Weighted energy detection of ultra-wideband signals

Abstract

Non-coherent energy detectors are motivated for ultra-wideband (UWB) impulse radios with simple circuitry. A major performance-degrading factor in energy detection is the noise floor, which is aggravated in low-duty-cycle UWB signals with a large bandwidth-time product. We develop weighted energy detection techniques for effective noise suppression. The received signal is processed by a set of parallel integrators, each corresponding to a different integration time window within a symbol period. The outputs of these integrators are weighted and linearly combined to generate decision statistics for signal detection and data demodulation. Signal segments with larger noise contributions are given smaller weights, thus improving the receive SNR. The decision thresholds and weighting coefficients are derived analytically to optimize the detection performance.