Performance Of Several Detectors Research Articles

Data detection based on matrix decomposition for massive MIMO systems in realistic channel scenarios

Massive multiple-input multiple-output (MIMO) is a key technology for modern wireless communication systems. In massive MIMO receivers, data detection is a computationally expensive task. In this paper, we explore the performance and the computational complexity of matrix decomposition based detectors in realistic channel scenarios for different massive MIMO configurations. In addition, data detectors based on decomposition algorithms are compared to the approximate-inversion detection (AID) methods. It is shown that the alternating-direction-method-of-multipliers-based-Infinity-Norm (ADMIN) detection is promising in realistic channel environment and the performance is stable even when the ratio of the base-station (BS) antenna elements to the number of users is small. In addition, this paper studies the performance of several detectors in imperfect channel state information (CSI) and correlated channels. Our work provides valuable insights for massive MIMO systems and very large-scale integration (VLSI) designers to select the appropriate massive MIMO detector based on their specifications.

Integrating X-ray kV millimetric field dosimetry with a synthetic diamond detector into the treatment planning system commissioning of a preclinical irradiator.

Small animal irradiators are equipped with x-ray beams and cone collimators with millimeter dimensions to be used in preclinical research. The use of small fields in the kV energy range may require the application of energy-dependent, field size-dependent, or depth-dependent correction factors to the dosimetric data acquired for treatment planning system (TPS) commissioning purposes to obtain accurate dose values. Considering that these corrections are also detector dependent, the suitability of a synthetic single-crystal diamond detector for small-field relative dosimetry in a preclinical irradiator (220-kVp) was evaluated to avoid the necessity of applying correction factors during TPS commissioning. The detector response was assessed during the transition for field sizes ranging from 20×20mm2 to 3×3mm2 , using the small animal radiation research platform (SARRP). The percentage depth dose distributions (PDDs), lateral profiles and output factors (OFs) were measured. The PDDs for the synthetic diamond detector were compared to the distributions acquired using a small-volume microchamber (0.016cm3 ) and with Monte Carlo calculations using the MC3D in-house software package. The profiles and OFs were compared to the data from a silicon solid-state detector and to radiochromic film data provided by the manufacturer; for the OF determination, measurements made using a microchamber were added for comparison. The performance of several detectors used as references was previously validated for relative dosimetry in preclinical irradiators. A commercial TPS was commissioned for the factor-based algorithm, using the data acquired with the diamond detector, and no additional correction factors were applied. To verify the performance of the TPS and the accuracy of the dosimetric methodology, radiochromic film irradiation in water was conducted, and two-dimensional (2D) dose distributions in the coronal and axial planes were compared under different gamma criteria. Compared with the microchamber and MC3D distributions, the agreement of the PDDs using the synthetic diamond detector was better than 2%. The profile data exhibited very good agreement compared with the data from the silicon detector, with an average and a maximum difference of 0.31 and 0.39mm in the penumbras, respectively. Compared with the data from the radiochromic film, the average and maximum differences were equal to 0.77 and 0.89mm, respectively. Very good agreement, within 1%, was obtained between the OFs measured with the synthetic diamond detector and the radiochromic film, compared only for the cone collimators. The validation of the TPS commissioning using gamma criteria compared to film showed an average passing rate of 100% and 93.2% with a global gamma criterion of 1mm/3% for the coronal and axial planes, respectively, including the 3×3mm2 field size and penumbra regions. Synthetic diamond is a suitable detector for the complete relative dosimetry of small x-ray fields. The commissioning of the TPS with its own beam dosimetric data exhibited encouraging results even in a 3×3mm2 field and penumbra region. This methodology allows for the prediction of 2D dose distributions with an accuracy in water ranging from 3 to 5% compared to the 2D distribution from film dosimetry.

Channel Models and Detectors for Two-Dimensional Magnetic Recording

Two-dimensional magnetic recording (TDMR) is a novel recording architecture intended to support densities beyond those of conventional recording systems. The gains from TDMR come primarily from more powerful coding and signal processing algorithms that allow the bits to be packed more tightly on the disk, and yet be retrieved with acceptable error rates. In this paper, we present some preliminary results for an advanced channel model based on micromagnetic simulations, coined the Grain Flipping Probability model. This model requires a one-time computationally complex characterization phase, but subsequently provides fast and accurate two-dimensional (2-D) readback waveforms that include effects captured from micromagnetic simulations and the statistical effects derived from the granularity of the recording medium. We also show the performance of several detectors over a pre-existing TDMR channel model directly as a function of channel density rather than the signal-to-noise ratio (SNR).

Empirical dead-time corrections for synchrotron sources

An experimental comparison of models for performing dead-time corrections of photon-counting detectors at synchrotron sources is presented. The performance of several detectors in the three operating modes of the Advanced Photon Source is systematically compared, with particular emphasis on asymmetric fill patterns. Several simple and well known correction formulas are evaluated. The results demonstrate the critical importance of detector speed and synchrotron fill pattern in selecting the proper dead-time correction.

Locally Optimum Detection of Signals in Multiplicative and First-Order Markov Additive Noises

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In most previously reported studies on locally optimum detection of signals, independent observations have been assumed in various noise environments. The use of an independent observation model may cause a considerable performance degradation in detection applications of modern high data-rate communication systems exhibiting dependence among interference components. In this paper, the detection of weak known and random signals is addressed in observations corrupted by multiplicative and first-order Markov additive noises. The asymptotic and finite sample-size performance of several detectors are obtained and compared: it is confirmed that the dependence of noise components need to be taken into account to maintain detection performance appropriately. </para>

Performance of microstrip gas chambers passivated by thin semiconducting glass and plastic films

Patterned microstrip gas chamber substrates have been covered with ion-beam sputtered glass with electronic conductivity or a polymer which was subsequently irradiated with an ion-beam. The sputtering procedure is described in detail. The performance of several detectors is reported.

Comparison of known signal detection schemes under a weakly dependent noise model

The authors consider the discrete-time signal detection problem under the presence of additive noise exhibiting weak dependence. They first propose a weakly dependent noise model, in which the additive noise is modelled as a moving average process. They derive the locally optimum, memoryless, and one-memory detector test statistics under the model. The asymptotic performance of the one-memory detector is compared with that of the locally optimum and memoryless detectors. Specific examples for the asymptotic performance comparison of these detectors are considered. The authors also investigate the finite sample-size performance of several detectors through Monte-Carlo simulation. It is observed that the one-memory detector can achieve almost optimum performance at the expense of only one memory unit under the weakly dependent noise model, and is rather insensitive to slight model change.