Time-varying encoders for constrained systems: an approach tolimiting error propagation

Time-varying encoders for constrained systems are introduced. The approach generalizes the state-splitting (ACH) algorithm in a way that yields encoders consisting of multiple phases, with encoding proceeding cyclically from one phase to the next. The framework is useful for design of high-rate codes with reduced decoder error propagation and reduced complexity     

Improved Gilbert-Varshamov bound for constrained systems

Nonconstructive existence results are obtained for block error-correcting codes whose codewords lie in a given constrained system. Each such system is defined as a set of words obtained by reading the labels of a finite directed labeled graph. For a prescribed constrained system and relative minimum distance δ, the new lower bounds on the rate of such codes improve on those derived recently by V.D. Kolesnik and V.Y. Krachkovsky (1991). The better bounds are achieved by considering a special subclass of sequences in the constrained system, namely, those having certain empirical statistics determined by δ     

Bit-rate control for MPEG encoders

Bit-rate control is a central problem in designing image sequence compression systems. In this paper we describe a new approach to bit-rate control for inter-frame encoders such as MPEG encoders. This approach uses concepts from control theory. Its central feature is a surprisingly simple but effective model for the encoder, which consists of a gain element, a delay element and additive noise. In our system we control the bit-rate with a PI-controller which is set to achieve two objectives: (1) we want the picture quality to be as uniform as possible, and (2) we want to use as closely as possible the available amount of bits. It is demonstrated in the paper that these two objectives, when considered separately, lead to contradictory settings of the controller. This dilemma can be solved by using Bit Usage Profiles that indicate how the bits have to be spread over the pictures. The effectiveness of the approach is demonstrated by designing a bit-rate control for an MPEG encoder that has a nearly constant bit-rate per group of pictures (GOP). Such a bit-rate control is of high value for applications like magnetic recording, where a constant bit-rate per GOP is required in order to realize playback trick modes, e.g. the fast forward mode.     

Constellation labeling for linear encoders

This paper investigates optimal constellation labeling in the context of the edge profile. A constellation's edge profile lists the minimum-distance edge for each binary symbol error. The paper introduces the symmetric-ultracomposite (SU) labeling structure and shows that this structure provides undominated edge profiles for 2ⁿ-PSK, 2 ⁿ-PAM, and 2²ⁿ-point square QAM. The SU structure is a generalization of the commonly used reflected binary Gray code. With the proper choice of basis vectors, SU labeling can support either set-partition or Gray-code labeling of 2ⁿ-PSK, 2ⁿ-PAM, and 2²ⁿ-point square QAM. Notably, there are Gray-code and set-partition labelings that do not have the SU structure. These labelings yield inferior edge profiles. The SU structure does not apply to cross constellations. However, for any standard cross constellation with 32 or more points, a quasi-SU labeling structure can approximate the SU structure. With the correct choice of basis, quasi-SU labelings produce quasi-Gray labelings. However, the quasi-SU structure cannot support set-partition labeling. In fact, the quasi-SU structure provides a better edge profile than standard set-partition labeling. Thus, for cross constellations there is a choice between edge profile optimality and the group structure provided by set-partitioning. Here, the correct choice depends on whether the encoder trellis has parallel branches     

An analysis on optimal rates of BDB encoders for RLL and MTR systems

In most recording channels, modulation codes are employed to transform user data to sequences that satisfy some desirable constraint. Run-length-limited (RLL(d,k)) and maximum transition run (MTR(j,k)) systems are examples of constraints that improve timing and detection performance. A modulation encoder typically takes the form of a finite-state machine. Alternatively, a look-ahead encoder can be used instead of a finite-state encoder to reduce complexity. Its encoding process involves a delay called look-ahead. If the input labeling of a look-ahead encoder allows block decodability, the encoder is called a bounded-delay-encodable block-decodable (BDB) encoder. These classes of encoders can be viewed as generalizations of the well-known deterministic and block-decodable encoders. Other related classes are finite-anticipation and sliding-block decodable encoders. In this paper, we clarify the relationship among these encoders. We also discuss the characterization of look-ahead and BDB encoders using the concept of path-classes. To minimize encoder complexity, look-ahead is desired to be small. We show that for nonreturn to zero inverted (NRZI) versions of RLL|,(0,k),RLL(1,k), and RLL(d,infin), a BDB encoder does not yield a higher rate than an optimal block-decodable encoder. However, for RLL(d,k) such that dges4 and d+2lesk相似文献   

Optical encoders for small drives

Rotor position and speed information is essential for the control of motors, In fact, several encoders for motors with diameters greater than 13 mm already exist on the market, but most of the solutions are too expensive or unsuitable for smaller applications. Considering the low cost of small drives and their growing number in automation systems, there is a need for encoder solutions which do not increase overall system cost, but offer a controllable device, After a brief summary of existing angular encoders, their miniaturization problems are highlighted, followed by suggestions of suitable architectures for small devices.     

