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We prove, for the first time in the literature of communication theory and machine learning, the equivalence of joint maximum-likelihood (ML) optimal channel estimation and data detection (JOCEDD) to the problem of finding the L 1 -norm principal components of a real-valued data matrix. Optimal algorithms for L 1 -norm principal component analysis (PCA) are therefore direct solvers to the problem of interest, thus the proposed JOCEDD approach requires a polynomial number of operations. To avoid high computational costs incurred by the exact calculation of optimal L 1 principal components, we implement an efficient bit flipping-based algorithm for L 1 -norm PCA in a software-defined radio. In particular, we carry out experiments with two radios that operate at Wi-Fi frequencies in a multipath indoor radio environment and have no direct line-of-sight. We apply L 1 -norm PCA for JOCEDD over short frames that are transmitted over the single-input single-output communication link. We compare the performance of supervised data-aided channel estimation techniques versus JOCEDD in terms of bit-error-rate and demonstrate the superiority of the proposed approach across a wide range of signal-to-noise ratios.

There is an emerging need for high-rate underwater acoustic (UW-A) communication platforms to enable a new generation of underwater monitoring applications including video streaming. At the same time, modern UW-A communication architectures need to be flexible to adapt and optimize their communication parameters in real time based on the environmental conditions. Existing UW-A modems are limited in terms of achievable data rates and ability to adapt the protocol stack in real time. To overcome this limitation, we present the design, implementation, and experimental evaluation of a new high-rate software-defined acoustic modem (SDAM) with real-time adaptation capabilities for UW-A communications. We introduce new physical-layer adaptation mechanisms that enable either joint adaptation of communication parameters such as modulation constellation and channel coding rate or seamless switching between different communication technologies such as orthogonal-frequency-division-multiplexing and direct-sequence-spread-spectrum. The performance of the proposed SDAM has been evaluated in both indoor (water tank) and outdoor (lake) environments. We demonstrated that the SDAM achieves 104 kbit/s with bit-error-rate (BER) of 2 × 10-5, 208 kbit/s with BER of 10-3, and 260 kbit/s with BER of 10-2 in real time over a 200 m horizontal link at a very-shallow lake environment.

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.

Terahertz (THz)-band (0.1 THz to 10 THz) communication is envisioned as a key technology to meet the demand for faster, more ubiquitous wireless communication networks. For many years, the lack of compact, fast and efficient ways to generate, modulate, detect and demodulate THz-band signals has limited the feasibility of such communication systems. Recently, major progress within different device technologies is finally closing the so-called THz gap. For the time being, communication testbeds have been developed at sub-THz frequencies, i.e., at or near the boundary with millimeter-wave communication systems. Nonetheless, higher carrier frequencies and their associated bandwidth are needed to meet the demand for much higher data rates. In this paper, the TeraNova platform, i.e., the first integrated testbed for ultra-broadband wireless communications at true THz-band frequencies, is presented. The system consists of a transmitter and a receiver based on Schottky-diode frequency multiplying and mixing chains able to up & down-convert an information-bearing intermediate frequency (IF) signal up to 40 GHz-wide between 1 and 1.05 THz, i.e., the first absorption-defined transmission window above 1 THz. Guided by the experimental characterization of the THz channel in terms of path-loss and noise, tailored framing, time synchronization, channel estimation and single- and multi-carrier modulation techniques are implemented in software and realized by a state-of-the-art arbitrary waveform generator and a digital storage oscilloscope at the transmitter and the receiver, respectively. Experimental results are presented herein to highlight the opportunities and challenges to unleash the potential of the THz band.

We consider the problem of interference avoidance via all-spectrum digital waveform design in wireless communication links that operate in multipath fading environments. Specifically, we select a square-root raised cosine pulse-shaping signal that occupies all-hardware accessible frequency bandwidth. We propose an algorithm that optimizes a sequence of $L$ sign/phase-shifted repeats of the basic shaping pulse to form the all-spectrum digital waveform that will carry our information symbols. The sequence can take values from either binary or quaternary alphabets. We propose to optimize the specific values of the sign/phase shift sequence via bit flipping such that the signal-to-interference-plus-noise ratio (SINR) at the output of the max-SINR linear receiver is maximized at any given time. The complexity of the proposed algorithm is O( $L$ 3) and is independent of the alphabet size. Simulation studies demonstrate that the proposed digital waveform designs achieve practically the same SINR post-filtering performance with max-SINR optimal waveforms designed via exhaustive search.

