Localization via ultra-wideband radios: a look at positioning aspects for future sensor networks

UWB technology provides an excellent means for wireless positioning due to its high resolution capability in the time domain. Its ability to resolve multipath components makes it possible to obtain accurate location estimates without the need for complex estimation algorithms. In this article, theoretical limits for TOA estimation and TOA-based location estimation for UWB systems have been considered. Due to the complexity of the optimal schemes, suboptimal but practical alternatives have been emphasized. Performance limits for hybrid TOA/SS and TDOA/SS schemes have also been considered. Although the fundamental mechanisms for localization, including AOA-, TOA-, TDOA-, and SS-based methods, apply to all radio air interface, some positioning techniques are favored by UWB-based systems using ultrawide bandwidths.     

Stochastic resonance in binary composite hypothesis-testing problems in the Neyman–Pearson framework

Performance of some suboptimal detectors can be enhanced by adding independent noise to their inputs via the stochastic resonance (SR) effect. In this paper, the effects of SR are studied for binary composite hypothesis-testing problems. A Neyman–Pearson framework is considered, and the maximization of detection performance under a constraint on the maximum probability of false-alarm is studied. The detection performance is quantified in terms of the sum, the minimum, and the maximum of the detection probabilities corresponding to possible parameter values under the alternative hypothesis. Sufficient conditions under which detection performance can or cannot be improved are derived for each case. Also, statistical characterization of optimal additive noise is provided, and the resulting false-alarm probabilities and bounds on detection performance are investigated. In addition, optimization theoretic approaches to obtaining the probability distribution of optimal additive noise are discussed. Finally, a detection example is presented to investigate the theoretical results.     

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.     

Stochastic signaling in the presence of channel state information uncertainty

In this paper, stochastic signaling is studied for power-constrained scalar valued binary communications systems in the presence of uncertainties in channel state information (CSI). First, stochastic signaling based on the available imperfect channel coefficient at the transmitter is analyzed, and it is shown that optimal signals can be represented by a randomization between at most two distinct signal levels for each symbol. Then, performance of stochastic signaling and conventional deterministic signaling is compared for this scenario, and sufficient conditions are derived for improvability and nonimprovability of deterministic signaling via stochastic signaling in the presence of CSI uncertainty. Furthermore, under CSI uncertainty, two different stochastic signaling strategies, namely, robust stochastic signaling and stochastic signaling with averaging, are proposed. For the robust stochastic signaling problem, sufficient conditions are derived for reducing the problem to a simpler form. It is shown that the optimal signal for each symbol can be expressed as a randomization between at most two distinct signal values for stochastic signaling with averaging, as well as for robust stochastic signaling under certain conditions. Finally, two numerical examples are presented to explore the theoretical results.     

Performance evaluation of impulse radio UWB systems with pulse-based polarity randomization

In this paper, the performance of a binary phase shift keyed random time-hopping impulse radio system with pulse-based polarity randomization is analyzed. The effects of interframe interference and multiple-access interference on the performance of a generic Rake receiver are investigated for asynchronous systems in frequency-selective environments. A key step is to model the asynchronous system as a chip-synchronous system with uniformly distributed timing jitter for the transmitted pulses of interfering users. This model allows the analytical technique developed for the synchronous case to be extended to the asynchronous case and allows the derivation of closed-form equations for the bit error probability in various Rake receiver architectures. It is shown that a Gaussian approximation can be used for both multiple-access and interframe interference as long as the number of frames per symbols is large (typically, at least 5), whereas there is no minimum requirement for the number of users for the equations to hold. It is observed that under many circumstances, the chip-synchronous case shows a worse bit error probability performance than the asynchronous case; the amount of the difference depends on the autocorrelation function of the ultra-wideband pulse and the signal-to-interference-plus-noise-ratio of the system. Simulations studies support the approximate analysis.     

Cost minimization of measurement devices under estimation accuracy constraints in the presence of Gaussian noise

Novel convex measurement cost minimization problems are proposed based on various estimation accuracy constraints for a linear system subject to additive Gaussian noise. Closed form solutions are obtained in the case of an invertible system matrix. In addition, the effects of system matrix uncertainty are studied both from a generic perspective and by employing a specific uncertainty model. The results are extended to the Bayesian estimation framework by treating the unknown parameters as Gaussian distributed random variables. Numerical examples are presented to discuss the theoretical results in detail.     

Optimal and suboptimal receivers for code‐multiplexed transmitted‐reference ultra‐wideband systems

In this study, optimal and suboptimal receivers are investigated for code‐multiplexed transmitted‐reference (CM‐TR) ultra‐wideband systems. First, a single‐user scenario is considered, and a CM‐TR system is modeled as a generalized noncoherent pulse‐position modulated system. Based on that model, the optimal receiver that minimizes the bit error probability is derived. Then, it is shown that the conventional CM‐TR receiver converges to the optimal receiver under certain conditions and achieves close‐to‐optimal performance in practical cases. Next, multi‐user systems are considered, and the conventional receiver, blinking receiver, and chip discriminator are investigated. Also, the linear minimum mean‐squared error (MMSE) receiver is derived for the downlink of a multi‐user CM‐TR system. In addition, the maximum likelihood receiver is obtained as a performance benchmark. The practicality and the computational complexity of the receivers are discussed, and their performance is evaluated via simulations. The linear MMSE receiver is observed to provide the best trade‐off between performance and complexity/practicality. Copyright © 2011 John Wiley & Sons, Ltd.     

Ranging in a Single-Input Multiple-Output (SIMO) System

In this letter, optimal ranging in a single-input multiple-output (SIMO) system is studied. The theoretical limits on the accuracy of time-of-arrival (TOA) (equivalently, range) estimation are calculated in terms of the Cramer-Rao lower bound (CRLB). Unlike the conventional phased array antenna structure, a more generic fading model is employed, which allows for the analysis of spatial diversity gains from the viewpoint of a ranging system. In addition to the optimal solution, a two-step suboptimal range estimator is proposed, and its performance is compared with the CRLBs.     

Regional and structural analysis of the manufacturing industry in Turkey

The geography of the manufacturing industry has been changing due to technological development, flexible production and reducing transportation costs regarding the new specialization and distribution process in the world. While manufacturing production has been moving from developed countries to the relatively less developed ones, which have become the emerging economies over the last two decades, the concentration of these activities within the countries has always received the attention of researchers. On the other hand, not only the geographical shift but also structural shifts have increasingly been an important phenomenon of the twenty-first century. It is known that the level of technology and innovation makes a significant contribution to regional economic development. Determinants of manufacturing agglomerations have created a wide literature based on different empirical studies. Moreover the structural changes of industry need to be investigated regarding the spatial agglomerations. The aim of this paper is to explore how the factors of manufacturing agglomerations have differentiated due to the technological level across the country. Furthermore, we assume that the agglomeration mechanism is likely to vary across the space. Therefore, we have run both global and local regression models based on the employment data of the 81 NUTS III level regions (provinces) of Turkey in 2012. The results point out that the factors of agglomerations are different in the east and west provinces, while GWR has significantly improved global results.