On the classification of binary space shift keying modulation

Blind and non-cooperative classification of the modulation employed in signals originating from unknown or partly known sources has widespread applications in civilian and military contexts. One of the most recent and interesting approaches to digital modulation which has been enabled by multiantenna transceivers is the spatial modulation, where the indices of the transmit antennas activated in a given symbol period are utilized to transmit information bits. Clearly, existing modulation classification methods, designed for the identification of conventional modulation types, are not capable of classifying the family of spatially modulated signals that make use of the space dimension. In this work, for the first time in the literature, a modulation classification method is proposed for a modulation type belonging to the family of Spatial Modulations: the Binary Space Shift Keying modulation (BSSK

Joint space time block code and modulation classification for MIMO systems

Non-cooperative identification of unknown communication signals is a popular research area with widespread civilian and military applications. Multiple input multiple output (MIMO) systems employing multi-antenna transmission pose new challenges to signal identification systems, such as the classification of the employed space time block code (STBC) and modulation in the presence of the self-interference inherent to the multi-antenna transmission. In the existing literature, these two classification problems have been handled separately, despite the fact that they are interrelated. This letter presents a novel approach to MIMO signal identification by considering the modulation type and the STBC classification tasks as a joint classification problem

Joint modulation classification and antenna number detection for MIMO systems

Noncooperative classification of the modulation type of communication signals finds application in both civilian and military contexts. Existing modulation classification methods for multiple-input multiple-output (MIMO) communication systems commonly require a priori information on the number of transmit antennas employed by the multiantenna transmitter, which, in most of the noncooperative scenarios involving modulation classi- fication, is unknown and needs to be blindly extracted from the received signal. Since the problems of MIMO modulation classification and detection of the number of transmit antennas are highly coupled, we propose a decision theoretic approach for spatial multiplexing MIMO systems that considers these two tasks as a joint multiple hypothesis testing problem. The proposed method exhibits a high performance even in moderate to low SNR regimes while requiring no a priori knowledge of the channel state information and the noise variance

Cyclostationarity based blind block timing estimation for alamouti coded mimo signals

Blind parameter estimation algorithms provide a powerful tool for application scenarios where the use of training or pilot sequences is not desirable, e.g., in order to improve the bandwidth efficiency of the transmission, or in non-cooperative scenarios where such sequences are not available to the receiver. This letter proposes a blind block timing estimation algorithm for Alamouti space-time block coded signals exploiting the second order joint cyclostationary characteristics of the received signal vector, which is induced by the space time block coding operation performed by the transmitter. The proposed algorithm outperforms the existing algorithms by a wide margin

Sequential decision fusion for abnormality detection via diffusive molecular communications

This paper considers the task of abnormality detection in a fluid medium, employing a molecular communications (MC) based network of nanoscale sensors. This task entails sensing, detection and reporting of abnormal changes in the environment that may characterize a disorder or an abnormal event. Such distributed detection (DD) problems are of paramount interest, especially in applications such as health monitoring, disease diagnosis, targeted drug delivery, environmental sensing and monitoring, contaminant detection and removal, and environmental remediation. This letter proposes, for the first time in the literature, to employ a sequential probability ratio test based approach to the decision fusion in diffusive MC based DD. The proposed approach leads to considerable gains in the average number of samples required for the decision compared to its fixed-sample size counterparts, resulting in a significant improvement in the average decision delay. In the investigated DD scenarios, we observe savings of up to 50% in the number of samples required for decision fusion

On the cyclostationary statistics of ultra-wideband signals in the presence of timing and frequency jitter

Cyclostationarity is an inherent characteristic of many man-made communication signals, which, if properly recognized, can be exploited for performing various signal-processing tasks. Determining the cyclostationary characteristics of a signal of interest is the first step in the design of signal processing systems exploiting this cyclostationary behaviour. This paper investigates the cyclostationary statistics of various signalling schemes employed in ultra-wideband (UWB) communication systems. Analytical expressions are derived for the cyclic autocorrelation and spectral correlation density functions in the presence of random timing and frequency jitter, which are characterized by discrete-time stationary random processes with known distribution functions

On the effects of random timing jitter on spectrum sensing algorithms based on cyclostationarity

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 interest. In practice, imperfections in the signal generation or reception may affect the cyclic statistics of a signal of interest, leading to a degradation in the performance of cyclostationarity-exploiting spectrum sensing schemes based on an ideal signal model. A typical source of imperfection is random timing jitter, which can occur at the transmitter side, most notably in the form of pulse timing jitter for digitally modulated signals, or at the receiver side in the form of sampling jitter. In this work, we explore the effect of random timing jitter on the second order cyclostationary statistics of wide sense cyclostationary signals. General analytical expressions are derived for the cyclic statistics of signals in the presence of sampling and pulse timing jitter and specific results are provided for cases of practical interest. Subsequently, the effect of the both jitter types on a cyclostationary-based spectrum sensing algorithm is investigated via simulations.Publisher's Versio

On the effect of random sampling jitter on cyclostationarity based spectrum sensing algorithms for cognitive radio

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.Publisher's Versio

On the spectral correlation of UWB impulse radio signals

Cyclostationarity is an inherent characteristic of many communication signals, which can be exploited for performing various signal processing tasks. Determining the cyclic statistics of a signal of interest is often necessary in the design of signal processing systems exploiting this cyclostationary behaviour. This work investigates the second order cyclic statistics of various signalling schemes employed in ultra wideband impulse radio systems. Analytical expressions are derived for the cyclic autocorrelation and spectral correlation density functions.Publisher's Versio