We introduce maximum-SINR, sparse-binary waveforms that modulate data information symbols over the entire continuum of the available/device-accessible spectrum. We present an optimal algorithm that designs the proposed waveforms by maximizing the signal-to-interference-plus-noise ratio (SINR) at the output of the maximum- SINR linear filter at the receiver. In addition, we propose a suboptimal, computationally-efficient algorithm. Simulation studies compare the proposed sparse-binary waveforms with their conventional non-sparse binary counterparts and demonstrate their superior SINR performance. The post-filtering SINR and bit-error rate (BER) improvements attained by the proposed waveforms are also experimentally verified in a software-defined radio testbed operating in multipath laboratory environment, in the presence of colored interference.

We consider a secondary multi-hop cognitive radio network with decentralized control that operates cognitively to coexist with primary users. We propose a new spread-spectrum management paradigm, in which, unlike mainstream dynamic spectrum access research, digital waveforms are designed to occupy the entire available spectrum, and to adaptively track the interference profile at the receiver to maximize the link capacity while avoiding interference to primary users. In this context, we study the problem of maximizing the network throughput of a multi-hop network through joint routing and spread-spectrum channelization. We first propose a centralized formulation of the network control problem. We then propose an algorithm that can be seen as a distributed localized approximation of the throughput-maximizing policy. We refer to the proposed jointly-designed routing and code-division channelization algorithm as ROCH (Routing and cOde-division CHannelization). Specifically, power and spreading code are jointly selected to maximize the pre-detection secondary \mathrm{SINR} while providing quality of service guarantees to on-going primary and secondary transmissions, while the routing algorithm dynamically selects relays based on the network traffic dynamics and on the achievable data rates on different secondary links. We study the throughput and delay performance of ROCH through a extensive simulation experiments, which demonstrate the appeal of the proposed framework through significant performance gains compared to baseline solutions.

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.

In this paper, we consider a heterogeneous ad-hoc network where primary users may cooperate with cognitive radio (CR) users for the transmission of their data. We propose a new cooperation protocol that allows CR users to relay primary user signals in exchange for some spectrum. The spectrum released by primary users is used by CR users for their own data transmission. The proposed protocol maximizes the primary user power savings and the CR users' own data transmission rate. In addition, it provides more robust (potentially continuous) service for CR users, compared to the conventional practice in cognitive networks where cognitive users transmit in the spectrum holes of primary users (i.e., their service is interrupted when primary users need to transmit and no spectrum holes are available). More specifically, we propose a CR user power allocation scheme that maximizes the rate of transmission of CR user own data, for any given CR user power budget and a given bandwidth released from the primary user. Furthermore, we determine a range of possible transmission power levels that can be used by the primary user during cooperation without sacrificing its target transmission rate, and we derive a necessary condition on the quality of the channel between the primary user and the CR user that enables cooperation. Extensive numerical and simulation studies illustrate our theoretical developments and show that cooperation between a primary and CR user may lead, for example, to up to 80% savings of primary user power when compared to a noncooperation scheme at the same transmission power level.

We consider the problem of cognitive code-division channelization (simultaneous power and code-channel allocation) for secondary transmission links co-existing with an unknown primary code-division multiple-access (CDMA) system. We first develop a blind primary-user identification scheme to detect the binary code sequences (signatures) utilized by primary users. To create a secondary link we propose two alternative procedures -one of moderate and one of low computational complexity- that optimize the secondary transmitting power and binary code-channel assignment in accordance with the detected primary code channels to avoid "harmful" interference. At the same time, the optimization procedures guarantee that the signal-to-interference-plus-noise ratio (SINR) at the output of the maximum SINR linear secondary receiver is no less than a certain threshold to meet secondary transmission quality of service (QoS) requirements. The extension of the channelization problem to multiple secondary links is also investigated. Simulation studies presented herein illustrate the theoretical developments.

We consider the problem of simultaneous power and code-channel allocation for a secondary transmitter/receiver pair coexisting with a primary code-division multiple-access (CDMA) system. Our objective is to find the optimum transmitting power and code sequence of the secondary channel that maximize the signal-to-interference-plus-noise ratio (SINR) at the output of the maximum SINR linear receiver, while at the same time the SINR of all primary channels at the output of their max-SINR receiver is maintained above a certain threshold. This is a non-convex NP-hard optimization problem. We propose a novel feasible suboptimum solution using semidefinite programming. Simulation studies illustrate the theoretical developments.

