Energy-aware multiband communications in heterogeneous networks

This paper investigates the energy-efficiency of well-known spectrum sensing algorithms that exploit the sensed signal's energy, autocorrelation or cyclostationarity features to estimate the presence or absence of that signal in a given spectrum. We investigate the trade-off between energy-efficiency, complexity, and sensing accuracy of those detectors and, their suitability for energy-efficient WiFi spectrum sensing that enables interoperability of Long Term Evolution Advanced (LTE-A) and WiFi systems. Results obtained show significant improvement in correct detection probability and reduced sensing time using the low complexity autocorrelation detectors when compared to other detectors under low signal to noise ratio channel conditions.