Fundamental limits on time delay estimation in dispersed spectrum cognitive radio systems

In this paper, fundamental limits on time delay estimation are studied for cognitive radio systems, which facilitate opportunistic use of spectral resources. First, a generic Cramer-Rao lower bound (CRLB) expression is obtained in the case of unknown channel coefficients and carrier-frequency offsets (CFOs) for cognitive radio systems with dispersed spectrum utilization. Then, various modulation schemes are considered, and the effects of unknown channel coefficients and CFOs on the accuracy of time delay estimation are quantified. Finally, numerical studies are performed in order to verify the theoretical analysis. © 2006 IEEE

Range estimation in multicarrier systems in the presence of interference: Performance limits and optimal signal design

Cataloged from PDF version of article.Theoretical limits on time-of-arrival (equivalently, range) estimation are derived for multicarrier systems in the presence of interference. Specifically, closed-form expressions are obtained for Cramer-Rao bounds (CRBs) in various scenarios. In addition, based on CRB expressions, an optimal power allocation (or, spectrum shaping) strategy is proposed. This strategy considers the constraints not only from the sensed interference level but also from the regulatory emission mask. Numerical results are presented to illustrate the improvements achievable with the optimal power allocation scheme, and a maximum likelihood time-of-arrival estimation algorithm is studied to assess the effects of the proposed approach in practical estimators. © 2011 IEEE

Economic Galileo E5 Receiver

The Galileo system introduces an extremely wideband civil E5 signal for high precision navigation. The structure of the receiver for the E5 signal is complicated due to the signal complexity and the large bandwidth. It is possible to process the whole E5 signal or process separately E5a and E5b parts combining obtained results afterwards (we call here such method as piece-wise processing). The second procedure has three times worse standard deviation of the pseudorange then first one. The main goal of the paper is to present a design of an E5 receiver which we will call the economic E5 receiver (ecoE5). It is built from jointly controlled correlators for the processing of the E5a and E5b signals which are parts of the E5 signal. Control of these partial E5a and E5b correlators is realized by only one delay and one phase lock loops. The performance, i.e. the pseudorange noise and multipath errors, of the receiver equipped with the ecoE5, is only slightly worse (the standard deviation of the pseudorange noise is 10 - 20% larger) than the performance of the optimal E5 receiver and it is much better than the performance of the receiver combining the piecewise (E5a and E5b) measurements. The ecoE5 receiver hardware demands are about one quarter of the hardware demands of the classical E5 receiver

Theoretical Limits on Time Delay Estimation for Ultra-Wideband Cognitive Radios

In this paper, theoretical limits on time delay estimation are studied for ultra-wideband (UWB) cognitive radio systems. For a generic UWB spectrum with dispersed bands, the Cramer-Rao lower bound (CRLB) is derived for unknown channel coefficients and carrier-frequency offsets (CFOs). Then, the effects of unknown channel coefficients and CFOs are investigated for linearly and non-linearly modulated training signals by obtaining specific CRLB expressions. It is shown that for linear modulations with a constant envelope, the effects of the unknown parameters can be mitigated. Finally, numerical results, which support the theoretical analysis, are presented.Comment: IEEE ICUWB 200

Optimal channel switching for average capacity maximization

Optimal channel switching is proposed for average capacity maximization in the presence of average and peak power constraints. A necessary and sufficient condition is derived in order to determine when the proposed optimal channel switching approach can or cannot outperform the optimal single channel approach, which performs no channel switching. Also, it is stated that the optimal channel switching solution can be realized by channel switching between at most two different channels. In addition, a low-complexity optimization problem is derived in order to obtain the optimal channel switching solution. Numerical examples are provided to exemplify the derived theoretical results. © 2014 IEEE

