUs). In database-driven cognitive radio, PUs and SUs must provide their locations to enable dynamic channel allocation, which raises location privacy breach concern. Previous studies only focus on unilateral privacy preservation, i.e., only PUs’ or SUs’ privacy is preserved. In this paper, we propose to protect bilateral location privacy of PUs and SUs. The main challenge lies in how to coordinate PUs and SUs to maximize their utilities provided that their location privacy is protected. We first introduce a quantitative method to calculate both PUs’ and SUs’ location privacy, and then design a novel privacy preserving Utility Maximization protocol (UMax). UMax allows for both PUs and SUs to adjust their privacy preserving levels and optimize transmit power iteratively to achieve the maximum utilities. Through extensive evaluations, we demonstrate that our proposed protocol can efficiently increase the utilities of both PUs and SUs while preserving their location privacy.

中文翻译：

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数据库驱动的认知无线电网络中的双边隐私保护效用最大化协议

数据库驱动的认知无线电已被公认为减少主要用户 (PU) 和次要用户 (SU) 之间干扰的有效方式。在数据库驱动的认知无线电中，PU 和 SU 必须提供它们的位置以启用动态信道分配，这引发了位置隐私泄露问题。以往的研究只关注单边隐私保护，即只保护PUs 或SUs 的隐私。在本文中，我们建议保护 PU 和 SU 的双边位置隐私。主要挑战在于如何协调 PU 和 SU 以最大化其效用，前提是他们的位置隐私受到保护。我们首先介绍了一种计算 PU 和 SU 位置隐私的定量方法，然后设计了一种新颖的隐私保护效用最大化协议（UMax）。UMax 允许 PU 和 SU 调整其隐私保护级别并迭代优化传输功率以实现最大效用。通过广泛的评估，我们证明我们提出的协议可以有效地增加 PU 和 SU 的效用，同时保护它们的位置隐私。