Iterative multiuser detection for turbo-coded synchronous CDMA inGaussian and non-Gaussian impulsive noise

We develop an iterative multiuser receiver for decoding turbo-coded synchronous code-division multiple-access signals in both Gaussian and non-Gaussian noise. A soft-input soft-output nonlinear multiuser detector is combined with a set of single-user channel decoders in an iterative detection/decoding structure. The nonlinear multiuser detector utilizes the prior probabilities of each user's bits to form soft estimates used for multiple-access interference cancellation. The channel decoders perform turbo-code decoding and produce posterior probabilities which are fed back to the multiuser detector for use as prior probabilities. Simulation results show that the proposed multiuser receiver performs well in both Gaussian and non-Gaussian noise. In particular, single-user turbo-code performance can be approached within a few iterations with medium to low cross correlation (ρ⩽0.5)     

Approximately optimum detection of deterministic signals inGaussian and compound Poisson noise

An approximate but explicit likelihood ratio is derived for detecting deterministic signals in Gaussian and compound Poisson noise. The approximation in the derivation is based on the assumption that the localized noise elements rarely overlap each other. The derived log-likelihood ratio consists of two distinct parts. One is the conventional correlation detector for detecting deterministic signals in Gaussian noise. The other is a nonlinear processor which compensates for the degradation of the correlation detector caused by the localized noise, and is activated only by the presence of the localized noise. As such, it involves covariance operators of both the Gaussian and the localized noise, and is obtained by using the simultaneous diagonalization and orthogonalization of quadratic forms in function space involving eigenfunctions of certain composite operators     

Optimal linear detectors for additive noise channels

In an attempt to gain insight into the design of linear detectors for additive white noise channels (discrete-time case), we describe several procedures, both optimal and suboptimal. Using the Wiener representation for nonlinear systems, we derive an ad hoc suboptimal design procedure. Exact designs are found when the noise amplitude's probability distribution is stable and when the noise is Laplacian. Considering all the linear detectors thus derived, no general form for the optimal linear detector's unit-sample response becomes apparent. Performance analyses and simulations indicate substantial performance losses occur when linear detectors are used instead of optimal (likelihood ratio) ones     

Memoryless quantizer- detectors for constant signals in m-dependent noise

The performance and design of data quantizers for use in memoryless discrete-time detection systems operating with dependent samples is considered. This problem is approached on a large-sample-size small-signal basis, andm-dependence is used to model the dependence structure among data samples. By considering the particular situation of detecting known constant signals in additive noise, previous results for memoryless detector analysis are applied to derive expressions for the evaluation of quantizer-detector performance for this situation. Design criteria are established for the optimum selection of quantizer parameters, and these are seen to be generalizations of earlier designs for the corresponding independent sampling case.     

Computationally efficient electronic-circuit noise calculations

The interreciprocal adjoint network concept is applied to the computer simulation of electronic-circuit noise performance. The method described is extremely efficient, allowing consideration of an arbitrarily large number of uncorrelated noise sources with less effort than for the original small signal a.c. analysis. Because all noise sources may be considered, no a priori assumption need be made as to which noise sources are dominant in a complicated circuit. The method is illustrated with an operational- amplifier example.     

Salt-and-Pepper noise removal by median-type noise detectors and detail-preserving regularization.

This paper proposes a two-phase scheme for removing salt-and-pepper impulse noise. In the first phase, an adaptive median filter is used to identify pixels which are likely to be contaminated by noise (noise candidates). In the second phase, the image is restored using a specialized regularization method that applies only to those selected noise candidates. In terms of edge preservation and noise suppression, our restored images show a significant improvement compared to those restored by using just nonlinear filters or regularization methods only. Our scheme can remove salt-and-pepper-noise with a noise level as high as 90%.     

