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Full Version: A Compressed Sensing Based Ultra-Wideband Communication System
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Peng Zhang, Zhen Hu, Robert C. Qiu
Brian M. Sadler


Abstract
Sampling is the bottleneck for ultra-wideband (UWB) communication. Our major contribution is to exploit the channel itself as part of compressed sensing, through waveformbased pre-coding at the transmitter. We also have demonstrated a UWB system baseband bandwidth (5 GHz) that would, if with the conventional sampling technology, take decades for the industry to reach. The concept has been demonstrated, through simulations, using real-world measurements. Realistic channel estimation is also considered.



INTRODUCTION

Ultra-wideband (UWB represents a new paradigm in wireless communication. The unprecedented radio bandwidth provides advantages such as immunity from flat fading. Two primary challenges exist: (1) how to collect energy over the rich multipath components; (2) extremely high sampling rate analog to digital conversion (A/D). Time reversal provides a promising solution to the first problem .

In particular, the concept of time reversal has recently demonstrated in a real-time hardware test-bed. At the heart of time reversal, the channel itself is exploited as a part of the transceiver. This idea makes sense since when few movements exist, the channel is time-invariant and reciprocal . In principle, most of the processing at the receiver can be moved to the transmitter—where energy consumption and computation are sufficient for many advanced algorithms. A natural question arises: Can we move the hardware complexity of the receiver to the transmitter side to reduce the sampling rate of A/D to the level of 125 Msps—for which excellent high dynamic range commercial solutions are available? Fortunately compressed sensing (CS) is a natural framework for our purpose.

CS has been used to UWB communications. Our major contribution is to exploit the channel itself as part of compressed sensing, through waveform-based pre-coding at the transmitter. Only one low-rate A/D is used at the receiver. We also have demonstrated (Fig. 1) a UWB system covering the 3 GHz – 8 GHz frequency band that would, if with the conventional sampling technology, take decades for the industry to reach.

This paper is organized as follows. Section II introduces the CS theory background and extends CS concept to a continuous time filter based architecture. Section III describes the proposed CS based UWB system together with a CS based channel estimation method. Section IV shows the simulation results and section V gives the conclusions.



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