Identification of SM-OFDM and AL-OFDM Signals Based on Their Second-Order Cyclostationarity

Abstract

Automatic signal identification (ASI) has important applications to both commercial and military communications, such as software defined radio, cognitive radio, spectrum surveillance and monitoring, and electronic warfare. While ASI has been intensively studied for single-input single-output systems, only a few investigations have been recently presented for multiple-input multiple-output systems. This paper introduces a novel algorithm for the identification of spatial multiplexing (SM) and Alamouti coded (AL) orthogonal frequency division multiplexing (OFDM) signals, which relies on the second-order signal cyclostationarity. Analytical expressions for the second-order cyclic statistics of SM-OFDM and AL-OFDM signals are derived and further exploited for the algorithm development. The proposed algorithm provides a good identification performance with low sensitivity to impairments in the received signal, such as phase noise, timing offset, and channel conditions.

36 pages, 14 figures, TVT2015

Cited by in corpus (4)

• Joint Blind Identification of the Number of Transmit Antennas and MIMO Schemes Using Gerschgorin Radii and FNN
• Blind Identification of SFBC-OFDM Signals Using Subspace Decompositions and Random Matrix Theory
• Blind Identification of SFBC-OFDM Signals Based on the Central Limit Theorem
• On the Identification of SM and Alamouti Coded SC-FDMA Signals: A Statistical-Based Approach