Performance analysis of asymptotically optimal noncoherentdetection of trellis-coded multi-amplitude/-phase modulation signals inGaussian noise and ISI channels

Performance upper bounds for noncoherent receivers employed in conjunction with single and multi-amplitude/-phase signals, transmitted over time dispersive and Gaussian noise channels are derived. Based upon a metric which has been previously derived by the authors, we present analytical expressions and computer generated results for the performance of asymptotically optimal noncoherent detection over such channels. As a typical application of the developed theoretical analysis, we consider wideband telecommunication systems. Where time dispersion resulting in intersymbol interference (ISI) is one of the significant sources of system performance degradation. Numerical evaluation of the optimal noncoherent decoding algorithms, shows the proposed bounds to be an effective and efficient means of evaluating the performance of the noncoherent receivers under investigation. Using the derived bounds, performance evaluation results for modulation schemes such as π/4-shift DQPSK (differential quadrature phase shift keying), 8- and 16-DQAM (differential quadrature amplitude modulation), at very low bit-error rates (BER), which would otherwise pose impractically high computational loads when using Monte-Carlo error counting techniques, are readily obtained. At BER>10^-4 evaluation results generated via computer simulation have verified the tightness of the bounds     

A thermodynamic noise model for nonlinear resistors

A Gaussian white noise model for passive nonlinear resistors, valid in the linear quadratic current-voltage (I-V) approximation at zero bias, is suggested. Although approximative, the model, which has originally been developed by R.L. Stratonovich, is thermodynamically well founded. The model is applied to the shot noise of exponential diodes and tunnel junctions as well as to the thermal noise of JFET's and MOSFET's. Within the range of the linear-quadratic approximation, the results are in full agreement with the well-known device specific standard low frequency thermal and shot noise models for these devices. The model can he considered as a linear-quadratic short circuit noise current generalization of Nyquist's formula     

On nonlinear direct-sequence detectors in arbitrary power-limitedinterference

Communication over a waveform channel corrupted by additive white Gaussian noise and by an unknown and arbitrary interference of bounded power is considered. For this channel, an upper bound is presented for the worst-case error probability of a communication system comprising a direct-sequence spread spectrum modulator and a nonlinear correlation receiver. It is shown that this bound is exponentially tight as the number of chips used in the modulator becomes large. This bound is evaluated for several detector nonlinearities. Numerical examples and comparisons to the performance of a pure Gaussian noise channel are also given     

Simplified 1/f noise calculations

A new tool, called the equivalent number of decades ND/sub e/, is introduced to simplify the analysis of noise in circuits containing 1/f noise sources. ND/sub e/ is similar to the familiar concept of equivalent noise bandwidth for white sources. A simple expression for ND/sub e/ is derived for a single-pole lowpass filter and is shown to be approximately correct for Butterworth and Chebyshev filters as well.<>     

Performance of nonlinear detectors in spatial multiplexing for spatially correlated channels

Spatial multiplexing is used in multiple input multiple output (MIMO) wireless systems to increase the data rate. Some nonlinear detectors, such as minimum mean square error (MMSE) Vertical Bell laboratories layered space-time (VBLAST), Maximum A-Posteriori (MMSE VBLAST MAP), and MMSE Improved VBLAST detectors are used in place of a over more complex detector, such as maximum likelihood detector or singular value decomposition based detector. We have presented simulation results of MIMO symbol error rate versus average SNR for MMSE VBLAST MAP and MMSE Improved VBLAST schemes assuming spatially correlated channels for M-ary QAM. We have observed that the performance of MMSE VBLAST MAP and MMSE Improved VBLAST detectors is almost identical in spatially uncorrelated channels. However, in the case of spatially correlated channels, MMSE Improved VBLAST outperforms MMSE VBLAST MAP. We have also seen that complexity of the Improved VBLAST algorithm is higher than the complexity of VBLAST MAP algorithm.     

Intermediate frequency zero-crossing detectors for Bluetooth enhanced data rate system

In the recent years, Bluetooth has become an important short range transmission system which provides data rates up to 3 Mbit/s in its enhanced data rate mode (EDR). Illustrated is a low-cost intermediate frequency (IF) zero-crossing detector (ZXD) for EDR. It is shown that the proposed IF ZXD for EDR facilitates robust performance, approaching theoretical bounds in the case of single path transmission.     

