COMPARATIVE ANALYSIS OF ML AND MAP DETECTORS FOR PAM CONSTELLATIONS IN AWGN CHANNEL

In this paper we perform a comparative performances analysis of “maximum a posteriori” (MAP) and “maximum likelihood” (ML) detectors for one-dimensional constellation in the adaptive white Gaussian noise (AWGN) channel. More precisely, error probabilities per symbol for the aforementioned detectors are compared for the case when the pulse amplitude modulation (PAM) constellation with the equidistant and non-equiprobable constellation points is used as one-dimensional constellation. We perform analysis for different distributions of the constellation point probabilities and different values of the signal-to-noise ratio (SNR). The analysis indicates which detector can be adequate choice for the certain distribution of constellation point probabilities and the SNR. Besides this, for the straightforward performance assessment of the MAP detector we derive a formula for the symbol error probability. Our analysis also points out that the nonuniform distribution of the constellation points probabilities does not necessarily improve the symbol error probability. With the aim to decrease the symbol error probability we propose a method for defining constellation point probabilities. The presented results show that PAM constellation designed by utilizing the method we propose significantly outperforms the conventional PAM constellation in terms to the symbol error probability

PIECEWISE-LINEAR RADIAL COMPRESSION FUNCTION FOR PYRAMID TWO-DIMENSIONAL QUANTIZER

In this paper a companding-type approach is presented to designing the pyramid two-dimensional quantizer whose cells are obtained by radial spreading of the cubic cells. For a memoryless Laplacian source, the optimal radial compression function and rate allocation between the radius and location quantizers are determined subject to the mean-squared error (MSE) criterion. The results also include formulation of a new method for linearization of compression function, based on a compression function derivative discretization. It is of special importance since the unclosed-form of optimal radial compression function causes certain difficulties in companding quantizer implementation

Switched Nonuniform and Piecewise Uniform Scalar Quantization of Laplacian Source

In this paper switched nonuniform and piecewise uniform scalar quantization of Laplacian source are analyzed. This scalar quantization techniques are used in order to obtain higher signal quality by increasing signal-to-quantization noise ratio (SNRQ) with respect to it’s necessary robustness over a broad range of input variances in a wide range of signal volumes. We observe μ-law compandor implementation to achieve compromise between high-rate digitalization and variance adaptation. The main contribution of this model is kipping almost the same quality as the nonuniform compandor model, with simpler realization structure and the possibility of it’s applying for digitalization of wide range continuous signals

Did the Eurasian ice sheets melt completely in early Marine Isotope Stage 3? New evidence from Norway and a synthesis for Eurasia

We describe glaci-lacustrine sediments buried under thick tills in Folldalen, south-east Norway, a site located close to the former centre of the Scandinavian Ice Sheet. Thus, the location implies that the ice sheet had melted when the sediments were deposited. The exposed ground was occupied by arctic vegetation. The best age estimate from 20 quartz luminescence dates is 55.6 ± 4.6 ka. Due to possible incomplete bleaching, an age in the younger part of the time range is most probable. We conclude that the Scandinavian Ice Sheet melted almost completely away early in Marine Isotope Stage (MIS) 3. Our review shows that the other Eurasian ice sheets also disappeared in that period. In north-western Germany, there were forests, containing warmth-demanding trees early in MIS 3, indicating a summer climate only slightly cooler than at present, thus supporting the evidence that the adjacent ice sheets had melted. The melting of the Eurasian ice sheets contributed to 50–100% of the sea-level rise from MIS 4 to MIS 3, implying that the much larger North American ice sheets did not melt much. In contrast, the Eurasian ice sheets contributed only about 30% to the sea-level drop from MIS 3 to MIS 2, meaning that the North American ice sheets during that period expanded strongly.publishedVersio

