Iterative algorithms to compensate for quantization noise in monobit transmitted-reference receivers

Recently finite-resolution digital receivers have been proposed for weighted-transmitted reference ultra-wideband (WTR-UWB) systems. However, employing a finite-resolution receiver severely degrades the performance due to a sever quantization noise. In this paper, two novel iterative algorithms are proposed to recover the reference pulse based on the detected data pulses and employing nonlinear signal processing while preventing the error propagation. The first algorithm exploits a new signal processing approach, referred to as polarity invariant square law technique. In this approach the reconstructed reference pulse is first squared and multiplied by its sign and then is used to demodulate the monobit data pulses. Hence, it can be assumed that in this technique data pulses have been recovered from monobit quantization noise as well. In the second algorithm, the mentioned reconstructed reference pulse is cubed and then is used for demodulation. Simulation results illustrate that employing these two novel signal-processing methods highly mitigates the contribution of the small (noise dominant) samples to the decision statistic. The performance of the proposed algorithms is evaluated at a data rate of 23.78 Mbps over in-vehicle channels, taking into account noise, inter-symbol interference (ISI), and inter-block interference (IBI). The obtained simulation results demonstrate that the proposed algorithms enhance the performance about 1.7 dB as compared to the existing algorithms. As a result, applying these algorithms would be a promising approach to implement high performance monobit transmitted-reference (TR) receivers.