Recognition Among OFDM-Based Systems Utilizing Cyclostationarity-Inducing Transmission

This paper presents cyclostationarity-inducing transmission techniques that enable the receiver to distinguish among different systems employing OFDM (Orthogonal Frequency Division Multiplexing) as a common air interface. Several systems using different air interfaces may have different properties of cyclostationarity that can be utilized to distinguish among them. However, this is usually not possible when the same air interface is used. To address this problem for systems using OFDM as an air interface, we consider methods that induce different properties of cyclostationarity in the transmitter of different systems. Specifically, we configure the OFDM signal before transmission such that its cyclic autocorrelation function (CAF) has peaks at certain pre-chosen cycle frequencies. The difference in the cycle frequencies, at which the CAF peaks occur for the configured OFDM signals, is utilized to distinguish among several systems even when OFDM is used as a common air interface. Two configuration methods for the OFDM signal are proposed. The first proposed method inserts a specific preamble at the head of each OFDM frame. Each preamble is configured such that only a selected subset of subcarriers is used for transmission. A different subset of subcarriers results in the occurrence of CAF peaks at different cycle frequencies for the OFDM signal. The second proposed method is based on dedicating a few subcarriers in an OFDM frame to the transmission of specific signals so that the whole frame exhibits cyclostationarity at pre-chosen cycle frequencies. For this method, we introduce a method for generating signals on the dedicated subcarriers and describe their relation to the cycle frequencies of the configured OFDM frame. Both proposed methods are evaluated by computer simulation in a multipath Rayleigh fading environment. Simulation results show that system recognition based on the proposed methods exhibits excellent detection probability.