Time-of-arrival estimation in OFDM-based cognitive radio systems

Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 2010.Thesis (Master's) -- Bilkent University, 2010.Includes bibliographical references leaves 56-60.Cognitive radio (CR) systems can efficiently utilize the radio spectrum due to their ability to sense environmental conditions and adapt their communications parameters (such as power, carrier frequency, and modulation) so as to enable dynamic reuse of the available spectrum. In this thesis, theoretical limits on time-of-arrival (TOA) estimation are derived for CR systems in the presence of interference. Specifically, closed form expressions are obtained for Cramer-Rao bounds (CRBs) on TOA estimation in orthogonal frequency division multiplexing (OFDM) based CR systems in various scenarios. Based on the CRB expressions, an optimal power allocation strategy that provides the best possible TOA estimation accuracy is proposed. This strategy considers the constraints imposed by regulatory emission mask and the sensed interference spectrum. The maximum likelihood (ML) TOA estimator is derived for an OFDM-based signalling scheme, and its performance is investigated against the theoretical limits offered by the CRB expressions. In addition, numerical results for the CRBs and ML TOA estimator are obtained and the effects of the optimal power allocation strategy on the accuracy of ML TOA estimator are examined in the absence/presence of interference. The use of optimal power allocation strategy instead of the conventional power assignment scheme is demonstrated to provide significant gains in terms of the TOA estimation accuracy. Analysis of the performance sensitivity of the optimal power allocation strategy to the uncertainty in spectrum estimation is performed, and the performance of optimal power allocation is observed to be consistently superior to that of the uniform power allocation even for substantially high values of spectral estimation errors.Karışan, YasirM.S

Performance Analysis of Dispersed Spectrum Cognitive Radio Systems

Dispersed spectrum cognitive radio systems represent a promising approach to exploit the utilization of spectral resources to full extent. Therefore, the performance analysis of such systems is conducted in this research. The Average symbol error probability of dispersed spectrum cognitive radio systems is derived for two cases: where each channel realization experiences independent and dependent Nakagami-m fading, respectively. In addition, the derivation is extended to include the effects of modulation type and order by considering M-PSK and M-QAM modulation schemes. We then study the impacts of topology on the effective transport capacity performance of ad hoc dispersed spectrum cognitive radio systems where the nodes assume 3- dimensional (3D) configurations. We derive the effective transport capacity considering a cubic grid distribution. In addition, numerical results are presented to demonstrate the effects of topology on the effective transport capacity of ad hoc dispersed cognitive radio systems

Cognitive-radio systems for spectrum, location, and environmental awareness

In order to perform reliable communications, a system needs to have sufficient information about its operational environment, such as spectral resources and propagation characteristics. Cognitive-radio technology has capabilities for acquiring accurate spectrum, location, and environmental information, due to its unique features such as spectrum, location, and environmental awareness. The goal of this paper is to give a comprehensive review of the implementation of these concepts. In addition, the dynamic nature of cognitive-radio systems - including dynamic spectrum utilization, transmission, the propagation channel, and reception - is discussed, along with performance limits, challenges, mitigation techniques, and open issues. The capabilities of cognitive-radio systems for accurate characterization of operational environments are emphasized. These are crucial for efficient communications, localization, and radar systems. © 2010 IEEE

