Individual Data Streams Research Articles

Challenges in the Measurement and Data-Processing Chain of the LISA Mission

The LISA Mission (Laser Interferometer Space Antenna) is currently under mission formulation with a launch date planned in 2020. The purpose of the mission is the observation of gravitational waves at frequencies between 0.1 mHz and 1 Hz by measuring distance fluctuations between inertial reference points, represented by cubic proof masses. In order to provide a sufficient sensitivity of the instrument, distance fluctuations between two inertial reference points must be measured with a strain accuracy of around 10−20 Hz−1/2. This is achieved by setting up a laser interferometer with a base-length of 5⋅106 km and a path-length measurement noise in the order of 10 pm Hz−1/2. For a correct evaluation of the data on the ground, it is essential that the science data telemetry preserves all required frequency domain information. That is, any on-board data-processing and down-sampling must be done with great care in order not to introduce aliasing or other artifacts into the data stream. As an additional complication, most of the optical metrology data is dominated by laser phase noise which is about eight orders of magnitude larger than the required instrument sensitivity. However, by applying a method called “time-delayed interferometry” during the ground data processing, this laser phase noise can be eliminated from the data. This method has already been demonstrated in a detailed simulation environment, but it requires a very careful filtering, synchronization, and interpolation of the individual data streams. Last but not least, a calibration of system parameters is necessary in many areas of the LISA measurement system. The system design must therefore ensure that all data required for these calibrations is available on-ground in a quality that allows a successful computation of the calibration coefficients within a reasonable time-frame. The data streams do not only include data from the optical metrology system, but also from the drag-free and attitude control system which are used to derive other information, such as the charge state of the proof mass. This yields a strong coupling between the different disciplines since data that is only used for housekeeping purposes in other missions becomes an essential part of the science data stream for the LISA mission. This paper gives an overview of the LISA measurement and data-processing chain. It highlights the most challenging areas that have been identified so far and describes the intended solution methods.

Linear processing and sum throughput in the multiuser MIMO downlink

We consider linear precoding and decoding in the downlink of a multiuser multiple-input, multiple-output (MIMO) system, wherein each user may receive more than one data stream. We propose several mean squared error (MSE) based criteria for joint transmit-receive optimization and establish a series of relationships linking these criteria to the signal-to-interference-plus-noise ratios of individual data streams and the information theoretic channel capacity under linear minimum MSE decoding. In particular, we show that achieving the maximum sum throughput is equivalent to minimizing the product of MSE matrix determinants (PDetMSE). Since the PDetMSE minimization problem does not admit a computationally efficient solution, a simplified scalar version of the problem is considered that minimizes the product of mean squared errors (PMSE). An iterative algorithm is proposed to solve the PMSE problem, and is shown to provide near-optimal performance with greatly reduced computational complexity. Our simulations compare the achievable sum rates under linear precoding strategies to the sum capacity for the broadcast channel.

Development of a model of data-flows for precision agriculture based on a collaborative research project

The understanding of actual and potential data-flows in the practice of precision agriculture (PA) is an essential prerequisite for the optimisation and automation of information management in this field. As a contribution to this process, this paper presents an analysis of the data-flows within the work of a collaborative research project concerned with the testing of the methods developed within the project on two demonstration fields. This work provides a good case study for the modelling of a range of data-flows covering a broad spectrum of PA techniques. Using the notation and software tools for the Unified Modeling Language (UML), a complete model of all identified data-flows was created. Individual data-streams relating to particular source or product datasets were then extracted from this model. These data-streams present a practical application of the model in identifying the benefit that may be obtained from a particular gathered dataset (e.g. yield data) or in identifying the data that must be gathered to generate a particular product dataset (e.g. sustainability indicators). Whilst the current model is focussed on one particular research project, it has potential to be extended to cover more generally the common practice of precision agriculture. Such a model may then be used by farmers as a roadmap for the adoption for precision agriculture by allowing them to determine what datasets are available to them or may be easily collected and what products they may generate from these, or vice versa to identify what datasets they must obtain in order to generate a particular dataset of interest.

