Frequency-Shift Filtering for Interference Mitigation in Sensor Networks: Signal Parameter Impacts and Empirical Performance Benchmark

Frequency-shift (FRESH) filtering is a low-compute technique that is deemed an attractive alternative to successive interference cancellation (SIC) algorithms in communication systems that involve resource-constrained devices. FRESH filters exploit the cyclostationary properties of interfering signals by linearly combining the spectrally redundant components of a signal such that they destructively add. Therefore, the performance in terms of bit error rate or mean squared error achievable by a FRESH filter is dependent on the cyclostationarity features exhibited by a signal. Their computationally simple architecture makes FRESH filters well-suited for low-power wireless sensors, whereas their protocol-agnostic operation is appealing to all manners of cognitive radio, making them an excellent component of ad hoc or infrastructure-less networks. This paper surveys the published FRESH filter designs for communication systems and provides empirical data on their performance under a variety of signal-of-interest and interferer signal properties. We contrast various FRESH filter configurations and ways to determine filter coefficients, comparing against a baseline SIC algorithm in terms of cancellation performance.