Xampling: Signal Acquisition and Processing in Union of Subspaces

We introduce Xampling, a unified framework for signal acquisition and processing of signals in a union of subspaces. The main functions of this framework are two. Analog compression that narrows down the input bandwidth prior to sampling with commercial devices. A nonlinear algorithm then detects the input subspace prior to conventional signal processing. A representative union model of spectrally-sparse signals serves as a test-case to study these Xampling functions. We adopt three metrics for the choice of analog compression: robustness to model mismatch, required hardware accuracy and software complexities. We conduct a comprehensive comparison between two sub-Nyquist acquisition strategies for spectrally-sparse signals, the random demodulator and the modulated wideband converter (MWC), in terms of these metrics and draw operative conclusions regarding the choice of analog compression. We then address lowrate signal processing and develop an algorithm for that purpose that enables convenient signal processing at sub-Nyquist rates from samples obtained by the MWC. We conclude by showing that a variety of other sampling approaches for different union classes fit nicely into our framework.Comment: 16 pages, 9 figures, submitted to IEEE for possible publicatio

Wavelet—Artificial Neural Network Receiver for Indoor Optical Wireless Communications

The multipath induced intersymbol interference (ISI) and fluorescent light interference (FLI) are the two most important system impairments that affect the performance of indoor optical wireless communication (OWC) systems. The presence of either incurs a high optical power penalty (OPP) and hence the interferences should be mitigated with suitable techniques to ensure optimum system performance. The discrete wavelet transform (DWT) and the artificial neural network (ANN) based receiver to mitigate the effect of FLI and ISI has been proposed in the previous study for the one-off keying (OOK) modulation scheme. It offers performance improvement compared to the traditional methods of employing a high pass filter (HPF) and a finite impulse response (FIR) equalizer. In this paper, the investigation of the DWT-ANN based receiver for baseband modulation techniques including OOK, pulse position modulation (PPM) and digital pulse interval modulation (DPIM) are reported. The proposed system is implemented using digital signal processing (DSP) board and results are verified by comparison with simulation data

Self-Interference Cancellation Using Time-Domain Phase Noise Estimation in OFDM Full-Duplex Systems

In full-duplex systems, oscillator phase noise (PN) problem is considered the bottleneck challenge that may face the self-interference cancellation (SIC) stage especially when orthogonal frequency division multiplexing (OFDM) transmission scheme is deployed. Phase noise degrades the SIC performance significantly, if not mitigated before or during the SIC technique. The presence of the oscillator phase noise has different impacts on the transmitted data symbol like common phase error (CPE) and inter-carrier interference (ICI). However, phase noise can be estimated and mitigated digitally in either time or frequency domain. Through this work, we propose a novel and simple time domain self-interference (SI) phase noise estimation and mitigation technique. The proposed algorithm is inspired from Wiener filtering in time domain. Simulation results show that the proposed algorithm has a superior performance than the already-existing time-domain or frequency domain PN mitigation solutions with a noticeable reduction in the computational complexity

Adaptive OFDM System Design For Cognitive Radio

Recently, Cognitive Radio has been proposed as a promising technology to improve spectrum utilization. A highly flexible OFDM system is considered to be a good candidate for the Cognitive Radio baseband processing where individual carriers can be switched off for frequencies occupied by a licensed user. In order to support such an adaptive OFDM system, we propose a Multiprocessor System-on-Chip (MPSoC) architecture which can be dynamically reconfigured. However, the complexity and flexibility of the baseband processing makes the MPSoC design a difficult task. This paper presents a design technology for mapping flexible OFDM baseband for Cognitive Radio on a multiprocessor System-on-Chip (MPSoC)

Sub-Nyquist Sampling: Bridging Theory and Practice

Sampling theory encompasses all aspects related to the conversion of continuous-time signals to discrete streams of numbers. The famous Shannon-Nyquist theorem has become a landmark in the development of digital signal processing. In modern applications, an increasingly number of functions is being pushed forward to sophisticated software algorithms, leaving only those delicate finely-tuned tasks for the circuit level. In this paper, we review sampling strategies which target reduction of the ADC rate below Nyquist. Our survey covers classic works from the early 50's of the previous century through recent publications from the past several years. The prime focus is bridging theory and practice, that is to pinpoint the potential of sub-Nyquist strategies to emerge from the math to the hardware. In that spirit, we integrate contemporary theoretical viewpoints, which study signal modeling in a union of subspaces, together with a taste of practical aspects, namely how the avant-garde modalities boil down to concrete signal processing systems. Our hope is that this presentation style will attract the interest of both researchers and engineers in the hope of promoting the sub-Nyquist premise into practical applications, and encouraging further research into this exciting new frontier.Comment: 48 pages, 18 figures, to appear in IEEE Signal Processing Magazin