Worst-case power-constrained noise for binary-input channels

Additive noise channels with binary-valued inputs and real-valued outputs are considered. The maximum error probability and the minimum channel capacity achieved by any power-constrained noise distribution are obtained. A general framework which applies to a variety of performance measures shows that the least-favorable noise distribution is, in general, a mixture of two lattice probability mass functions. The framework holds for m-ary input constellations on finite-dimensional lattices.<>     

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     

Nearest neighbor decoding for additive non-Gaussian noise channels

We study the performance of a transmission scheme employing random Gaussian codebooks and nearest neighbor decoding over a power limited additive non-Gaussian noise channel. We show that the achievable rates depend on the noise distribution only via its power and thus coincide with the capacity region of a white Gaussian noise channel with signal and noise power equal to those of the original channel. The results are presented for single-user channels as well as multiple-access channels, and are extended to fading channels with side information at the receiver     

Sequence detection and adaptive channel estimation for ISI channels under class-a impulsive noise

In this paper, sequence detection and channel estimation for frequency-selective, intersymbol interference (ISI)-producing channels under Class-A impulsive noise are considered. We introduce a novel suboptimum sequence detection (SSD) scheme and show that although SSD employs a simplified metric, it achieves practically the same performance as maximum-likelihood sequence detection (MLSD). For both SSD and MLSD, a lower bound on the achievable performance is derived, which is similar to the classical matched-filter bound for frequency-selective (fading) channels under Gaussian noise. For channel estimation, we adopt a minimum entropy criterion and derive efficient least-mean-entropy and recursive least-entropy algorithms. For both adaptive algorithms, we analyze the steady-state channel-estimation error variance. Theoretical considerations and simulation results show that in Class-A impulsive noise, the proposed sequence detection and adaptive channel-estimation schemes yield significant performance gains over their respective conventional counterparts (designed for Gaussian noise). Although the novel algorithms require knowledge of the Class-A noise-model parameters, their computational complexity is comparable to that of the corresponding conventional algorithms.     

Particle filtering for demodulation in fading channels withnon-Gaussian additive noise

An efficient particle filtering algorithm is developed to solve the problem of demodulation of M-ary modulated signals under conditions of fading channels in the presence of non-Gaussian additive noise. Simulations for MDPSK signals are presented. The results show that the algorithm outperforms the current methods     

Mutual information in stationary channels with additive noise

A continuous time stationary channel with additive noise presented byY(t) = X(t) + Z(t)is considered, where{X(t)}and{Z(t)}are mutually independent stationary processes representing the channel input and the noise, respectively, and{Y(t)}represents the channel output. It is shown that, under some general assumptions, the mutual information between the input{ X(t); 0 leq t leq T }and the output{ Y(t); 0 leq t leq T }can be expressed in the formAT + B(T)with a constantAand a functionB(T)given in terms of the conditional mutual informations between the "past" and the "future" given the "present" of the output and the noise. It is also shown that the remainder termB(T)converges to a constant asTtends to infinity.     

On the design of raptor codes for binary-input gaussian channels

This paper studies the problem of Raptor-code design for binary-input AWGN (BIAWGN) channels using the mean-LLR-EXIT chart approach presented in [1]. We report that there exist situations where such a design approach may fail or fail to produce capacity-achieving codes, for certain ranges of channel SNR. Suggestions and discussions are provided pertaining to the design of Raptor codes for BIAWGN channels using the mean-LLR-EXIT chart.     

On error exponents of modulo lattice additive noise channels

Modulo lattice additive noise (MLAN) channels appear in the analysis of structured binning codes for Costa's dirty-paper channel and of nested lattice codes for the additive white Gaussian noise (AWGN) channel. In this paper, we derive a new lower bound on the error exponents of the MLAN channel. With a proper choice of the shaping lattice and the scaling parameter, the new lower bound coincides with the random-coding lower bound on the error exponents of the AWGN channel at the same signal-to-noise ratio (SNR) in the sphere-packing and straight-line regions. This result implies that, at least for rates close to channel capacity, 1) writing on dirty paper is as reliable as writing on clean paper; and 2) lattice encoding and decoding suffer no loss of error exponents relative to the optimal codes (with maximum-likelihood decoding) for the AWGN channel.     

