Dimitris A. Pados

Extracting Spread-Spectrum Hidden Data From Digital Media

We consider the problem of extracting blindly data embedded over a wide band in a spectrum (transform) domain of a digital medium (image, audio, video). We develop a novel multicarrier/signature iterative generalized least-squares (M-IGLS) core procedure to seek unknown data hidden in hosts via multicarrier spread-spectrum embedding. Neither the original host nor the embedding carriers are assumed available. Experimental studies on images show that the developed algorithm can achieve recovery probability of error close to what may be attained with known embedding carriers and host autocorrelation matrix.

Software-defined underwater acoustic networks: toward a high-rate real-time reconfigurable modem

We review and discuss the challenges of adopting software-defined radio principles in underwater acoustic networks, and propose a software-defined acoustic modem prototype based on commercial off-the-shelf components. We first review current SDR-based architectures for underwater acoustic communications. Then we describe the architecture of a new software-defined acoustic modem prototype, and provide performance evaluation results in both indoor (water tank) and outdoor (lake) environments. We present three experimental testbed scenarios that demonstrate the real-time reconfigurable capabilities of the proposed prototype and show that it exhibits favorable characteristics toward spectrally efficient cognitive underwater networks, and high data rate underwater acoustic links. Finally, we discuss open research challenges for the implementation of next-generation software-defined underwater acoustic networks.

Compressed-Sensed-Domain L 1 -PCA Video Surveillance

We consider the problem of foreground and background extraction from compressed-sensed (CS) surveillance videos that are captured by a static CS camera. We propose, for the first time in the literature, a principal component analysis (PCA) approach that computes directly in the CS domain the low-rank subspace of the background scene. Rather than computing the conventional L2-norm-based principal components, which are simply the dominant left singular vectors of the CS-domain data matrix, we compute the principal components under an L1-norm maximization criterion. The background scene is then obtained by projecting the CS measurement vector onto the L1 principal components followed by total-variation (TV) minimization image recovery. The proposed L1-norm procedure directly carries out low-rank background representation without reconstructing the video sequence and, at the same time, exhibits significant robustness against outliers in CS measurements compared to L2-norm PCA. An adaptive CS- L1-PCA method is also developed for low-latency video surveillance. Extensive experimental studies described in this paper illustrate and support the theoretical developments.

Scalable video transmission over wireless DS-CDMA channels using minimum TSC spreading codes

In this letter, we report results on the relative performance of scalable video transmission via a single-rate or a multirate direct sequence code-division multiple-access channel using minimum total squared correlation spreading codes. Our findings demonstrate the superiority of the multirate system on a wide range of chip rates of practical interest.

L 1 -fusion: Robust linear-time image recovery from few severely corrupted copies

We address the problem of recovering an unknown image of interest, when only few, severely corrupted copies are available. We employ, for the first time in the literature, corruption-resistant L1-Principal-Components (L1-PCs) of the image data-set at hand. Specifically, the calculated L1-PCs are used for reliability-based patch-by-patch fusion of the corrupted image copies into a single high-quality representation of the original image (L1-fusion). Our experimental studies illustrate that the proposed method offers remarkable recovery results for several common corruption types, even under high corruption rate, small number of copies, and varying corruption type among copies. An additional theoretical contribution of this work is that the L1-PC of a data matrix of non-negative entries (e.g., image data) is for the first time shown to be optimally calculable with complexity linear to the matrix dimensions - as of now, the fastest-known optimal algorithm is of polynomial complexity. In the light of this result, L1-fusion is carried out with linear cost comparable to that of the simple copy-averaging alternative. The linear-low cost of L1-fusion allows for the recovered image to be, optionally, further refined by means of sophisticated single-image restoration techniques.

Addressing next-generation wireless challenges with commercial software-defined radio platforms

We review commercially available software- defined radio platforms and classify them with respect to their ability to enable rapid prototyping of next-generation wireless systems. In particular, we first discuss the research challenges imposed by the latest software-defined radio enabling technologies including both analog and digital processing hardware. Then we present the state-of-the-art commercial software-defined radio platforms, describe their software and hardware capabilities, and classify them based on their ability to enable rapid prototyping and advance experimental research in wireless networking. Finally, we present three experimental testbed scenarios (wireless terrestrial, aerial, and underwater) and argue that the development of a system design abstraction could significantly improve the efficiency of the prototyping and testbed implementation process.

Multiuser CDMA Signal Extraction

We consider the problem of extraction on wireless direct-sequence code-division multiple-access (DS-CDMA) systems. We develop an iterative least-squares-type algorithm that extracts the information symbols of the multiple concurrent DS-CDMA users and assumes no knowledge of either the signature waveforms or the channel state. The proposed scheme utilizes a novel initialization step that is based on auxiliary-vector (AV) subspace decomposition. Simulation studies evaluate the performance of the proposed extraction procedure in realistic data limited environments and show that, for observation records of sufficient length, information data extraction can be achieved with probability of error rather close to what may be attained with known signatures and channel state. *Corresponding author.

Adaptive assignment of binary user spreading codes in DS-CDMA systems

In direct-sequence code-division-multiple-access (DS-CDMA) systems, the pre-detection signal-to-interference-plus-noise ratio (SINR) at the output of the single-user minimum-mean-square-error (MMSE) filter is a function of the specific user spreading code (signature). In this paper, we consider the adaptive optimization of the user signature assignment such that the output SINR of the MMSE filter is maximized under a transmitter power constraint. In the context of binary signatures, the complexity of the signature optimization procedure is exponential in the processing gain. A low-cost suboptimum adaptive binary signature assignment algorithm is derived based on conditional optimization principles. We use this algorithm to design an efficient system-wide multiuser adaptive signature set assignment scheme. The performance of the proposed scheme is evaluated under asynchronous multipath fading DS-CDMA channel models and is compared to the performance of systems with arbitrarily chosen signature sets.

Decoding of framewise compressed-sensed video via interframe total variation minimization

Abstract. Compressed sensing is the theory and practice of sub-Nyquist sampling of sparse signals of interest. Perfect reconstruction may then be possible with significantly fewer than the Nyquist required number of data. In this work, we consider a video system where acquisition is performed via framewise pure compressed sensing. The burden of quality video sequence reconstruction falls, then, solely on the decoder side. We show that effective decoding can be carried out at the receiver/decoder side in the form of interframe total variation minimization. Experimental results demonstrate these developments.

Capacity, throughput, and delay of slotted ALOHA DS-CDMA links with adaptive space-time auxiliary-vector receivers

We investigate the user capacity, throughput, and delay characteristics of a mobile slotted ALOHA direct-sequence code-division-multiple-access (DS-CDMA) link with dedicated signatures under multipath fading and packet-rate adaptive antenna array signal reception. For a given system transmission bit rate, the packet size is designed to be sufficiently small to conform with the coherence time of the channel. Then, on an individual packet-by-packet basis, a phase-ambiguous spatial-temporal channel estimate is produced by a blind (unsupervised) eigensubspace procedure. The space-time channel estimate is phase corrected via a few pilot packet mid-amble bits and used for joint spatial-temporal multiple-access-interference suppression according to the principles of auxiliary-vector filtering. Subsequently, packet success probabilities are derived in the presence or absence of forward error correction and are used to evaluate the throughput and delay characteristics of the link.