In this paper we develop a new analytical methodology for the evaluation of the outage probability of cooperative decode-and-forward (DF) automatic-repeat-request (ARQ) relaying under packet-rate fading (fast fading or block fading) channels, where the channels remain fixed within each ARQ transmission round, but change independently from one round to another. We consider a single relay forwarding Alamouti-based retransmission signals in the cooperative ARQ scheme. In particular, (i) we derive a closed-form asymptotically tight (as SNR → ∞) approximation of the outage probability; (ii) we show that the diversity order of the DF cooperative ARQ relay scheme is equal to 2L-1, where L is the maximum number of ARQ (re)transmissions; and (iii) we develop the optimum power allocation for the DF cooperative ARQ relay scheme. The closed-form expression clearly shows that the achieved diversity is partially due to the DF cooperative relaying and partially due to the fast fading nature of the channels (temporal diversity). With respect to power allocation, it turns out that the proposed optimum allocation scheme depends only on the link quality of the channels related to the relay, and compared to the equal power allocation scheme it leads to SNR performance gains of more than 1 dB. Numerical and simulation studies illustrate the theoretical developments.

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.

We present the first complete software-based framework for real-time experimental evaluation of secondary multi-hop cognitive underlay networks with decentralized control. We build a $7$-node software-defined radio testbed and implement a distributed algorithm that maximizes the secondary network throughput, while at the same time avoids interference to primary users through joint Routing and cOde-waveform CHannelization (ROCH). ROCH is implemented using GNU Radio and Universal Software Radio Peripherals ($\mathrm{USRP-N210s}$). The implementation of ROCH is facilitated by the architectural abstractions of a novel radio framework, referred to as RcUBe, that provides reconfigurability at the PHY, MAC, and network layers of the protocol stack.

Existing commercial wireless systems are mostly hardware-based, and rely on closed and inflexible designs and architectures. Moreover, despite recent significant algorithmic developments in cross-layer network adaptation and resource allocation, existing network architectures are unable to incorporate most of these advancements. While software-defined radio (SDR) was envisioned as a new paradigm promising radical runtime adaptation through all layers of the networking protocol stack, the reality of the state-of-the-art in wireless networking practice is far from having fulfilled such promise of fast and intelligent reconfigurability and adaptability. Networking research based on the “software-defined radio” paradigm has suffered almost invariably from the lack of adequate and coherently designed abstractions to (i) define networking protocols and their cross-layer interactions across all layers of the protocol stack; (ii) define decision-making algorithms to control such interactions. To address this need, we introduce RcUBe (Real-time Re-configurable Radio), a novel architectural radio framework based on abstractions that offer real-time reconfigurability and optimization capabilities at the PHY, MAC, and network layers of the protocol stack. Unlike state-of-the-art solutions, RcUBe offers a structured methodology at variable levels of abstraction to accommodate implementations of a wide range of network architectures and protocols and complex decision-making in a modular, platform-independent way. RcUBe provides these features through a design structured into four distinct, but interacting planes, namely decision, control, data, and register plane. The broad capabilities of the proposed framework are demonstrated on a network level software-defined radio setup through a range of experiments where RcUBe is used to implement various reconfigurable functionalities of a wireless system at the PHY, MAC, and network layer.

We implement and real-time demonstrate for the first time ROCH; a distributed cognitive algorithm that maximizes secondary network throughput, while at the same time avoids interference to primary users through joint Routing and cOde-waveform CHannelization. ROCH performance is evaluated on a $7$-node software-defined radio testbed using the open-source radio framework, GNU Radio, and Universal Software Radio Peripherals (USRP-N$210$s). The implementation of ROCH is facilitated by the architectural abstractions of the RcUBe radio framework, that provides real-time reconfigurability at the PHY, MAC, and network layers of the protocol stack.

In this paper, we consider the transmission of video over wireless direct-sequence code-division multiple access (DS-CDMA) channels. A layered (scalable) video source codec is used. The layers may be time-multiplexed and transmitted over a single CDMA channel or each layer can be transmitted over a different CDMA channel. For the latter case, spreading codes of different lengths are allowed for each CDMA channel (multirate CDMA). Thus, a different number of chips per bit can be used for the transmission of each scalable layer. For a given fixed energy value per chip and chip rate, the selection of a spreading code length affects the transmitted energy per bit and bit rate for each scalable layer. An MPEG-4 source encoder is used to provide a two-layer signal-to-noise-ratio scalable bit stream. Each of the two layers is channel-coded using rate-compatible punctured convolutional codes. Then, the data are interleaved, spread, carrier-modulated, and transmitted over the wireless channel. A multipath Rayleigh fading channel model is assumed. At the other end, the signal is collected by an antenna array front. After carrier demodulation, multiple-access-interference suppressing despreading is performed using adaptive space-time auxiliary-vector (AV) filters. The choice of the AV space-time receiver is dictated by realistic channel fading rates that limit the data record available for receiver adaptation and redesign. Our experimental results demonstrate the effectiveness of such a multirate DS-CDMA system for wireless video transmission.

