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There are a wide array of methods for writing code generators. We advocate for a point in the design space, which we call *metaprogramming with combinators*, where programmers use (and write) combinator libraries that directly manipulate object language terms. The key language feature that makes this style of programming palatable is quasiquotation. Our approach leverages quasiquotation and other host language features to provide what is essentially a rich, well-typed macro language. Unlike other approaches, metaprogramming with combinators allows full control over generated code, thereby also providing full control over performance and resource usage. This control does not require sacrificing the ability to write high-level abstractions. We demonstrate metaprogramming with combinators through several code generators written in Haskell that produce VHDL targeted to Xilinx FPGAs. 

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. 

Functional hardware description languages (FHDL) provide powerful tools for building new abstractions that enable sophisticated hardware system to be constructed by composing small reusable parts. Raising the level of abstractions in hardware designs means the programmer can focus on high-level circuit structure rather than mundane low-level details. The language features that facilitate this include high-order functions, rich static type system with type inference, and parametric polymorphism. We use hand-written structural and behavioral VHDL, Simulink, and the Kansas Lava FHDL to re-implement several components taken from a Simulink model of an orthogonal frequency-division multiplexing (OFDM) physical layer (PHY). Our development demonstrates that an FHDL can require fewer lines of code than traditional design languages without sacrificing performance. 

As aspects of our daily lives become more interconnected with the emergence of the Internet of Things (IoT), it is imperative that our devices are reliable and secure from threats. Vulnerabilities of Wi-Fi Protected Access (WPA/WPA2) have been exposed in the past, motivating the use of multiple security techniques, even with the release of WPA3. Physical layer security leverages existing components of communication systems to enable methods of protecting devices that are well-suited for IoT applications. In this work, we provide a low-complexity technique for generating secret keys at the Physical layer to enable improved IoT security. We leverage the existing carrier frequency offset (CFO) and channel estimation components of Orthogonal Frequency Division Multiplexing (OFDM) receivers for an efficient approach. The key generation algorithm we propose focuses on the unique CFO and channel experienced between a pair of desired nodes, and to the best of our understanding, the combination of the features has not been examined previously for the purpose of secret key generation. Our techniques are appropriate for IoT devices, as they do not require extensive processing capabilities and are based on second order statistics. We obtain experimental results using USRP N210 software defined radios and analyze the performance of our methods in post-processing. Our techniques improve the capability of desired nodes to establish matching secret keys, while hindering the threat of an eavesdropper, and are useful for protecting future IoT devices. 

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.