On cyclostationary analysis of WiFi signals for direction estimation

Cyclostationary analysis is a powerful tool to study the Signal-Selective Direction Estimation (SSDE) problem as different types of wireless signals have different cyclostationary patterns. Generally speaking, each type of wireless signal has unique cyclic frequencies with the frequency-selective property, which distinguishes itself from other types of signals. The cyclostationary property of a signal may be induced by its modulation method, its carrier frequency, and/or its frame structure. In this paper, we study the cyclostationary property of IEEE 802.11 (WiFi) signals induced by their underlying OFDM frame structure, which includes pilots, cyclic prefix (CP), and preambles. We first analyze the pilot-induced, CP-induced, and preamble-induced cyclostationary properties of WiFi signals, respectively. We then derive their spectral correlation function (SCF) and investigate their applicability to solving the SSDE problem. Simulation results show that the pilot-induced cyclostationary property of WiFi signals is a promising feature that can be used to solve the SSDE problem.

[1]  Marcos E. Castro,et al.  CYCLOSTATIONARY DETECTION FOR OFDM IN COGNITIVE RADIO S YSTEMS , 2011 .

[2]  Anass Benjebbour,et al.  Cyclostationarity-Inducing Transmission Methods for Recognition among OFDM-Based Systems , 2008, EURASIP J. Wirel. Commun. Netw..

[3]  W. Gardner.  Exploitation of spectral redundancy in cyclostationary signals , 1991, IEEE Signal Processing Magazine.

[4]  Sachin Katti,et al.  PinPoint: Localizing Interfering Radios , 2013, NSDI.

[5]  Jie Xiong,et al.  ArrayTrack: A Fine-Grained Indoor Location System , 2011, NSDI.

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

[7]  Philippe Ciblat,et al.  OFDM System Identification for Cognitive Radio Based on Pilot-Induced Cyclostationarity , 2009, 2009 IEEE Wireless Communications and Networking Conference.

[8]  Yide Wang,et al.  An extended cyclic music algorithm , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[9]  Linda Doyle,et al.  Cyclostationary Signatures in Practical Cognitive Radio Applications , 2008, IEEE Journal on Selected Areas in Communications.

[10]  R. O. Schmidt,et al.  Multiple emitter location and signal Parameter estimation , 1986 .

[11]  Sachin Katti,et al.  DOF: a local wireless information plane , 2011, SIGCOMM 2011.

[12]  B. G. Agee,et al.  Cyclic MUSIC algorithms for signal-selective direction estimation , 1989, International Conference on Acoustics, Speech, and Signal Processing,.

[13]  Steven R. Schnur.  Identification and classification of OFDM based signals using preamble correlation and cyclostationary feature extraction , 2009 .

[14]  W. A. Brown,et al.  Computationally efficient algorithms for cyclic spectral analysis , 1991, IEEE Signal Processing Magazine.

[15]  Xianda Zhang,et al.  An improved signal-selective direction finding algorithm using second-order cyclic statistics , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.