Generic low complex filter bank based spectrum sensing approach for LTE cognitive radio

For mobile user equipments (UE) a careful power management is essential. Despite this fact, quite an amount of energy is wasted in today's UEs' analogue (AFE) and digital frontends (DFE). The latter are engineered for extracting the wanted signal from a spectral environment defined in the corresponding communication standards with their extremely tough requirements. These requirements define a worstcase scenario still ensuring reliable communication. In a typical receiving process those requirements can be considered as less critical. Knowledge about the actual environmental spectral conditions allows to reconfigure both frontends to the actual needs and to save energy. In this paper we present a highly efficient generic spectrum sensing approach, endowing both the AFE and DFE with increased intelligence by adopting their performance to the instantaneous spectrum allocation. We call this approach long term evolution cognitive radio. A low complex multiplier free filter bank will be introduced. Our presentation includes also simulation results, which will illustrate the performance of the overall system, and a complexity comparison to different FFT based implementations.