Tradeoff functions for constrained systems with unconstrained positions

We introduce a new method for analyzing and constructing combined modulation and error-correcting codes (ECCs), in particular codes that utilize some form of reverse concatenation and whose ECC decoding scheme requires easy access to soft information. We expand the work of Immink and Wijngaarden and also of Campello, Marcus, New, and Wilson, in which certain bit positions in the modulation code are deliberately left unconstrained for the ECC parity bits, in the sense that such positions can take on either bit value without violating the constraint. Our method of analysis involves creating a single graph that incorporates information on these unconstrained positions directly into the constraint graph without any assumptions of periodicity or sets of unconstrained positions, and is thus completely general. We establish several properties of the tradeoff function that relates the density of unconstrained positions to the maximum code rate. In particular, the tradeoff function is shown to be concave and continuous. Algorithms for computing lower and upper bounds for this function are presented. We also show how to compute the maximum possible density of unconstrained positions and give explicit values for the runlength-limited (RLL(d,k)) and maximum-transition-run (MTR(j,k)) constraints.     

Robust constrained linear receivers for CDMA wireless systems

For code-division multiple access (CDMA) communication systems, many constrained linear receivers have been developed to suppress multiple access interference. The linearly constrained formulations are generally sensitive to multipath fading and other types of signal mismatch. We develop robust linear receivers by exploring appropriate constraints. Multiple linear constraints are exploited to preserve the output energy that is scattered in multipath channels. In addition, a quadratic inequality constraint on the weight vector norm is used to improve robustness with respect to imprecise signal modeling. These constraints can be applied to the minimum output energy (MOE) detector to mitigate the signal mismatch problem and to the decision directed minimum mean square error (MMSE) detector to prevent error propagation and eliminate the need for training sequences at startup. Adaptive implementations for the proposed detectors are presented using recursive least square (RLS) updating in both the direct form and the partitioned linear interface canceller (PLIC) structure. Simulations are performed in a multipath propagation environment to illustrate the performance of the proposed detectors     

Rank constrained temporal-spatial matrix filters for CDMA systems

Efficient interference suppression techniques are needed to maximally utilize the potential gains of code-division multiple-access systems. In this letter, a receiver structure which combines multiuser detection (temporal filtering) and receiver beamforming (spatial filtering) in a multipath environment is considered. Following previous work, we model the receiver as a linear matrix filter and use the minimum mean-squared error (MMSE) as the performance criterion. Motivated by the high complexity of the optimum receiver, we propose rank constrained temporal-spatial filters which are simpler and near-optimum. The MSE is minimized subject to a structural constraint, using an iterative algorithm based on alternating minimization. The constraint on the receiver matrix filter narrows down the solution space, which helps to solve the optimization problem more efficiently. The constraint can be set appropriately by the system designer to achieve the desired tradeoff between performance and complexity. Numerical results indicate that a performance close to that of the optimum filter can be achieved with a simple iterative structure, even in highly loaded systems. Adaptive implementation of the rank constrained filters is derived. A new adaptive scheme is proposed which is a combination of the alternating minimization and the least mean squares methods. The convergence properties are investigated along with the effect of the number paths.     

Optimal filtering for multirate systems

For a multirate system where the output sampling is slower than the input updating, this brief aims at designing filters for fast state estimation in the H/sub 2/ and H/sub /spl infin// settings. Because of the multirate nature, linear matrix inequality solutions to the design problems involve a nonconvex constraint, which is numerically tackled by the product reduction algorithm. Finally, a design example is given and the effectiveness of the approach is illustrated.     

Optimal constrained representation and filtering of signals

A random signal is observed in independent random noise. We are addressing the problem of finding the optimum signal estimate that is constrained to lie in a given linear subspace. The optimality is defined in the sense of weighted mean square error. In the second step, we find the optimum linear subspace of given dimensionality. It is shown to be the linear manifold spanned by the eigenvectors of the simultaneous diagonalization of the signal and noise covariance, that correspond to the largest eigenvalues. The result is valid for both discrete and continuous time. For large observation time and stationary signals, it is shown that the constrained optimal estimate is determined by the two spectral densities and a weighted Fourier Transform of the noise observations. The above result applies to both discrete time and continuous time signals.The Wiener filter emerges as a special case of the constrained filtering estimate, when the linear subspace is enlarged to coincide with the total measurement space.     

Basic encoders for Abelian convolutional codes

A specific criterion is presented to check the noncatastrophic property of encoders for a convolutional code with a certain type of automorphism. In most cases to which the criterion is applicable, only a very small amount of computation is required.     