In this paper we design, implement, and experimentally evaluate a wireless software-defined radio platform for cognitive channelization in the presence of narrowband or wideband primary stations. Cognitive channelization is achieved by jointly optimizing the transmission power and the waveform channel of the secondary users. The process of joint resource allocation requires no a-priori knowledge of the transmission characteristics of the primary user and maximizes the signal-to- interference-plus-noise ratio (SINR) at the output of the secondary receiver. This is achieved by designing waveforms that span the whole continuum of available/device-accessible spectrum, while satisfying a peak power constraint for the secondary users and an interference temperature (IT) constraint for the primary users. We build a four-node software-defined radio testbed and experimentally demonstrate in an indoor laboratory environment the theoretical concepts of all-spectrum cognitive channelization in terms of pre-detection SINR and bit- error-rate (BER) at both primary and secondary receivers.

We propose a receiver configuration and we develop a software-defined-radio testbed for real-time cognitive underwater multiple-access communications. The proposed receiver is fully reconfigurable and executes (i) all-spectrum cognitive channelization and (ii) combined synchronization, channel estimation, and demodulation. Online (real-time) experimental field studies using in-house built modems demonstrate our theoretical developments and show that cognitive channelization is a powerful proposition for underwater communications that leads to significant improvement of spectrum utilization. Even in the absence of interference, due to the noise characteristics of the acoustic channel, cognitive channelization offers significant performance improvements in terms of receiver pre-detection signal-to-interference-plus-noise-ratio and bit-error-rate.

We consider the problem of embedding multiuser data in digital media (such as images, video sequences, audio) with minimum perceived distortion. In this direction, we find the orthonormal set of embedding carriers that achieves maximum sum signal-to-interference-plus-noise ratio (sum-SINR) at the output of the receiver linear filters for any fixed embedding amplitude values. Then, for any given total embedding distortion constraint, we calculate the optimal multicarrier assignment and embedding amplitude values that maximize the sum capacity of the embedding process. Experimental results presented herein for multiuser data embedding in images demonstrate the effectiveness of the proposed methods.

Cooperative communication has emerged as a new wireless network communication concept, in which parameter optimization such as power budget and time allocation plays an important role in cooperative relaying protocol designs. While most existing works on cooperative relaying protocol designs considered equal-time allocation scenario, i.e. equal time duration is assigned to each source and each relay, in this work we intend to design and optimize cooperative communication protocols by exploring all possible variations in time and power domains. We jointly optimize the power and time allocations for the cooperative relaying protocol such that the outage probability of the protocol is minimized. Specifically, for any given time allocation, we are able to determine the corresponding optimum power allocation analytically with a closed-form expression. We also show that in order to minimize the outage probability of the protocol, one should always allocate more energy and time to the source than the relay. Extensive numerical and simulation studies illustrate our theoretical developments.

In this paper, we systematically analyze the outage probability performance of the distributed cooperative multicast with randomized orthogonal space-time codes (OSTC) for wireless multimedia networks. The distributed cooperative multicast protocol with randomized OSTC enables users who successfully decode signals from base station or access point serving as relays to forward the signals to other users, and consequently the overall performance of wireless multimedia multicast can be greatly improved. We derive a closed-form expression for the outage probability for the distributed cooperative multicast with randomized OSTC. To get more insight, we further develop an asymptotically tight approximation for the outage probability which reveals the diversity order of the protocol as K + 1, where K is the size of the randomized OSTC used in the protocol. Based on the asymptotically tight approximation of the outage probability, we are able to determine an optimum power allocation for the distributed cooperative multicast protocol. It shows that in a statistic sense, we should allocate 1/(K + 1) of the total power budget to the BS/AP and evenly distribute the rest for the users as relaying power. Numerical and simulation results validate our theoretical development.

We consider arbitrary Hybrid-Automatic-Repeat-Request (H-ARQ) wireless links over quasi-static Rayleigh fading channels. In this paper, we translate the repeat-request advantage of the intended receiver over potential eavesdroppers to link security. In particular, with statistical-only knowledge of the channel and noise, we find for the first time in the literature the optimal power allocation sequence over the H-ARQ rounds that maximizes the outage probability of eavesdroppers for any given target outage probability of the trusted receiver. Simulation studies demonstrate orders of magnitude difference in outage probability between eavesdroppers and intended receiver.

