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Traditionally, the radio spectrum has been allocated statically. However, this process has become obsolescence as most of the allocated spectrum is underutilized, and the part of the spectrum that is mainly used by the technologies that we use for daily communication is over-utilized. As a result, there is a shortage of available spectrum to deploy emerging technologies like 5G that require high demands on data. Several global efforts are addressing this problem, i.e., the Citizens Broadband Radio Service (CBRS) and Licensed Shared Access (LSA) bands, to increase the spectrum reuse by providing multi-tiers spectrum sharing frameworks in the re-allocated radio spectrum. However, these approaches suffer from two main problems. First, this is a slow process that may take years before authorities can reassign the spectrum to new uses. Second, they do not scale fast since it requires a centralized infrastructure to protect the legacy technology and coordinate and grant access to the shared spectrum. As a solution, the Spectrum Collaboration Challenge (SC2) challenge has shown that Collaborative Intelligent Radio Network (CIRN), i.e., Artificial Intelligence (AI)based autonomous wireless radio technologies that collaborate, can share and reuse spectrum efficiently without any coordination and with the guarantee of incumbent protection. In this paper, we present the architectural design and the experimental validation of an incumbent protection system for the next generation of spectrum sharing frameworks. The proposed system is a twostep AI-based algorithm that recognizes, learns, and proactively predicts the transmission pattern of the incumbent in near real-time, less than 300 ms to perform a prediction, with an accuracy above 95% to correctly predict where the incumbent is transmitting in the future. The proposed algorithm was validated in Colosseum, the RF channel emulator built for the SC2 competition, using up to two incumbents simultaneously, which have different transmission patterns, and sharing spectrum with up to 5 additional networks.

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DARPA, the Defense Advanced Research Projects Agency from the United States, has started the Spectrum Collaboration Challenge with the aim to encourage research and development of coexistence and collaboration techniques of heterogeneous networks in the same wireless spectrum bands. Team SCATTER has been participating in the challenge since its beginning, back in 2016. SCATTER’s open-source software defined physical layer (SCATTER PHY) has been developed as a standalone application, with the ability to communicate with higher layers through a set of well defined messages (created with Google’s Protocol buffers) and that exchanged over a ZeroMQ bus. This approach allows upper layers to access it remotely or locally and change all parameters in real time through the control messages. SCATTER PHY runs on top of USRP based software defined radio devices (i.e., devices from Ettus or National Instruments) to send and receive wireless signals. It is a highly optimized and real-time configurable SDR based PHY layer that can be used for the research and development of novel intelligent spectrum sharing schemes and algorithms. The main objective of making SCATTER PHY available to the research and development community is to provide a solution that can be used out of the box to devise disruptive algorithms and techniques to optimize the sub-optimal use of the radio spectrum that exists today. This way, researchers and developers can mainly focus their attention on the development of smarter (i.e., intelligent algorithms and techniques) spectrum sharing approaches. Therefore, in this paper, we describe the design and main features of SCATTER PHY and showcase several experiments performed to assess the effectiveness and performance of the proposed PHY layer.

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