Optimal waveform selection for tracking systems

Investigates adaptive waveform selection schemes where selection is based on overall target tracking system performance. Optimal receiver assumptions allow the inclusion of transmitted waveform specification parameters in the tracking subsystem defining equations. The authors give explicit expressions for two one-step ahead optimization problems for a single target in white Gaussian noise when the tracker is a conventional Kalman filter. These problems may be solved to yield the most improvement possible in tracking performance for each new transmitted pulse. In cases where target motion is restricted to one dimension, closed-form solutions to the local (one step ahead) waveform optimization problem have been obtained. The optimal waveform selection algorithms in the paper may be included with conventional Kalman filtering equations to form an enhanced Kalman tracker. Simulation examples are presented to illustrate the potential of the waveform selection schemes for the optimal utilization of the capabilities of modern digital waveform generators, including multiple waveform classes. The extension of the basic waveform optimization scheme to more complex tracking scenarios is also discussed     

Optimal design for cellular mobile systems

Cellular zone design parameters for a land mobile communication system are clarified. System parameters having a strong influence on cellular system performance are discussed and some problems encountered when system parameters are changed are examined.     

Sliding block codes between constrained systems

The construction of finite-state codes between constrained systems called sofic systems introduced by R. Karabed and B. Marcus (1988) is continued. It is shown that if Σ is a shift of finite type and S is a sofic system with k/n=h(S )/h(Σ), where h denotes entropy, there is a noncatastrophic finite-state invertible code from Σ to S at rate k:n if Σ and S satisfy a certain algebraic condition involving dimension groups, and Σ and S satisfy a certain condition on their periodic points. Moreover, if S is an almost finite type sofic system, then the decoder can be sliding block     

Lossless sliding-block compression of constrained systems

A method is presented for designing lossless sliding-block compression schemes that map constrained sequences onto unconstrained ones. The new compression scheme is incorporated into a coding technique for noisy constrained channels, which has applications to magnetic and optical storage. As suggested previously by Immink (see ibid., vol.43, p.1389-99, 1997), the use of a lossless compression code can improve the performance of a modified concatenation scheme where the positions of the error-correcting code and constrained code are reversed (primarily in order to eliminate error propagation due to the constrained code). Examples are presented that demonstrate the advantage of using sliding-block compression over block compression in a noisy constrained setting     

Probabilistic learning technique for improved accuracy ofsinusoidal encoders

Sinusoidal-encoder-based digital tachometers are often limited by nonidealities in both encoder construction and interface electronics. A probabilistically based compensation technique is presented which dispenses with the need for specialized calibration equipment. A code-density array, obtained during a learning phase, is utilized to yield a compensation function which approximates to the average relationship over the mechanical cycle between the calculated electrical angle (as determined by an arctangent-based algorithm) and the actual angle. An extended version of this probabilistically compensated sinusoidal encoder technique is used to compensate for variations in the encoder characteristics as it rotates through a mechanical cycle. An analysis of the learning-time requirements of the system is presented. Practical results, utilizing performance measures common in the testing of analog-to-digital converters, confirm the utility of the method. An example of the benefits which accrue from the inclusion of the enhanced sensor in closed-loop systems is also provided     

Velocity and acceleration estimation for optical incremental encoders

Optical incremental encoders are extensively used for position measurements in motion systems. The position measurements suffer from quantization errors. Velocity and acceleration estimations obtained by numerical differentiation largely amplify the quantization errors. In this paper, the time stamping concept is used to obtain more accurate position, velocity and acceleration estimations. Time stamping makes use of stored events, consisting of the encoder counts and their time instants, captured at a high resolution clock. Encoder imperfections and the limited resolution of the capturing rate of the encoder events result in errors in the estimations. In this paper, we propose a method to extend the observation interval of the stored encoder events using a skip operation. Experiments on a motion system show that the velocity estimation is improved by 54% and the acceleration estimation by 92%.     

Optimal video placement for hierarchical video-on-demand systems

We have been implementing a VOD system over ATM networks based on a hierarchical three-level network architecture. One of the most important design problems is how to organize video programs stored at different level of servers. In this paper, we propose an optimal video placement strategy which gives the optimal number of video copies should be stored at each level of server such that the cost function can be minimized while a lower bound of the request rejection probability for each video is guaranteed. Our major contribution is that we model the time-variant request arrivals as a non-homogeneous Poisson process     

Optimal linear-quadratic systems for detection and estimation

The problem of linear-quadratic systems for detection has long been solved by assuming the deflection criterion and Gaussian noise. It is shown here that the Gaussian assumption can be removed, and a complete solution is presented for an arbitrary probability distribution with finite fourth-order moments. The optimal solution can always be obtained by solving a linear system of equations. Some properties of the optimal systems are developed for particular examples of nonGaussian noise. It is shown that there is a strong relationship between linear-quadratic optimal detection and optimal estimation, which extends results known for the purely linear case