We developed a new spread-spectrum management paradigm in which, unlike mainstream dynamic spectrum access research, digital waveforms are (i) designed to occupy the entire available spectrum and (ii) adaptively track the interference profile at the receiver to maximize link capacity while avoiding interference to existing users. In this context, we studied the problem of maximizing the network throughput of a multi-hop network through joint routing and spread-spectrum channelization. We first presented a centralized formulation of the network control problem. We then developed an algorithm that can be seen as a distributed localized approximation of the throughput-maximizing policy. We refer to the proposed jointly-designed routing and code-division channelization algorithm as ROCH (Routing and cOde-division CHannelization).

Pados, D. A., Medley, M. J., and Batalama, S. N., Adaptive Antenna Array Receivers for Spread-Spectrum Signals in Non-Gaussian Noise, Digital Signal Processing 11 (2001) 144–158 We consider the problem of recovering a spread-spectrum (SS) signal in the presence of unknown highly correlated spread-spectrum interference and impulsive noise. In terms of basic system and signal model considerations, we assume availability of a narrowband adaptive antenna array that experiences additive white Gaussian noise in time and across elements, as well as impulsive disturbance with direction-of-arrival (DOA) that changes at the chip rate. The space–time receiver design developed in this work is characterized by the following attributes: (i) Adaptive interference suppression is pursued in the joint space–time domain. (ii) An adaptive parametric nonlinear front end offers effective suppression of impulsive disturbances at low computational cost. (iii) An adaptive auxiliary-vector linear filter postprocessor offers effective, low-complexity suppression of SS interferers and leads to superior bit-error-rate (BER) performance under rapid, short-data-record system adaptation. Numerical and simulation comparisons with plain and outlier resistant space–time minimum-variance-distortionless-response (MVDR) filtering procedures are included to illustrate and support the theoretical developments.

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.

Direct-sequence/code-division multiple-access (DS/CDMA) communication systems equipped with adaptive antenna arrays offer the opportunity for jointly effective spatial and temporal (code) multiple-access interference (MAI) and channel noise suppression. This work focuses on the development of fast joint space-time (S-T) adaptive optimization procedures that may keep up with the fluctuation rates of multipath fading channels. Along these lines, the familiar S-T RAKE processor is equipped with a single orthogonal S-T auxiliary vector (AV) selected under a maximum magnitude cross-correlation criterion. Then, blind joint spatial/temporal MAI and noise suppression with one complex S-T degree of freedom can be performed. This approach is readily extended to cover blind processing with multiple AVs and any desired number of complex degrees of freedom below the S-T product. A sequential procedure for conditional AV weight optimization is shown to lead to superior bit-error-rate (BER) performance when rapid system adaptation with limited input data is sought. Numerical studies for adaptive antenna array reception of multiuser multipath Rayleigh-faded DS/CDMA signals illustrate these theoretical developments. The studies show that the induced BER can be improved by orders of magnitude, while at the same time significantly lower computational optimization complexity is required in comparison with joint S-T minimum-variance distortionless response or equivalent minimum mean-square-error conventional filtering means.

Wireless physical-layer security is an emerging field of research aiming at preventing eavesdropping in an open wireless medium. In this paper, we propose a novel waveform design approach to minimize the likelihood that a message transmitted between trusted single-antenna nodes is intercepted by an eavesdropper. In particular, with knowledge first of the eavesdropper's channel state information (CSI), we find the optimum waveform and transmit energy that minimize the signal-to-interference-plus-noise ratio (SINR) at the output of the eavesdropper's maximum-SINR linear filter, while at the same time provide the intended receiver with a required pre-specified SINR at the output of its own max-SINR filter. Next, if prior knowledge of the eavesdropper's CSI is unavailable, we design a waveform that maximizes the amount of energy available for generating disturbance to eavesdroppers, termed artificial noise (AN), while the SINR of the intended receiver is maintained at the pre-specified level. The extensions of the secure waveform design problem to multiple intended receivers are also investigated and semidefinite relaxation (SDR) -an approximation technique based on convex optimization- is utilized to solve the arising NP-hard design problems. Extensive simulation studies confirm our analytical performance predictions and illustrate the benefits of the designed waveforms on securing single-input single-output (SISO) transmissions and multicasting.