Tomlinson-Harashima Precoding in MIMO Systems: A Unified Approach to Transceiver Optimization Based on Multiplicative Schur-Convexity

This paper deals with the design of a multicarrier multiple-input multiple-output system which performs nonlinear Tomlinson-Harashima precoding at the transmitter and linear equalization at the receiver. The goal is the joint optimization of the processing matrices at both ends of the wireless link, assuming a constraint on the overall transmit power. We consider different design criteria which require the maximization/minimization of objective functions that depend on the mean square errors over the individual data streams. A unified framework for the solution of a great number of optimization problems is developed, based on the concept of <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">multiplicative</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Schur-convexity</i> . We show that many widely used design criteria can be easily accommodated in our framework. Our analysis is centered on two theorems which, in the case of cooperative processing among the different subcarriers, provide closed-form solutions to a number of optimization problems. On the other hand, when an independent processing is assumed at each subcarrier closed-form solutions may not exist. Nonetheless, exploiting the results of the two theorems, we show that for a variety of cost functions the optimization problem can be efficiently solved. Theoretical analysis and computer simulations are used to assess the performance of the proposed schemes and make comparisons with linear transceiver architectures. It turns out that nonlinear precoding provides better results than linear prefiltering when the cost function is multiplicatively Schur-convex. In contrast, when the cost function is multiplicatively Schur-concave the nonlinear scheme is equivalent to the linear one.

A framework for designing mimo systems with decision feedback equalization or tomlinson-harashima precoding

We consider joint transceiver design for point-to-point Multiple-Input Multiple-Output communication systems that implement interference (pre-)subtraction; i.e., Decision Feedback Equalization (DFE) or Tomlinson-Harashima precoding (THP). We develop a unified framework for joint transceiver design of these two dual systems by considering design criteria that are expressed as functions of the (logarithm of the) Mean Square Error (MSE) of the individual data streams. By deriving two inequalities that involve the logarithms of the individual MSEs, we obtain optimal designs for two broad classes of communication objectives, namely those that are Schur-convex and Schur-concave functions of these logarithms. These two classes embrace several design criteria for which the optimal transceiver design has remained an open problem. For Schur-convex objectives, the optimal design results in data streams with equal MSEs. In addition to other desirable properties, this design simultaneously minimizes the total MSE and the average bit error rate, and maximizes the Gaussian mutual information; a property that is not achieved by a linear transceiver. Moreover, we show that the optimal design yields objective values that are superior to the corresponding optimal objective value for a linear transceiver. For Schur-concave objectives, the optimal DFE design results in linear equalization and the optimal THP design results in linear precoding. The proposed design framework can be regarded as a counterpart of the existing framework for linear transceiver design.

Applications of Space Division Multiplexing and Those Performance in a MIMO Channel

Currently, space division multiplexing (SDM), where individual data streams are transmitted from different antennas simultaneously, is expected to be a promising technology for achieving a high data rate within a limited frequency band in a multiple-input multiple-output channel. In this paper, transmitter and receiver architectures of SDM applications are described, and performance improvement with the increase of data streams is shown referring to results of computer simulations. In addition, channel coded systems are also evaluated.

Chip-Package Co-Implementation of a Triple DES Processor

This paper describes the design and implementation of a dedicated data encryption standard (DES) processor. The processor consists of three 0.6 /spl mu/m complementary metal oxide semiconductor (CMOS) integrated circuits (ICs) mounted on a single MCM-D thin-film substrate. Each chip can operate on an individual data stream, or the three can be cascaded to implement the so-called triple-DES (3DES) function for increased security. Measurements show 3DES operation at 110 MHz, which translates to a throughput of over 7 Gb/s, the highest reported 3DES throughput to date. System features which contribute to this throughput are the use of area-array (flip-chip) input/output (I/O) and global IC power/ground/clock distribution in the MCM package. In this case, package-level distribution reduced clock skew by 150 ps, and reduced the chip area required for power distribution by 20%. This paper also includes measurements of switching noise of the MCM's V/sub dd/ plane and how it correlates with a simple model of the system power distribution.

A wavelet domain diversity method for transmission of images over wireless channels

We propose a wavelet domain diversity combining method to combat errors during image transmission on wireless channels. For images represented in the wavelet domain, diversity is used to obtain multiple data streams corresponding to the transmitted image at the receiver. These individual image data streams are combined to form a composite image with higher perceptual quality. Both uncompressed and compressed images are considered. The SPIHT algorithm is used for image compression. Diversity combining methods for both uncompressed and compressed images exploit the characteristics of the wavelet transform. For compressed images, unequal error protection is employed in conjunction with diversity combining. Simulation results demonstrate that the quality of the received image can be significantly improved.

PROCESS MONITORING WITH MULTIPLE PRODUCTS AND PRODUCTION LINES

Traditional quality assurance methods are often based on the monitoring of individual product data streams. For many situations in the process industry, such an approach is not very effective for quickly detecting problems affecting larger groupings of ..