Sampling rate reduction for 60 GHz UWB communication using compressive sensing

Authors:
Jia Meng;Javad Ahmadi-Shokouh;Husheng Li;E. Joe Charlson;Zhu Han;Sima Noghanian;Ekram Hossain
Affiliations:
Department of Electrical and Computer Engineering Department, University of Houston, Houston, Texas;Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, Manitoba, Canada;Department of Electrical and Computer Science, University of Tennessee, Knoxville, Tennessee;Department of Electrical and Computer Engineering Department, University of Houston, Houston, Texas;Department of Electrical and Computer Engineering Department, University of Houston, Houston, Texas;Department of Electrical Engineering, University of North Dakota, Grand Forks, North Dakota;Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, Manitoba, Canada
Venue:
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Year:
2009

Citing 9
Cited 0

A practical Bayesian framework for backpropagation networks

Neural Computation
Sparse bayesian learning and the relevance vector machine

The Journal of Machine Learning Research
Convex Optimization

Convex Optimization
Resource Allocation for Wireless Networks: Basics, Techniques, and Applications

Resource Allocation for Wireless Networks: Basics, Techniques, and Applications
Toeplitz-Structured Compressed Sensing Matrices

SSP '07 Proceedings of the 2007 IEEE/SP 14th Workshop on Statistical Signal Processing
Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information

IEEE Transactions on Information Theory
Compressed sensing

IEEE Transactions on Information Theory
Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?

IEEE Transactions on Information Theory
Exploiting the 60 GHz band for local wireless multimedia access: prospects and future directions

IEEE Communications Magazine

Quantified Score

Hi-index	0.00

Visualization

Abstract

60 GHz ultra wide-band (UWB) communication is an emerging technology for high speed short range communications. However, the requirement of high-speed sampling increases the cost of receiver circuitry such as analog-to-digital converter (ADC). In this paper, we propose to use a compressive sensing framework to achieve a significant reduction of sampling rate. The basic idea is based on the observation that the received signals are sparse in the time domain due to the limited multipath effects at 60 GHz wireless transmission. According to the theory of compressive sensing, by carefully designing the sensing scheme, sub-Nyquist rate sampling of the sparse signal still enables exact recovery with very high probability. We discuss an implementation for a low-speed A/D converter for 60 GHz UWB received signal. Moreover, we analyze the bit error rate (BER) performance for BPSK modulation under RAKE reception. Simulation results show that in the single antenna pair system model, sampling rate can be reduced to 2.2% with 0.3dB loss of BER performance if the input sparsity is less than 1%. Consequently, the implementation cost of ADC is significantly reduced.