LEVEL CROSSING RATE OF MACRODIVERSITY SYSTEM OVER COMPOSITE GAMMA SHADOWED ALPHA-KAPPA-MU MULTIPATH FADING CHANNEL

In this paper macrodiversity system with macrodiversity selection combining (SC) receiver and two microdiversity SC receivers operating over composite shadowed multipath fading environment is considered. Received signal is subjected simultaneously to gamma long term fading and α-κ-μ short term fading resulting in system performance degradation. Macrodiversity SC receiver reduces gamma long term fading effects and microdiversity SC receivers mitigate α-κ-μ short term fading effects. Analitical expression for average level crossing rate of proposed wireless mobile system represented as an infinite series is evaluated. Mathematical and numerical analysis are shown influences of gamma fading severity, α-κ-μ multipath fading severity, and Rician factor on average level crossing rate

Optimization of the 24-Bit Fixed-Point Format for the Laplacian Source

The 32-bit floating-point (FP32) binary format, commonly used for data representation in computers, introduces high complexity, requiring powerful and expensive hardware for data processing and high energy consumption, hence being unsuitable for implementation on sensor nodes, edge devices, and other devices with limited hardware resources. Therefore, it is often necessary to use binary formats of lower complexity than FP32. This paper proposes the usage of the 24-bit fixed-point format that will reduce the complexity in two ways, by decreasing the number of bits and by the fact that the fixed-point format has significantly less complexity than the floating-point format. The paper optimizes the 24-bit fixed-point format and examines its performance for data with the Laplacian distribution, exploiting the analogy between fixed-point binary representation and uniform quantization. Firstly, the optimization of the 24-bit uniform quantizer is performed by deriving two new closed-form formulas for a very accurate calculation of its maximal amplitude. Then, the 24-bit fixed-point format is optimized by optimization of its key parameter and by proposing two adaptation procedures, with the aim to obtain the same performance as of the optimal uniform quantizer in a wide range of variance of input data. It is shown that the proposed 24-bit fixed-point format achieves for 18.425 dB higher performance than the floating-point format with the same number of bits while being less complex

Optimization of the 24-Bit Fixed-Point Format for the Laplacian Source

The 32-bit floating-point (FP32) binary format, commonly used for data representation in computers, introduces high complexity, requiring powerful and expensive hardware for data processing and high energy consumption, hence being unsuitable for implementation on sensor nodes, edge devices, and other devices with limited hardware resources. Therefore, it is often necessary to use binary formats of lower complexity than FP32. This paper proposes the usage of the 24-bit fixed-point format that will reduce the complexity in two ways, by decreasing the number of bits and by the fact that the fixed-point format has significantly less complexity than the floating-point format. The paper optimizes the 24-bit fixed-point format and examines its performance for data with the Laplacian distribution, exploiting the analogy between fixed-point binary representation and uniform quantization. Firstly, the optimization of the 24-bit uniform quantizer is performed by deriving two new closed-form formulas for a very accurate calculation of its maximal amplitude. Then, the 24-bit fixed-point format is optimized by optimization of its key parameter and by proposing two adaptation procedures, with the aim to obtain the same performance as of the optimal uniform quantizer in a wide range of variance of input data. It is shown that the proposed 24-bit fixed-point format achieves for 18.425 dB higher performance than the floating-point format with the same number of bits while being less complex

IMPROVED LINEARIZATION OF THE OPTIMAL COMPRESSION FUNCTION FOR LAPLACIAN SOURCE

In this paper, linearization of the optimal compression function is done and hierarchical coding (by coding the regions firstly and then the cells inside the region) is applied, achieving simple and fast process of coding and decoding. The signal at the entrance of the scalar quantizer is modeled by Laplacian probability density function. It is shown that the linearization of inner regions very little influences distortion and therefore only the last region should be optimized. Two methods of optimization of the last region are proposed, that improve performances of the scalar quantizer, and obtained SQNR (signal-to-quantization noise ratio) is close to that of the nonlinear optimal compression function