Second-Order Cyclostationarity of BT-SCLD Signals: Theoretical Developments and Applications to Signal Classification and Blind Parameter Estimation

Cyclostationarity: New trends and applications

“…In addition, cyclic statistics have been derived for: longcode DSSS signals [107], continuous phase modulated (CPM) signals [45,258], digital pulse streams modulated by cyclostationary sequences [268], multicarrier modulated signals [377], UWB signals [266,267,354], OFDM signals [59], OFDM and single carrier linearly digitally modulated signals [279], WiMAX and long-term evolution (LTE) OFDM signals [6], spatial multiplexing OFDM (SM-OFDM) and Alamouti coded OFDM (AL-OFDM) signals [181], block transmitted SCLD (BT-SCLD) signals [379], LTE SC-FDMA signals [178], LTE advanced signals [336], BOC signals [228], and global position system (GPS) signals [256].…”

On the Identification of SM and Alamouti-Coded SC-FDMA Signals: A Statistical-Based Approach

“…For example, the algorithm in [14], for single transmit antenna scenario, can be adapted to the scenario under consideration to estimate the block length. On the other hand, by using the properties that E{d 2 i (m)} = E{d 4 i (m)} = 0 for the symbols drawn from Ω-point constellation, Ω ≥ 4 [1], and that the signal, noise, and channel coefficients are independent, one can easily show that A SM r (τ ) = 0, ∀τ = 0, ..., N + ν − 1.…”

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

“…Due to the three Kronecker delta functions on the right-hand side of (16), the two summations over n 0 and n 1 are taken over a few non-zero terms only. For non-zero terms in (16), δ (mod (n 0 + n 1 , N )) = 0 and either δ(τ − (N + ν) + n 0 − n 1 ) = 0 or δ(τ + (N + ν) + n 0 − n 1 ) = 0.…”

“…is the signum function. Consequently, based on the above and (16), one can easily obtain the CCF expression in (17).…”