We consider the problem of joint admission control and resource allocation in a secondary code-division network coexisting with a narrow-band primary system. Our objective is to find the maximum number of admitted secondary links and then find the optimal transmitting powers and code sequences of those secondary links such that the total energy consumption of the secondary network is minimized subject to the conditions that primary interference temperature constraints, secondary Signal-to-Interference-plus-Noise Ratio (SINR) constraints and secondary peak power constraints are all satisfied. This is an NP-hard optimization problem which motivates the development of efficient suboptimal algorithms. We propose a novel iterative algorithm to solve this problem in a computationally efficient manner. Numerical results demonstrate that the proposed algorithm provides excellent solutions that result in large admitted percentage of secondary links and high energy efficiency.

We study a framework that captures the interdependencies between spreading channelization and routing for a secondary multi-hop cognitive radio network that operates cognitively to coexist with primary users. We consider interactions between dynamic routing and code-division channelization functionalities for cognitive radio networks. With this respect, we study the effect of joint routing, spreading code and power allocation on the network throughput. A solution for joint routing and spread-spectrum channelization is proposed as a localized approximation of the throughput-maximizing problem. Specifically, power and spreading code are allocated to guarantee the quality of service of the on-going primary and secondary transmissions, while the routing algorithm dynamically selects relays based on the network traffic dynamics and on the achievable data rates on different secondary links.

We consider the problem of passive spread-spectrum steganalysis where the objective is to decide the presence or absence of spread-spectrum hidden data in a given image (a binary hypothesis testing problem). Unlike conventional feature-based approaches, we describe an unsupervised (blind) low-complexity approach based on generalized least-squares principles that may enable rapid high-volume image processing. Extensive experiments on image sets and comparisons with existing steganalysis techniques demonstrate most satisfactory classification performance measured in probability of correct detection versus induced false alarm rate.

We cover five general areas in this report: (1) design and optimize cooperative automatic-repeat-request (ARQ) relaying protocol for airborne networks; (2) optimize power assignment for hybrid ARQ protocols in airborne networks; (3) design and optimize differential cooperative relaying protocols for airborne networks; (4) design and optimize multi-source multi destination relaying schemes for airborne networks; and (5) design and optimize cognitive code-division channelization for airborne networks.

Two feedforward neural structures intended for binary hypothesis testing are considered. The first structure, FFS1, is a tandem structure, while the second structure, FFS2, involves cumulative feedforward feedback. Both parametric and robust designs for the two structures are considered and analyzed in terms of induced false alarm and power probabilities. The inferiority of the FFS1 is rigorously proved in terms of the rate with which the induced power probability increases with respect to the number of the neural elements. Asymptotic results are presented, as well as numerical results, with emphasis on the Gaussian and location parameter nominal hypotheses model. Learning algorithms for the parameter involved in the robust network designs are discussed as well. >

A cognitive radio network with decentralized control (i.e., a cognitive ad hoc network) is considered in this demonstration. The demo implements a decentralized and localized algorithm for throughputmaximization through joint routing and interference-avoiding waveform selection. The algorithm adapts to time-varying traffic demands, interference profile, and network topology to locally maximize the achievable data rate while avoiding harmful interference to co-located primary or secondary users. The prototype is based on a cross-layer protocol stack implemented in Python, which leverages GNU Radio for adaptive signal generation on a USRP2 software-defined-radio platform.

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. Cooperative transmission exploits spatial diversity without multiple antennas at each node to increase capacity with reliability guarantees. This idea is particularly attractive in wireless environments due to the diverse channel quality and the limited energy and bandwidth resources. With cooperation, source node and relay node cooperatively transmit data to the destination. In such a virtual multiple antenna transmission system, the capacity of the cooperative link is much larger than that of the direct link from source to destination. In this paper, we will study decentralized and localized algorithms for joint dynamic routing, relay assignment, and spectrum allocation under a distributed and dynamic environment.

A distributed joint routing and spectrum sharing algorithm for video streaming applications over cognitive radio ad hoc networks is proposed in this article. The proposed cross-layer control scheme dynamically allocates routes, spectrum and power to maximize the network throughput under the constraints posed by delay-sensitive video applications. The algorithm evaluates the expected delay of competing flows in single-hop and two-hop networks considering the time-varying spectrum condition and occupancy, traffic characteristics, and the condition of queues at intermediate nodes. Simulation results show that the proposed algorithm significantly reduces the packet loss rate and improves the average peak signal-to-noise ratio (PSNR) of the received video streams.

In this paper, a new analytical approach is developed for the evaluation of the outage probability of decode-and-forward (DF) automatic-repeat-request (ARQ) relaying under packet-rate fading (fast fading) channels. Based on this approach, a closed-form asymptotically tight (as SNR → ∞) approximation of the outage probability is derived, and the diversity order of the DF cooperative ARQ relay scheme is shown to be equal to 2L - 1, where L is the maximum number of ARQ retransmissions. The closed-form expression clearly shows that the achieved diversity is partially due to the DF cooperative relaying and partially due to the fast fading nature of the channels (temporal diversity). Numerical and simulation studies illustrate the theoretical developments.

