Space time block code classification for MIMO signals exploiting cyclostationarity

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

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

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

Spatial-Frequency Block Coding Automatic Recognition with Non-Gaussian Interference for Cognitive MIMO-OFDM Systems

Space-time/frequency block coding (STBCs/SFBCs) scheme is a crucial technique for enhancing the effectiveness and reliability of multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems with cognitive radio (CR) capability. Automatic recognition of STBCs/SFBCs is a prerequisite for achieving dynamic spectrum sharing in cognitive MIMO-OFDM systems. In contrast to existing works, this paper proposes a weighted cross-correlation function-based algorithm to recognize SFBCs for cognitive MIMO-OFDM systems with Gaussian noise and non-Gaussian impulsive interference. The proposed algorithm extracts the space-frequency redundancy information of different OFDM subcarriers on different receiver antenna pairs by using weighted cross-correlation functions. Then, the weighted cross-correlation feature vectors are constructed by exploiting the multi-antenna system so as to design the detection statistics and thresholds based on the central limit theorem. Finally, a decision tree method is adopted to discriminate between several SFBCs. The proposed algorithm does not require prior information such as channel coefficients, modulation schemes, noise power, or interference power. Simulation results show that the proposed algorithm is robust against non-Gaussian impulsive interference and achieves high recognition performance in the case of a small number of samples and a low signal-to-noise ratio. Index Terms-Cognitive radio, multiple-input multiple-output, non-Gaussian impulsive interference, orthogonal frequency division multiplexing, parameter recognition, space-frequency block coding

PERFORMANCE ANALYSIS OF DIFFERENT SCHEMES FOR TRANSMISSION OF WATERMARKED MEDICAL IMAGES OVER FADING CHANNELS

ABSTRACT Performance Analysis of Different Schemes for Transmission of Watermarked Medical images over Fading Channels Praveen Kumar Korrai In this thesis, we investigate different types of robust schemes for transmission of medical images with concealed patient information as a watermark. In these schemes, spatial domain digital watermarking technique is adapted to embed the patient information as a watermark into the lower order bits of the medical images to reduce the storage and transmission overheads. The watermark, which comprises text data, is encrypted to prevent unauthorized access of data. To enhance the robustness of the embedded information, the encrypted watermark is coded by concatenation of Reed Solomon (RS) and low density parity check (LDPC) codes. A robust scheme for transmission of watermarked images over impulsive noisy wireless channels is first proposed and its performance analyzed. In this scheme, the bursty wireless channel is simulated by adding impulse noise to the watermark embedded image. Furthermore, turbo channel coding is used to correct the transmission errors over impulsive noisy wireless channels. However, single input single output (SISO) channel capacity is not enough to provide modern wireless services such as data and multimedia messaging services. Further, it is not reliable due to multipath fading. To overcome these problems, a multiple-input multiple-output (MIMO) transmission scheme in which multiple antennas are used at both the transmitter and the receiver has emerged as one of the most significant technical breakthroughs in modern wireless communications. MIMO can improve the channel capacity and provide diversity gain. Hence, a scheme with a MIMO channel is proposed for the transmission of watermarked medical images over Rayleigh flat fading channels and its performance analyzed using MIMO maximum likelihood detector at the receiver. We present another scheme, namely, MIMO space frequency block coded OFDM (MIMO SFBC OFDM) in this thesis for transmission of watermarked medical images over Rayleigh fading channels to mitigate the detrimental effects due to frequency selective fading. The performance of this MIMO SFBC OFDM scheme is analyzed and compared with that of SISO-OFDM using minimum mean square error V-BLAST- based detection at the receiver. The efficacy of the different proposed schemes is illustrated through implementation results on watermarked medical images