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Next generation wireless services and applications, including Augmented Reality, Internet-of-Things, and Smart- Cities, will increasingly rely on Dynamic Spectrum Access (DSA) methods that can manage spectrum resources rapidly and efficiently. Advances in regulatory policies, standardization, networking, and wireless technology are enabling DSA methods on a more granular basis in terms of time, frequency, and geographical location which are key for the operation of 5G and beyond-5G networks. In this context, this paper proposes a novel DSA algorithm that leverages IEEE 1900.5.2 Spectrum Consumption Models (SCMs) which offer a mechanism for RF devices to: (i) “announce” or “declare” their intention to use the spectrum and their needs in terms of interference protection; and (ii) determine compatibility (i.e., non-interference) with existing devices. In this paper, we develop an SCM-based DSA algorithm for spectrum deconfliction in large-scale wireless network environments and evaluate this algorithm in terms of computation time, efficiency of spectrum allocation, and number of device reconfigurations due to interference using a custom simulation platform. The results demonstrate the benefits of using SCMs and their capabilities to perform fine grained spectrum assignments in dynamic and dense communication environments. 

While millimeter-wave (mmWave) wireless has recently gained tremendous attention with the transition to 5G, developing a broadly accessible experimental infrastructure will allow the research community to make significant progress in this area. Hence, in this paper, we present the design and implementation of various programmable and open-access 28/60 GHz software-defined radios (SDRs), deployed in the PAWR COSMOS advanced wireless testbed. These programmable mmWave radios are based on the IBM 28 GHz 64-element dual-polarized phased array antenna module (PAAM) subsystem board and the Sivers IMA 60 GHz WiGig transceiver. These front ends are integrated with USRP SDRs or Xilinx RF-SoC boards, which provide baseband signal processing capabilities. Moreover, we present measurements of the TX/RX beamforming performance and example experiments (e.g., real-time channel sounding and RFNoC-based 802.11ad preamble detection), using the mmWave radios. Finally, we discuss ongoing enhancement and development efforts focusing on these radios.