Multipath Delay Estimation for Frequency Hopping Systems

The multipath delay estimation problem for a slow frequency hopping system is studied. High resolution delay estimation algorithms are proposed by exploiting invariance structures in the data packet. The proposed approach converts the problem of delay estimation using temporally received packets to one of estimating directions-of-arrival in array processing. Two closed-form estimators are developed. The first algorithm is based on the use of a single invariance and applies the ESPRIT algorithm. The second approach utilizes multiple invariances, and enforces the Cayley-Hamilton constraint in the signal subspace. It is shown, via an analysis of acquisition time, that the use of multiple invariances significantly shortens the number of hops required for parameter identifiability. Simulation examples also demonstrate the advantage of exploiting multiple invariances.

[1]  Ananthram Swami,et al.  Channel estimation for frequency hopping systems , 1999, MILCOM 1999. IEEE Military Communications. Conference Proceedings (Cat. No.99CH36341).

[2]  L. B. Milstein,et al.  Theory of Spread-Spectrum Communications - A Tutorial , 1982, IEEE Transactions on Communications.

[3]  Bjorn Ottersten,et al.  Performance analysis of the total least squares ESPRIT algorithm , 1991, IEEE Trans. Signal Process..

[4]  Marvin K. Simon,et al.  Spread spectrum communications handbook (revised ed.) , 1994 .

[5]  Pou-Tou Sun,et al.  Hidden preamble detector for acquisition of frequency hopping multiple-access communication system , 1997 .

[6]  Y. A. Chau,et al.  Spectral-estimation-based acquisition for frequency-hopping spread-spectrum communications in a nonfading or Rayleigh-fading channel , 1997, IEEE Trans. Commun..

[7]  Thomas Kailath,et al.  ESPRIT-estimation of signal parameters via rotational invariance techniques , 1989, IEEE Trans. Acoust. Speech Signal Process..

[8]  L. Tong,et al.  Multichannel blind identification: from subspace to maximum likelihood methods , 1998, Proc. IEEE.

[9]  Thomas Kailath,et al.  ESPRIT-A subspace rotation approach to estimation of parameters of cisoids in noise , 1986, IEEE Trans. Acoust. Speech Signal Process..

[10]  T. Kailath,et al.  Estimation of Signal Parameters via Rotational Invariance Techniques - ESPRIT , 1986, MILCOM 1986 - IEEE Military Communications Conference: Communications-Computers: Teamed for the 90's.

[11]  Gene H. Golub,et al.  Matrix computations , 1983 .

[12]  Jaap C. Haartsen,et al.  The Bluetooth radio system , 2000, IEEE Personal Communications.

[13]  Lang Tong,et al.  Signal parameter estimation via the Cayley-Hamilton constraint , 2001, IEEE Signal Processing Letters.

[14]  F. R. Gantmakher.  The Theory of Matrices , 1984 .

[15]  Roger L. Peterson,et al.  Slow frequency-hop TDMA/CDMA for macrocellular personal communications , 1994, IEEE Personal Communications.

[16]  Andreas Polydoros,et al.  Hop-timing estimation for FH signals using a coarsely channelized receiver , 1994, Proceedings of MILCOM '94.

[17]  Andreas Polydoros,et al.  Hop-timing estimation for FH signals using a coarsely channelized receiver , 1996, IEEE Trans. Commun..

[18]  Ananthram Swami,et al.  Channel estimation for frequency hopping systems via multiple invariances , 2000, 2000 IEEE Wireless Communications and Networking Conference. Conference Record (Cat. No.00TH8540).

[19]  Björn E. Ottersten,et al.  Multiple invariance ESPRIT , 1992, IEEE Trans. Signal Process..

[20]  Michael D. Zoltowski,et al.  Closed-form multi-dimensional multi-invariance ESPRIT , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.