On optimizing fractional lower order covariance based synchronization method for random communication systems

Abstract

Previously, the concept of Pilot Assisted Synchronization (PAS) and Fractional Lower Order Covariance (FLOC) has been incorporated together to synchronize alphastable noise based communication system which gave birth to Synchronized Random Communication Systems (SRCS). In this paper, an optimization criterion, i.e. FLOC Margin, has been proposed to improve the efficiency of the Fractional Lower Order Covariance based Correlators (FLOCCs) at the receiver side, hence, resulting in enhanced Bit Error Rate (BER) performance of SRCS. Since, the characteristic exponent and impulsiveness parameter are mainly responsible in generating and shaping up the required pilot sequence, therefore, the effects of these parameters on BER performance has also been observed by fluctuating them in their respective ranges. It has been shown that the proposed optimization criterion increases the BER efficiency of SRCS and also reveals the specific range of the characteristic exponent and impulsiveness parameter which can be exploited to achieve the optimum performance.

Blind recognition of alpha‐stable random carrier signals by an eavesdropper in random communication systems

“…β heavily skewed either towards right or left (β not skewed). These observations related to FLOAC of αstable noise signal X, in [23,26], have helped to optimise the detection process of synchronised RCSs [27].…”

Role of Fractional Powers in Manuevering the Fractional Lower-Order Auto-Covariance of Symmetric Alpha-Stable Noise Signals

“…However, [ ] and [ ] has been computed for specific values of fractional powers, i.e. a = b= [5,[7][8][9]13], and the effects of maneuvering the fractional powers for its complete range on [ ] has not been analyzed yet. where is the dispersion parameter of the α-stable noise signal X and is the dispersion parameter of the gaussian noise G.…”

“…The FLOAC has helped in proposing the first synchronization for RCSs [7,8] where the capability of impulsive and skewness parameters to fluctuate the FLOAC was observed [9]. However, no detailed study has been carried out then to explore the role of fractional powers in maneuvering the FLOAC of SαS signals.…”

Role of Fractional Powers in Maneuvering the Fractional Lower-Order Auto-Covariance of Skewed Alpha-Stable Signals in Gaussian Noise Environment

“…However, [ ] and [ ] has always been exploited for fixed value of fractional powers which is usually fixed as a = b= [5,[7][8][9]13] and the complete effects of maneuvering the fractional powers on [ ] has not been analyzed yet.…”

“…The FLOAC has helped in establishing as well as optimizing synchronization method in RCSs [7,8] which was established after analyzing the role of impulsive and skewness parameters in fluctuating the FLOAC [9]. However, no detailed study has been carried out yet to explore the role of fractional powers in maneuvering the FLOAC.…”