In this paper, a new analytical approach is developed for the evaluation of the outage probability of decode-and-forward (DF) automatic-repeat-request (ARQ) relaying under packet-rate fading (fast fading) channels. Based on this approach, a closed-form asymptotically tight (as SNR →∞ ) approximation of the outage probability is de- rived, and the diversity order of th eD F cooperative ARQ relay scheme is shown to be equal to 2L − 1, where L is the maximum number of ARQ retransmissions. The closed-form expression clearly shows that the achieved diversity is partially due to the DF cooperative relaying and par- tially due to the fast fading nature of the channels (temporal diversity). Numerical and simulation studies illustrate the theoretical developments.

Derived from statistical conditional optimization criteria, the auxiliary-vector (AV) detection algorithm starts from the target vector and adding non-orthogonal auxiliary vector components generates an infinite sequence of tests that converges to the ideal matched filter (MF) processor for any positive definite input autocorrelation matrix. When the input autocorrelation matrix is replaced by a conventional sample-average estimate, the algorithm effectively generates a sequence of estimators of the ideal matched filter that offer exceptional bias/covariance balance for any given finite-size observation data record. In this work, the AV algorithm is evaluated on collected airborne phased-array radar data from the MCARM program and is seen to outperform in probability of detection (for any given false alarm rate) all known and tested adaptive detectors (for example AMF, generalized likelihood ratio test, the multistage Wiener filter algorithm, etc.).

In this paper we develop a novel iterative-least-squares-type method that identifies the population size of direct-sequence CDMA signal mixtures without any knowledge about the signatures of the active spread-spectrum signals in the system or the channel state and in the absence of pilot signaling (training sequence). Simulation studies demonstrate the performance of the proposed method and offer favorable comparisons with corresponding schemes based on the conventional Akaike information criterion, the minimum description length criterion, as well as their more recent modified versions.

We consider the problem of signature waveform design for code division multiplexing in wireless collaborative relay networks. In contract to conventional randomly chosen orthogonal codes, we develop an adaptive signature design strategy under the maximum predetection signal-to-interference-plus-noise-ratio (SINR) criterion. We evaluate numerically and by simulations the bit error rate (BER) and outage probability of cooperative wireless transmissions over code division multiplexing channels. Two basic decode-and-forward relay network architectures are considered and state-of-the-art performance is demonstrated.

We consider the problem of signature waveform design for code division medium-access-control (MAC) of wireless sensor networks (WSN). In contract to conventional randomly chosen orthogonal codes, an adaptive signature design strategy is developed under the maximum pre-detection SINR (signal to interference plus noise ratio) criterion. The proposed algorithm utilizes slowest descent cords of the optimization surface to move toward the optimum solution and exhibits, upon eigenvector decomposition, linear computational complexity with respect to signature length. Numerical and simulation studies demonstrate the performance of the proposed method and offer comparisons with conventional signature code sets.

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.

We propose an iterative generalized least squares procedure to recover unknown messages hidden in image hosts via spread-spectrum embedding. Neither the original host nor the embedding signature is assumed available. We demonstrate that for hidden messages of sufficient length (data sample support), recovery can be achieved with probability of error close to what may be attained with known embedding signature and known original host autocorrelation matrix. For small hidden messages, the signature estimate calculated by the iterative generalized least squares procedure can be fed as initial value to a (computationally costly) expectation-maximization signature identification scheme that we derive. Message recovery can again be carried out successfully by means of a linear sample-matrix-inversion minimum-mean-square-error receiver.

n this paper, we consider the transmission of video over wireless direct-sequence code-division multiple access (DS-CDMA) channels. A layered (scalable) video source codec is used and each layer is transmitted over a different CDMA channel. Spreading codes with different lengths are allowed for each CDMA channel (multirate CDMA). Thus, a different number of chips per bit can be used for the transmission of each scalable layer. For a given fixed energy value per chip and chip rate, the selection of a spreading code length affects the transmitted energy per bit and bit rate for each scalable layer. An MPEG-4 source encoder is used to provide a two-layer SNR scalable bitstream. Each of the two layers is channel-coded using Rate-Compatible Punctured Convolutional (RCPC) codes. Then, the data are interleaved, spread, carrier-modulated and transmitted over the wireless channel. A multipath Rayleigh fading channel is assumed. At the other end, we assume the presence of an antenna array receiver. After carrier demodulation, multiple-access-interference suppressing despreading is performed using space-time auxiliary vector (AV) filtering. The choice of the AV receiver is dictated by realistic channel fading rates that limit the data record available for receiver adaptation and redesign. Indeed, AV filter short-data-record estimators have been shown to exhibit superior bit-error-rate performance in comparison with LMS, RLS, SMI, or 'multistage nested Wiener' adaptive filter implementations. Our experimental results demonstrate the effectiveness of multirate DS-CDMA systems for wireless video transmission.