A class of memoryless robust detectors in dependent noise

A new general approach to the formulation of a detector in non-Gaussian noise satisfying the strong mixing condition is introduced. The only statistical knowledge required for the optimal design is a set of parameters which can be estimated from data and recursively updated. This eliminates the requirement that exact distributions be known and leads naturally to efficient adaptive detectors     

Signal detection in compound-Gaussian noise: Neyman-Pearson andCFAR detectors

This paper handles the problem of detecting signals with known signature and unknown or random amplitude and phase in the presence of compound-Gaussian disturbance with known spectral density. Two alternative approaches are investigated: the Neyman-Pearson criterion and the generalized likelihood ratio strategy. The first approach leads to a hardly implementable detector but provides an upper bound for the performance of any other detector. The generalized likelihood ratio strategy, instead, leads to a canonical detector, whose structure is independent of the disturbance amplitude probability density function. Based on this result, the threshold setting, which is itself independent on both the noise distribution and the signal parameters, ensures a constant false alarm rate. Unluckily, this receiver requires the averaging of infinitely many components of the received waveform. This is not really a drawback since a close approximation can be found for a practical implementation of the receiver. The performance analysis shows that the generalized likelihood ratio test (GLRT) detector suffers a quite small loss with respect to the optimum Neyman-Pearson receiver (less than 1 dB in the case of random amplitude) and largely outperforms the conventional square-law detector     

Capacity and cutoff rate calculations for a concatenated codingsystem

A model is developed for a concatenated coding system, and from it the overall channel cutoff rate and capacity is found using random coding arguments. The effects of interleaving between the inner and outer codes and of the availability of side information to the outer decoder are considered. The performance of several specific concatenated coding systems is calculated and used for comparison with the random coding result. From the analysis, a number of general conclusions regarding the design of concatenated coding systems are presented. All the results are derived assuming a block inner code     

Large deviation theorems for empirical types of Markov chainsconstrained to thin sets

An irreducible Markov chain with stationary transition probabilities on a finite directed graph is considered. The probability of large deviations of the random variable denoting the empirical type of the first n transitions is investigated     

Comparative studies of noise limitations in superconducting thin-film radiation detectors

We report measurements on the noise limitations of superconducting thin films operating as thermal detectors (bolometers) and as current-dependent detectors. By making measurements in each mode on the same film it is possible to make a comparative study of the noise limitations for both detection mechanisms in the same device. Thin tin films with normal state sheet resistances on the order of 100 Ω per square have been studied. The devices were scribed to produce total normal state resistances on the order of 10 kΩ and were mounted in the vacuum chamber of a demountable tail Dewar so that they were not in direct contact with liquid helium. The resulting bolometers have response times and sensitivities similar to those of Martin and Bloor. The dominant noise mechanisms we have observed appear to be Johnson noise in the thermal mode and 1/f noise in the current mode. These results confirm previous conclusions regarding the sensitivity of these films as radiation detectors.     

Dark noise of Ga0.47 In0.53As photoconductive detectors

We have studied the dark noise of planar, interdigitated Ga0.47In0.53As photoconductive detectors by measuring the statistical distribution of the dark current under DC bias. The measurements reveal two interesting results: (i) the probability distribution of the dark current around its DC level is Gaussian and (ii) the standard deviation of the probability distribution grows exponentially with increasing bias voltage. Utilising these data an optimum bias level was calculated to maximise the receiver sensitivity of the detector.     

Genetic design of optimum linear and nonlinear QRS detectors

Describes an approach to the design of optimum QRS detectors. The authors report on detectors including a linear or nonlinear polynomial filter, which enhances and rectifies the QRS complex, and a simple, adaptive maxima detector. The parameters of the filter and the detector, and the samples to be processed are selected by a genetic algorithm which minimizes the detection errors made on a set of reference ECG signals. Three different architectures and the experimental results achieved on the MIT-BIH Arrhythmia Database are described     

Some consequences of spatial correlation on noise calculations

A general, theoretical example is discussed in which the spectral density S₁ of the thermal noise is 4kT2Re[Z_(ω)] rather than 4kTnRe[Z_(ω)] for space-charge-limited current with I ∝ V″. A second example is indicated in which again S_v ≠ 4kT(V/I). This establishes that in general the correlation between fluctuations in different regions of a device cannot be ignored.