Source localization via time difference of arrival

Accurate localization of a signal source, based on the signals collected by a number of receiving sensors deployed in the source surrounding area is a problem of interest in various fields. This dissertation aims at exploring different techniques to improve the localization accuracy of non-cooperative sources, i.e., sources for which the specific transmitted symbols and the time of the transmitted signal are unknown to the receiving sensors. With the localization of non-cooperative sources, time difference of arrival (TDOA) of the signals received at pairs of sensors is typically employed. A two-stage localization method in multipath environments is proposed. During the first stage, TDOA of the signals received at pairs of sensors is estimated. In the second stage, the actual location is computed from the TDOA estimates. This later stage is referred to as hyperbolic localization and it generally involves a non-convex optimization. For the first stage, a TDOA estimation method that exploits the sparsity of multipath channels is proposed. This is formulated as an f1-regularization problem, where the f1-norm is used as channel sparsity constraint. For the second stage, three methods are proposed to offer high accuracy at different computational costs. The first method takes a semi-definite relaxation (SDR) approach to relax the hyperbolic localization to a convex optimization. The second method follows a linearized formulation of the problem and seeks a biased estimate of improved accuracy. A third method is proposed to exploit the source sparsity. With this, the hyperbolic localization is formulated as an an f1-regularization problem, where the f1-norm is used as source sparsity constraint. The proposed methods compare favorably to other existing methods, each of them having its own advantages. The SDR method has the advantage of simplicity and low computational cost. The second method may perform better than the SDR approach in some situations, but at the price of higher computational cost. The l1-regularization may outperform the first two methods, but is sensitive to the choice of a regularization parameter. The proposed two-stage localization approach is shown to deliver higher accuracy and robustness to noise, compared to existing TDOA localization methods. A single-stage source localization method is explored. The approach is coherent in the sense that, in addition to the TDOA information, it utilizes the relative carrier phases of the received signals among pairs of sensors. A location estimator is constructed based on a maximum likelihood metric. The potential of accuracy improvement by the coherent approach is shown through the Cramer Rao lower bound (CRB). However, the technique has to contend with high peak sidelobes in the localization metric, especially at low signal-to-noise ratio (SNR). Employing a small antenna array at each sensor is shown to lower the sidelobes level in the localization metric. Finally, the performance of time delay and amplitude estimation from samples of the received signal taken at rates lower than the conventional Nyquist rate is evaluated. To this end, a CRB is developed and its variation with system parameters is analyzed. It is shown that while with noiseless low rate sampling there is no estimation accuracy loss compared to Nyquist sampling, in the presence of additive noise the performance degrades significantly. However, increasing the low sampling rate by a small factor leads to significant performance improvement, especially for time delay estimation

Programming techniques for efficient and interoperable software defined radios

Recently, Software-Dened Radios (SDRs) has became a hot research topic in wireless communications eld. This is jointly due to the increasing request of reconfigurable and interoperable multi-standard radio systems able to learn from their surrounding environment and efficiently exploit the available frequency spectrum resources, so realizing the cognitive radio paradigm, and to the availability of reprogrammable hardware architectures providing the computing power necessary to meet the tight real-time constraints typical of the state-of-art wideband communications standards. Most SDR implementations are based on mixed architectures in which Field Programmable Gate Arrays (FPGA), Digital Signal Processors (DSP) and General Purpose Processors (GPP) coexist. GPP-based solutions, even if providing the highest level of flexibility, are typically avoided because of their computational inefficiency and power consumption. Starting from these assumptions, this thesis tries to jointly face two of the main important issues in GPP-based SDR systems: the computational efficiency and the interoperability capacity. In the first part, this thesis presents the potential of a novel programming technique, named Memory Acceleration (MA), in which the memory resources typical of GPP-based systems are used to assist central processor in executing real-time signal processing operations. This technique, belonging to the classical computer-science optimization techniques known as Space-Time trade-offs, defines novel algorithmic methods to assist developers in designing their software-defined signal processing algorithms. In order to show its applicability some "real-world" case studies are presented together with the acceleration factor obtained. In the second part of the thesis, the interoperability issue in SDR systems is also considered. Existing software architectures, like the Software Communications Architecture (SCA), abstract the hardware/software components of a radio communications chain using a middleware like CORBA for providing full portability and interoperability to the implemented chain, called waveform in the SCA parlance. This feature is paid in terms of computational overhead introduced by the software communications middleware and this is one of the reasons why GPP-based architecture are generally discarded also for the implementation of narrow-band SCA-compliant communications standards. In this thesis we briefly analyse SCA architecture and an open-source SCA-compliant framework, ie. OSSIE, and provide guidelines to enable component-based multithreading programming and CPU affinity in that framework. We also detail the implementation of a real-time SCA-compliant waveform developed inside this modified framework, i.e. the VHF analogue aeronautical communications transceiver. Finally, we provide the proof of how it is possible to implement an efficient and interoperable real-time wideband SCA-compliant waveform, i.e. the AeroMACS waveform, on a GPP-based architecture by merging the acceleration factor provided by MA technique and the interoperability feature ensured by SCA architecture