The value of bottom-up and robust neural network designs is demonstrated, as well as the performance superiority of recurrent neural structures over feedforward neural architectures. Along these lines, two neural structures are considered, one feedforward and one recurrent, whose objective is binary hypothesis testing. The first, FFS1, is a tandem feedforward structure, whereas the second, FFS2, is recurrent and involves cumulative forward feedback. Both parametric and robust designs for the two structures are considered and analyzed in terms of induced false alarm and power probabilities, and the inferiority of the FFS1 is rigorously proven in terms of the rate with which the induced power probability increases with the number of the neural elements. Asymptotic results are presented, as well as numerical results, with emphasis on the Gaussian and location parameter nominal hypotheses model, that exhibit the superiority of the robust designs clearly. Learning algorithms for the parameters involved in the robust network designs are also discussed. >

We extend our previous work on joint source-channel coding to scalable video transmission over wireless direct-sequence code-division-multiple-access (DS-CDMA) multipath fading channels. A SNR scalable video coder is used and unequal error protection (UEP) is allowed for each scalable layer. At the receiver-end an adaptive antenna array auxiliary-vector (AV) filter is utilized that provides space-time RAKE-type processing and multiple-access interference suppression. The choice of the AV receiver is dictated by realistic channel fading rates that limit the data record available for receiver adaptation and redesign. Our problem is to allocate the available bit rate of the user of interest between source and channel coding and across scalable layers, while minimizing the end-to-end distortion of the received video sequence. The optimization algorithm that we propose utilizes universal rate-distortion characteristic curves that show the contribution of each layer to the total distortion as a function of the source rate of the layer and the residual bit error rate (the error rate after channel coding). These plots can be approximated using appropriate functions to reduce the computational complexity of the solution.

In this paper we address the problem of navigation data demodulation by an adaptive GPS receiver that utilizes a bank of single-satellite linear-tap-delay filters and employs antenna-array reception. The presence of an antenna array allows the receiver to operate in the spatial domain in addition to the temporal (code) domain. We investigate disjoint-domain as well as joint-domain space-time GPS signal processing techniques and we consider design criteria of conventional matched-filter (MF) type, minimum-variance-distortionless-response (MVDR) type and auxiliary-vector (AV) type. The proposed structures utilize filters that operate at a fraction of the navigation data bit period (1 msec) and are followed by soft-decision detectors. Soft decisions taken over a navigation data bit period are then combined according to a simple combining rule. Simulation results illustrate the bit-error-rate (BER) performance of the investigated design alternatives.

Summarization: Derived from statistical conditional optimization criteria, the auxiliary-vector (AV) detection algorithm starts from the target vector and adding non-orthogonal auxiliary vector components generates an infinite sequence of tests that converges to the ideal matched filter (MF) processor for any positive definite input autocorrelation matrix. When the input autocorrelation matrix is replaced by a conventional sample-average estimate, the algorithm effectively generates a sequence of estimators of the ideal matched filter that offer exceptional bias/covariance balance for any given finite-size observation data record. In this work, the AV algorithm is evaluated on collected airborne phased-array radar data from the MCARM program and is seen to outperform in probability of detection (for any given false alarm rate) all known and tested adaptive detectors (for example AMF, generalized likelihood ratio test, the multistage Wiener filter algorithm, etc.). Παρουσιάστηκε στο: Radar Conference

This paper considers the problem of blindly extracting data embedded over a wide band in a spectrum (transform) domain of a digital medium (image, audio, video). We first develop a multi-signature iterative generalized least-squares (M-IGLS) core procedure to seek unknown data hidden in hosts via multi-signature direct-sequence spread-spectrum embedding. Neither the original host nor the embedding signatures are assumed available. Then, cross-correlation enhanced M-IGLS (CC-M-IGLS), a procedure described herein in detail that is based on statistical analysis of repeated independent M-IGLS processing of the host, is seen to offer most effective hidden message recovery. Experimental studies on images show that the proposed CC-M-IGLS algorithm can achieve recovery probability of error close to what may be attained with known embedding signatures and host autocorrelation matrix.