Juha Heiskala

(NOTE: Each chapter concludes with a Bibliography.) Preface. 1. Background and WLAN Overview. Review of Stochastic Processes and Random Variables. Review of Discrete-Time Signal Processing. Components of a Digital Communication System. OFDM WLAN Overview. Single Carrier Versus OFDM Comparison. 2. Synchronization. Timing Estimation. Frequency Synchronization. Channel Estimation. Clear Channel Assessment. Signal Quality. 3. Modulation and Coding. Modulation. Interleaving. Channel Codes. 4. Antenna Diversity. Background. Receive Diversity. Transmit Diversity. 5. RF Distortion Analysis for OFDM WLAN. Components of the Radio Frequency Subsystem. Predistortion Techniques for Nonlinear Distortion Mitigation. Adaptive Predistortion Techniques. Coding Techniques for Amplifier Nonlinear Distortion Mitigation. Phase Noise. IQ Imbalance. 6. Medium Access Control (MAC)for IEEE 802.ll Networks. MAC Overview. MAC System Architecture. MAC Frame Formats. MAC Data Services. MAC Management Services. MAC Management Information Base. 7. Medium Access Control (MAC) for HiperLAN/2 Networks. Network Architecture. DLC Functions. MAC Overview. Basic MAC Message Formats. PDU Trains. MAC Frame Structure. Building a MAC Frame. MAC Frame Processing. 8. Rapid Prototyping for WLANs. Introduction to Rapid Prototype Design. Good Digital Design Practices. Rapid Prototyping of a WLAN System. Index.

Caressing touch is an effective way to communicate emotions and to create social bonds. It is also one of the key mediators of early parental bonding. The caresses are generally thought to represent a social form of touching and indeed, slow, gentle brushing is encoded in specialized peripheral nerve fibers, the C-tactile (CT) afferents. In adults, areas such as the posterior insula and superior temporal sulcus are activated by affective, slow stroking touch but not by fast stroking stimulation. However, whether these areas are activated in infants, after social tactile stimulation, is unknown. In this study, we compared the total hemoglobin responses measured with diffuse optical tomography (DOT) in the left hemisphere following slow and fast stroking touch stimulation in 16 2-month-old infants. We compared slow stroking (optimal CT afferent stimulation) to fast stroking (non-optimal CT stimulation). Activated regions were delineated using two methods: one based on contrast between the two conditions, and the other based on voxel-based statistical significance of the difference between the two conditions. The first method showed a single activation cluster in the temporal cortex with center of gravity in the middle temporal gyrus where the total hemoglobin increased after the slow stroking relative to the fast stroking (p = 0.04 uncorrected). The second method revealed a cluster in the insula with an increase in total hemoglobin in the insular cortex in response to slow stroking relative to fast stroking (p = 0.0005 uncorrected; p = 0.04 corrected for multiple comparisons). These activation clusters encompass areas that are involved in processing of affective, slow stroking touch in the adult brain. We conclude that the infant brain shows a pronounced and adult-like response to slow stroking touch compared to fast stroking touch in the insular cortex but the expected response in the primary somatosensory cortex was not found at this age. The results imply that emotionally valent touch is encoded in the brain in adult-like manner already soon after birth and this suggests a potential for involvement of touch in bonding with the caretaker.

The excitation threshold of the human motor cortex was estimated on the basis of electroencephalographic responses evoked by transcranial magnetic stimulation. The hand area of the primary motor cortex was stimulated at 10 intensities, for seven healthy individuals. The four dominant peaks of the overall brain response could be reliably determined when stimulation was intense enough to induce a cortical electric field of approximately 33-44 mV/mm. This may be estimated as the threshold for evoking measurable brain activity by motor-cortex transcranial magnetic stimulation. The remarkably low threshold reflects the excellent sensitivity of the combination of transcranial magnetic stimulation and electroencephalography for the study of neuronal function of the cortex.

The significance of accurate knowledge of background optical properties and time-resolved information in reconstructing images of hemodynamic changes in the neonatal brain from diffuse optical imaging data was studied using Monte Carlo (MC) simulation. A segmented anatomical magnetic resonance (MR) image and literature-derived optical properties for each tissue type were used to create a voxel-based anatomical model. Small absorbing perturbations were introduced into the anatomical model to simulate localized hemodynamic responses related to brain activation. Perturbation MC (pMC) was used as the primary method of image reconstruction. For comparison, reconstructions were also performed using the finite element method (FEM) to solve the diffusion approximation (DA) to the radiative transfer equation (RTE). The effect of optode layout was investigated using three different grids. Of the factors studied, the density of the optode grid was found to have the greatest effect on image quality. The use of time-resolved information significantly improved the spatial accuracy with all optode grids. Adequate knowledge and modeling of the optical properties of the background was found to significantly improve the spatial accuracy of the reconstructed images and make the recovery of contrast of absorption changes more consistent over simplified modeling. Localization accuracy of small perturbations was found to be 2-3 mm with accurate a priori knowledge of the background optical properties, when a grid with high optode density (>1 optode cm(-2)) was used.

A Monte Carlo model capable of describing photon migration in arbitrary three-dimensional geometry with spatially varying optical properties and tissue anisotropy is presented. We use the model to explore the effects of anisotropy for optical measurements of the human head. An anisotropic diffusion equation that corresponds to our Monte Carlo model is derived, and a comparison between the Monte Carlo model and the diffusion equation solution with finite elements is given.