Michael J. Medley

Cross-Layer Routing and Dynamic Spectrum Allocation in Cognitive Radio Ad Hoc Networks

Throughput maximization is one of the main challenges in cognitive radio ad hoc networks, where the availability of local spectrum resources may change from time to time and hop by hop. For this reason, a cross-layer opportunistic spectrum access and dynamic routing algorithm for cognitive radio networks is proposed, which is called the routing and dynamic spectrum-allocation (ROSA) algorithm. Through local control actions, ROSA aims to maximize the network throughput by performing joint routing, dynamic spectrum allocation, scheduling, and transmit power control. Specifically, the algorithm dynamically allocates spectrum resources to maximize the capacity of links without generating harmful interference to other users while guaranteeing a bounded bit error rate (BER) for the receiver. In addition, the algorithm aims to maximize the weighted sum of differential backlogs to stabilize the system by giving priority to higher capacity links with a high differential backlog. The proposed algorithm is distributed, computationally efficient, and has bounded BER guarantees. ROSA is shown through numerical model-based evaluation and discrete-event packet-level simulations to outperform baseline solutions, leading to a high throughput, low delay, and fair bandwidth allocation.

ROSA: distributed joint routing and dynamic spectrum allocation in cognitive radio ad hoc networks

Throughput maximization is one of the main challenges in cognitive radio ad hoc networks, where local spectrum resources may change from time to time and hop-by-hop. For this reason, a cross-layer opportunistic spectrum access and dynamic routing algorithm for cognitive radio networks is proposed, called ROSA (ROuting and Spectrum Allocation algorithm). Through local control actions, ROSA aims at maximizing the network throughput by performing joint routing, dynamic spectrum allocation, scheduling, and transmit power control. Specifically, the algorithm dynamically allocates spectrum resources to maximize the capacity of links without generating harmful interference to other users while guaranteeing bounded BER for the receiver. In addition, the algorithm aims at maximizing the weighted sum of differential backlogs to stabilize the system by giving priority to higher-capacity links with high differential backlog. The proposed algorithm is distributed, computationally efficient, and with bounded BER guarantees. ROSA is shown through discrete-event packet-level simulations to outperform baseline solutions leading to a high throughput, low delay, and fair bandwidth allocation.

Narrow-band interference excision in spread spectrum systems using lapped transforms

In order to mitigate narrow-band interference in spread spectrum communications systems, novel communications receivers incorporating transform domain filtering techniques are designed. In this paper, lapped transforms are used to transform the received data signal to the transform domain wherein adaptive excision is performed. Transform domain detection algorithms, which yield bit decisions based on the remaining signal energy, are analyzed and, together with excision, are employed on a block-by-block basis to suppress single-tone and narrow-band Gaussian interference. System performance is analytically quantified in terms of the overall system bit-error rate (BER). Subsequent results are presented for a variety of channel conditions and compared to those obtained using excision algorithms based on orthonormal block transforms (Medley 1995). These results demonstrate the improved performance and increased robustness with respect to jammer frequency and bandwidth of lapped transform domain excision techniques relative to similar algorithms based on nonweighted block transforms.

Optimal Signature Design for Spread-Spectrum Steganography

For any given host image or group of host images and any (block) transform domain of interest, we find the signature vector that when used for spread-spectrum (SS) message embedding maximizes the signal-to-interference-plus-noise ratio (SINR) at the output of the corresponding maximum-SINR linear filter. We establish that, under a (colored) Gaussian assumption on the transform domain host data, the same derived signature minimizes host distortion for any target message recovery error rate and maximizes the Shannon capacity of the covert steganographic link. Then, we derive jointly optimal signature and linear processor designs for SS embedding in linearly modified transform domain host data and demonstrate orders of magnitude improvement over current SS steganographic practices. Optimized multisignature/multimessage embedding in the same host data is studied as well

