<p>The reaction cross section gives the probability that a particle will undergo a nonelastic process when passing through a nuclear medium. Therefore reaction cross section data are of importance both for theoretical studies and for applications in such diverse fields as medicine, biology, astrophysics and accelerator-driven transmutation of nuclear waste.</p><p>There exist many data sets with angular distributions of elastic scattering, but very few measurements of the complementary reaction cross section have been performed. The measurement is in principle simple but has in practice proved to be very difficult to perform, and the relatively limited amount of experimental data displays some serious inconsistencies.</p><p>Results from measurements of reaction cross sections are presented for:</p><p>• ³He on ⁹Be, ¹²C, ¹⁶O, ²⁸Si, ⁴⁰Ca, ^58,60Ni, ^{112,116,118,120,124}Sn and ²⁰⁸Pb at 96, 138 and 167 MeV</p><p>• protons on ¹²C, ⁴⁰Ca, ⁹⁰Zr and ²⁰⁸Pb at six energies in the energy range 80-180 MeV, and on </p><p>⁵⁸Ni at 81 MeV. </p><p>Experimental uncertainties were 3-9% for ³He and 1.5-8% for protons.</p><p>The apparatus and the experimental method used for the measurements of reaction cross sections, using a modified attenuation technique, is described. The detection method enables simultaneous measurements of reaction cross sections for five different sizes of the solid angles in steps from 99.0 to 99.8% of the total solid angle. The final results are obtained by extrapolation to the full solid angle.</p><p>Experimental results are compared with predictions from optical model calculations using phenomenological global optical potentials.</p><p>Phenomenological parametrizations of reaction cross sections for scattering of projectiles on targets are presented. The parametrizations show that reaction cross sections are very sensitive to matter distributions at very large radii of both the projectile and the target. For protons the derived relations makes it possible to predict the reaction cross sections on targets for which no experimental data exist.</p>

The reaction cross section gives the probability that a particle will undergo a nonelastic process when passing through a nuclear medium. Therefore reaction cross section data are of importance both for theoretical studies and for applications in such diverse fields as medicine, biology, astrophysics and accelerator-driven transmutation of nuclear waste. There exist many data sets with angular distributions of elastic scattering, but very few measurements of the complementary reaction cross section have been performed. The measurement is in principle simple but has in practice proved to be very difficult to perform, and the relatively limited amount of experimental data displays some serious inconsistencies. Results from measurements of reaction cross sections are presented for: • 3He on 9Be, 12C, 16O, 28Si, 40Ca, 58,60Ni, 112,116,118,120,124Sn and 208Pb at 96, 138 and 167 MeV • protons on 12C, 40Ca, 90Zr and 208Pb at six energies in the energy range 80-180 MeV, and on 58Ni at 81 MeV. Experimental uncertainties were 3-9% for 3He and 1.5-8% for protons. The apparatus and the experimental method used for the measurements of reaction cross sections, using a modified attenuation technique, is described. The detection method enables simultaneous measurements of reaction cross sections for five different sizes of the solid angles in steps from 99.0 to 99.8% of the total solid angle. The final results are obtained by extrapolation to the full solid angle. Experimental results are compared with predictions from optical model calculations using phenomenological global optical potentials. Phenomenological parametrizations of reaction cross sections for scattering of projectiles on targets are presented. The parametrizations show that reaction cross sections are very sensitive to matter distributions at very large radii of both the projectile and the target. For protons the derived relations makes it possible to predict the reaction cross sections on targets for which no experimental data exist.

The integration of Multiple Input Multiple Output (MIMO) and Orthogonal Frequency Division Multiplexing (OFDM) techniques has become a preferred solution for the high rate wireless technologies due to its high spectral efficiency, robustness to frequency selective fading, increased diversity gain, and enhanced system capacity. The main drawback of OFDM-based systems is their susceptibility to impairments such as Carrier Frequency Offset (CFO), Sampling Frequency Offset (SFO), Symbol Timing Error (STE), Phase Noise (PHN), and fading channel. These impairments, if not properly estimated and compensated, degrade the performance of the OFDM-based systems In this thesis, a system model for MIMO-OFDM that takes into account the effects of all these impairments is formulated. Using this system model, we de-rive Cramer-Rao Lower Bounds (CRLBs) for the joint estimation of deterministic impairments in MIMO-OFDM system, which show the coupling effect among different impairments and the significance of the joint estimation. Also, Bayesian CRLBs for the joint estimation of random impairments in OFDM system are derived. Similarly, we derive Hybrid CRLBs for the joint estimation of random and deterministic impairments in OFDM system, which show the significance of using Bayesian approach in estimation. Further, we investigate different algorithms for the joint estimation of all impairments in OFDM-based system. Maximum Likelihood (ML) algorithms and its low complexity variants, for the joint estimation of CFO, SFO, STE, and channel in MIMO-OFDM system, are proposed. We propose a low complexity ML algorithm which uses Compressed Sensing (CS) based channel estimation method in a sparse fading sce-nario, where the received samples used for estimation are less than that required for a Least Squares (LS) or Maximum a posteriori (MAP) based estimation. Also, we propose MAP algorithms for the joint estimation of the random impairments, PHN and channel, utilizing their statistical knowledge which is known a priori. Joint estimation algorithms for SFO and channel in OFDM system, using Bayesian framework, are also proposed in this thesis. The performance of the estimation methods is studied through simulations and numerical results show that the performance of the proposed algorithms is better than existing algorithms and is closer to the derived CRLBs.