Blind and noncooperative identification of the transmission parameters of unknown communication signals has been employed both in military and civilian applications. Multiple-Input-Multiple-Output (MIMO) transmission systems emerging in the last decade pose new challenges to the signal identification systems, one of which is the identification of the Space-Time Block Code (STBC) used in the transmission. In this work, we present a novel STBC classification algorithm that exploits the joint wide sense cyclostationary characteristics of the coded transmit signals as discriminating features. Compared to existing algorithms, the proposed method can discriminate between a large number of different STBCs.

Automatic classification of the modulation type of an unknown communication signal is a challenging task, with applications in both commercial and military contexts, such as spectrum surveillance, cognitive radio, and electronic warfare systems. Most of the automatic modulation classification (AMC) algorithms found in the literature assume that the signal of interest has been transmitted using a single antenna. In this paper, a novel AMC algorithm for multiple input multiple output (MIMO) signals is proposed, which employs fourth-order cumulants as features for classification. First, perfect channel state information (CSI) is assumed. Subsequently, a case of more practical relevance is considered, where the channel matrix is unknown and has to be estimated blindly by employing independent component analysis (ICA). The performance of the proposed classification algorithm is investigated through simulations and compared with an average likelihood ratio test (ALRT) which can be considered as optimum in the Bayesian sense, but has a very high computational complexity.

Cyclostationary characteristics of communication signals can be exploited for performing various signal processing tasks. Receiver impairments that affect the cyclic statistics of signals may lead to a degradation in the performance of cyclostationarity-based signal processing algorithms. Inphase/ quadrature (I/Q) imbalance, oscillator phase noise, and random sampling jitter can be counted amongst the typical receiver impairments encountered in wireless communication systems. In this work, we investigate the effects of these nonidealities on the second-order cyclic statistics of baseband communication signals. General results are derived for arbitrary complex-valued (and possibly improper) signals, and examples are provided for cases of practical interest.

Cognitive radio is an enabling technology, which is expected to lead to a more efficient utilization of the available spectral resources due to its flexibility and its ability to sense its spectral environment. Recently, spectrum sensing methods based on exploiting the cyclostationary characteristics of communication signals have been drawing considerable interest. Imperfections in the cognitive radio receiver that affect the cyclic statistics of a signal of interest may lead to a degradation in the performance of spectrum sensing algorithms based on cyclostationarity. One such typical source of imperfection is random timing jitter in the sampling process. In this work, we explore the effect of random sampling jitter on the second order cyclostationary statistics of wide sense cyclostationary signals. General analytical expressions are derived for the cyclic statistics of sampled signals in the presence of sampling jitter and specific results are provided for two cases of interest. Subsequently, the effect of the jitter on a spectrum sensing algorithm is investigated via simulations.

Cyclostationarity is an inherent characteristic of many communication signals, which can be exploited for performing various signal processing tasks. Imperfections in the signal generation that affect the cyclic statistics of a signal may lead to a degradation in the performance of signal processing algorithms which make use of this cyclostationary behaviour. One typical source of imperfection encountered in digital signalling techniques is random jitter in the pulse timing. In this work, we systematically derive analytical expressions for the cyclic statistics of digital baseband signalling schemes in the presence of timing jitter, under the assumption that the generating wide sense cyclostationary data sequence and the stationary jitter process are statistically independent.

The spectrum pooling strategy allows a license owner to share a part of his licensed spectrum with a secondary wireless system (the rental system, RS) during its idle times. The coexistence of two mobile systems on the same frequency band poses many new challenges, one of which is the reliable extraction of the channel allocation information (CAI), i.e. the channel occupation of the licensed system (LS). This paper presents a strategy for the extraction of the CAI based on exploiting the distinct cyclostationary characteristics of the LS and RS signals and demonstrates, via simulations, its application on a specific spectrum pooling scenario, where the LS is a GSM network and the RS is an OFDM based WLAN system

The spectrum pooling concept allows the license owner of a spectral band to share a sporadically used part of his licensed spectrum with a renter system, until he needs it himself. For the smooth operation of a spectrum pooling system, the license owner has to have absolute priority to access the shared spectrum. This means that the renter system has to monitor the channel and extract the channel allocation information (CAI), i.e. it has to detect which parts of the shared spectrum the owner system accesses in order to vacate immediately the frequency bands being required by the license owner and to gain access to the frequency bands which the license owner has stopped using. The paper proposes exploiting the cyclostationary properties of the spectrum owner signal for the extraction of the CAI in a specific spectrum pooling scenario, where the license owner is a GSM network and the spectrum renter is an OFDM based WLAN system.

Reconfigurable software radio equipment is seen as the key technology in the evolution of mobile communications. One of the most important properties of a software radio terminal is that it is capable of using a wide range of air interface standards, providing a seamless interoperability between different standards and an enhanced roaming capability. One of the key functions supporting this multimode operation is the air interface recognition. A Software radio terminal has to be capable of detecting, recognizing and monitoring the air interfaces available in the frequency environment. In our paper, we propose exploiting the distinct cyclostationary properties of different air interface signals as features for air interface recognition.