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Dynamic Spectrum Access (DSA) radios typically select their radio channels according to their data networking goals, a defined DSA spectrum operating policy, and the state of the RF spectrum. RF spectrum sensing can be used to collect information about the state of the RF spectrum and prioritize which channels should be assigned for DSA radio waveform transmission and reception. This paper describes a Greedy Channel Ranking Algorithm (GCRA) used to calculate and rank RF interference metrics for observed DSA radio channels. The channel rankings can then be used to select and/or avoid channels in order to attain a desired DSA radio performance level. Experimental measurements are collected using our custom software-defined radio (SDR) system to quantify the performance of using GCRA for a DSA radio application. Analysis of these results show that both pre and post-detection average interference power metrics are the most accurate metrics for selecting groups of radio channels to solve constrained channel assignment problems in occupied gray space spectrum. 

Traditional approaches to experimental characterization of wireless communication systems typically involves highly specialized and small-scale experiments to examine narrow aspects of each of these applications. We present the Grid SDR testbed, a unified experimental framework to rapidly prototype and evaluate these diverse systems using: (i) field measurements to evaluate real time transceiver and channel-specific effects and (ii) network emulation to evaluate systems at a large scale with controllable and repeatable channels. We present the hardware and software architecture for our testbed, and describe how it being used for research and education. Specifically, we show experimental network layer metrics in different application domains, and discuss future opportunities using this unique experimental capability. 

Most sensor networks on a naval vessel are wired directly to the control unit,[1, 16] and this includes the Power System. This paper demonstrates how an IEEE 802.15.4 based Wireless Sensor Network (WSN) could be used to have an easy to deploy, flexible and affordable Smart Grid Power System monitoring structure. In published literature, it has been qualitatively proven that a WSN can work on a ship, despite its more complex Radio Frequency (RF) environment. This work quantifies this, showing the achievable levels of Packet Error Rate under different levels of Signal to Interference and Noise Ratio, proving that it could be used instead of a wired channel. Another important aspect studied was the cybersecurity implications of using a wireless network versus a wired one. The effects of delayed, missing and faked power measurements were also studied, along with a discussion of what could be done to detect and mitigate them.