Kari Kalliojarvi

Roundoff errors in block-floating-point systems

Block-floating-point representation is a special case of floating-point representation, where several numbers have a joint exponent term. In this paper, roundoff errors in signal processing systems utilizing block-floating-point representation are studied. Special emphasis is on analysis of quantization errors when data is quantized to a block-floating-point format and on analysis of roundoff errors in digital filters utilizing block-floating-point arithmetic, block-floating-point roundoff errors are found to depend on the signal level in the same way as floating-point roundoff errors, resulting in approximately constant signal-to-noise-ratios (SNRs) over relatively large dynamic range. Both the analysis and simulation results show that block-floating-point is an efficient number representation format. In data representation, a superior performance to fixed- or floating-point representations can be achieved with block-floating-point representation with same total number of bits per sample. In digital filters, block-floating-point arithmetic can provide comparable performance to floating-point arithmetic with reduced complexity.

Low-complexity angle of arrival estimation of wideband signals using small arrays

When the signal to noise ratio is relatively high, the angle of arrival of the strongest signal can be estimated with a very simple method and a small 3D sensor array. The differences in the arrival times of the wideband signal received by spatially separated sensors are estimated using the polarity coincidence correlation. These time differences, i.e. time delays, determine the angle of arrival. In this paper the effects of quantization of the time delays are studied. It is found out that this simple method gives comparable performance to the conventional direct correlation based methods in the case of a relatively high signal to noise ratio.

Key technologies for IMT-advanced mobile communication systems

WINNER is an ambitious research project aiming at identification, development, and assessment of key technologies for IMT-advanced mobile communication systems. WINNER has devised an OFDMA-based system concept with excellent system-level performance for flexible deployments in a wide variety of operating conditions. The WINNER system provides a significant step forward from current 3G systems. Key innovations integrated into the system concept include flexible spectrum usage and relaying, adaptive advanced antenna schemes and pilot design, close to optimal link adaptation, hierarchical control signaling, and a highly flexible multiple access scheme. The end-to-end performance assessment results demonstrate that the WINNER concept meets the IMT-advanced requirements.

Awareness networking in wireless environments

This article presented a platform for awareness networking, targeted for distribution of locally relevant control information between nodes in heterogeneous wireless environments. This concept can be leveraged in many different ways and purposes, as shown with the examples given, which range from network discovery, to functionalities required in cognitive radio systems to distributed services facilitating localized mobile social networking. Although a wide range of applications can be envisioned, the same basic solution for distributing locally relevant control information applies to all of them. Future research work on awareness networking is required on multiple areas, covering the technical details of the connectivity solution, details of the distributed algorithms, functionalities, and services, and the regulatory support required for their realization.

Floating-point arithmetic in signal processing

The use of floating-point arithmetic in digital signal processing is considered. An introduction to floating-point arithmetic based on the IEEE floating-point standards is given. Finite wordlength effects of these arithmetic systems are presented. Floating-point hardware is discussed. The emphasis is on audio applications. As an example, amplitude distributions and signal-to-noise ratios of quantized music are considered, and audio standards using floating-point arithmetic are presented.<<ETX>>

Use of short floating-point formats in audio applications

Use of short floating-point formats that are shorter than the IEEE floating-point standard (ANSI/IEEE S+A 754-1985), 24+8-b, in digital audio applications is studied. The performance of these formats is analyzed in different parts of the digital audio signal processing chain and compared to the performance of widely used fixed-point formats. The statistics of practical audio signals and the characteristics of modern floating-point signal processors are considered in the analysis. >

Soft-decision decoding of binary linear block codes using reduced breadth-first search algorithms

The article discusses soft-decision decoding of binary linear block codes using the t-algorithm and its variants. New variants of the basic algorithm are presented that reduce the decoding complexity using a threshold adaptive to the signal-to-noise ratio and address the variable decoding complexity by either limiting the memory or using a generalized M-algorithm with a nonconstant state profile.

Distribution of roundoff noise in binary floating-point addition

A method for deriving the distribution of relative round off error in addition of two binary floating-point numbers is introduced. The distribution is needed in the calculation of variance of the relative roundoff error in floating-point addition. The resulting distribution depends on the statistics of the addends and the rounding strategy chosen. As an example, the distribution is derived for the addition of two uncorrelated numbers from Gaussian distribution. The result was verified by simulation.<<ETX>>

Soft-decision decoding of binary linear block codes using t-algorithm

This paper proposes a new and computationally efficient soft-decision decoding algorithm for binary linear block codes. It uses the tree representation of a systematically encoded block code. The tree representation is traversed through in a breadth-first fashion and it is adaptively pruned during the decoding using the following principle: if the metric difference between the best partial path and any other partial path at the same level is greater than a threshold value, then such a path is not extended any further. The threshold value is chosen based on a signal-to-noise ratio estimate. The efficiency of the pruning procedure is enhanced by constructing the tree so that the most reliable symbols are processed first. We show that practically optimum bit error rate performance in the additive white Gaussian noise channel can be efficiently achieved.

Novel floating-point A/D- and D/A-conversion methods

Floating-point arithmetic offers several benefits in digital signal processing. Floating-point A/D- and D/A-converters are needed in the realization of true floating-point signal processing systems. Novel, simple floating-point A/D- and D/A-conversion methods, based on the close resemblance of floating-point and logarithmic number representations, are introduced in this paper. These methods are easy to tailor to different specifications, and they offer a simple trade-off between dynamic range and accuracy.<<ETX>>