Subspace Direction Finding With an Auxiliary-Vector Basis

We develop a new subspace direction-of-arrival (DOA) estimation procedure that utilizes a noneigenvector basis. Computation of the basis is carried out by a modified version of the orthogonal auxiliary-vector (AV) filtering algorithm. The procedure starts with the linear transformation of the array response scanning vector by the input autocorrelation matrix. Then, successive orthogonal maximum cross-correlation auxiliary vectors are calculated to form a basis for the scanner-extended signal subspace. As a performance evaluation example, our studies for uncorrelated sources demonstrate a gain in the order of 15 dB over MUSIC, 7 dB over ESPRIT, and 3 dB over the grid-search maximum likelihood DOA estimator at probability of resolution 0.9 with a ten-element array and reasonably small observation data records. Results for correlated sources are reported as well

Antenna diversity for an OFDM system in a fading channel

This paper explores antenna diversity issues for orthogonal frequency division multiplexing (OFDM) in frequency flat and selective fading environment using three combining methods-maximal ratio combining (MRC), equal gain combining (EGC), and selection combining (SC). For OFDM, diversity combining can be done on individual subcarriers (narrowband combining) or on the entire OFDM symbol (wideband combining). For narrowband combining, OFDM diversity performance in a frequency selective channel can be predicted using flat fading analytic formulas, given that sub-channels are sufficiently narrowband. For wideband combining, an equivalent channel model based on the number of rays in the channel is formulated and an analytic expression for wideband SC is derived. Computer simulation is used to verify these expressions and methods to improve the three combining techniques are discussed, including metric filtering, selection grouping, and higher order selection diversity.

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.

Robust adaptive recovery of spread-spectrum signals with short data records

The problem under consideration is the adaptive reception of a multipath direct-sequence spread-spectrum (SS) signal in the presence of unknown correlated SS interference and additive impulsive noise. An SS receiver structure is proposed that consists of a vector of adaptive chip-based Hampel nonlinearities followed by an adaptive auxiliary-vector linear tap-weight filter. The nonlinear receiver front end adapts itself to the unknown prevailing noise environment providing robust performance over a wide range of underlying noise distributions. The adaptive auxiliary-vector linear tap-weight filter allows rapid SS interference suppression with a limited data record. Numerical and simulation studies under finite-data-record system adaptation show significant improvement in bit-error-rate performance over the conventional linear minimum variance-distortionless-response (MVDR) SS receiver or conventional MVDR filtering preceded by vector adaptive chip-based nonlinear processing.

Rapid combined synchronization/demodulation structures for DS-CDMA systems. I. Algorithmic developments

Blind adaptive linear receivers are considered for the demodulation of direct-sequence code-division multiple-access signals in asynchronous transmissions. The proposed structures are self-synchronized in the sense that adaptive synchronization and demodulation are viewed and treated as an integrated receiver operation. Two computationally efficient combined synchronization/demodulation schemes are proposed, developed, and analyzed. The first scheme is based on the principles of minimum-variance distortionless-response processing, while the second scheme follows the principles of auxiliary-vector filtering and exhibits enhanced performance in short data-record scenarios. In both cases, the resulting receiver is a linear structure of order exactly equal to the system processing gain. Simulation studies included in this paper demonstrate the coarse synchronization as well as the bit-error rate performance of the proposed strategies.

Spread Spectrum Visual Sensor Network Resource Management Using an End-to-End Cross-Layer Design

In this paper, we propose an approach to manage network resources for a direct sequence code division multiple access (DS-CDMA) visual sensor network where nodes monitor scenes with varying levels of motion. It uses cross-layer optimization across the physical layer, the link layer, and the application layer. Our technique simultaneously assigns a source coding rate, a channel coding rate, and a power level to all nodes in the network based on one of two criteria that maximize the quality of video of the entire network as a whole, subject to a constraint on the total chip rate. One criterion results in the minimal average end-to-end distortion amongst all nodes, while the other criterion minimizes the maximum distortion of the network. Our experimental results demonstrate the effectiveness of the cross-layer optimization.