A coding scheme for additive noise channels with feedback--II: Band-limited signals

In Part I of this paper, we presented a scheme for effectively exploiting a noiseless feedback link associated with an additive white Gaussian noise channel with {em no} signal bandwidth constraints. We now extend the scheme for this channel, which we shall call the wideband (WB) scheme, to a band-limited (BL) channel with signal bandwidth restricted to(- W, W). Our feedback scheme achieves the well-known channel capacity,C = W ln (1 +P_{u,v}/N_{0} W), for this system and, in fact, is apparently the first deterministic procedure for doing this. We evaluate the fairly simple exact error probability for our scheme and find that it provides considerable improvements over the best-known results (which are lower bounds on the performance of sphere-packed codes) for the one-way channel. We also study the degradation in performance of our scheme when there is noise in the feedback link.     

Adaptive signal detection over fast frequency-selective fading channels under class-A impulsive noise

The problem of adaptive detection of signals contaminated with Middleton's class-A impulsive noise and transmitted over a fast time-varying frequency-selective fading channel is addressed. Adaptive algorithms are derived to update the estimate of the channel parameters to the detector. A theoretical performance evaluation of the detector is provided. Computer simulations are performed to validate the theoretical developments.     

Audio watermarking under desynchronization and additive noise attacks

Digital watermarking is often modeled as the transmission of a message over a noisy channel denoted as "watermark channel". Distortions introduced by the watermark channel result mainly from attacks and may include interference from the original signal. One of the main differences with classical transmission situations stems from the fact that perceived distortions have to be taken into account. However, measuring the perceived impact an attack has on a watermarked signal is currently an unsolved problem. Possible means of circumventing this problem would be 1) to define the distortion in a so-called "perceived domain" and define an "ad hoc" equivalence between objective and perceived distortion or 2) to define an "equivalent distortion" by removing from the attack noise the part that is correlated to the host signal. This paper concentrates on the second approach and first shows that the resulting "equivalent" attack is a particular case of a thoroughly studied channel: filtering plus additive noise. However, the approach in this paper emphasizes the fact that the additive noise in the model has to be decorrelated with the signal. Then, the formalism is applied to (desynchronization plus noise) attacks on audio signals. In this context, this paper provides the corresponding capacities, as well as optimal "attack" and "defense" strategies in a game theory context.     

Signal space detection for recording channels with jitter noise

A delay-constrained sequence detector is considered for recording channels whose major impediments include intersymbol interference (ISI) and magnetic transition jitter noise. The jitter noise is data-dependent, and a given noise sample is correlated with neighboring noise samples. A sequence detector with a finite decision delay can be formulated in a finite dimensional vector space. For a correlated noise channel, the decision boundary is generally quadratic. We present a technique for obtaining a minimal set of hyperplanes approximating a quadratic decision boundary with a negligible performance loss. In this process, a distance measure, which is consistent with the notion of the effective SNR, is defined and used as a design parameter to trade the complexity and performance. As an achievable performance bound, we derive the effective SNR for the maximum-likelihood sequence detector (MLSD) for these channels. The performance of the partial response maximum likelihood (PRML) detector commonly adopted for current data storage channels as well as the Viterbi algorithm (VA) based on the traditional Euclidean metric, which serves as the MLSD for additive white Gaussian noise, are also analyzed and compared with that of the proposed signal space detector     

多加性QoS约束下的链路分离路由算法

对多个加性QoS约束下的链路分离路径问题进行了研究,针对现有算法求解结果依赖于网络结构,难以保证对任意网络都可求得可行解和最优解的问题,提出了一种与网络结构无关的多约束链路分离路径路由算法(MCLPRA,multiple constrained link-disjoint path routing algorithm).该算法基于SAMCRA,采用对解空间先分类,然后按类进行处理和搜索的方法,引入了控制搜索深度的参数,可保证对任意网络都能求得可行解.理论分析表明,MCLPRA能够在现有算法不能求解的情况下解得可行解和最优解.仿真结果显示,MCLPRA的可行解平均求解成功率明显高于现有算法且所求路径对长度也比现有算法更短.     

Capacity-achieving input distributions for some amplitude-limited channels with additive noise (Corresp.)

An additive noise channel wherein the noise is described by a piecewise constant probability density is shown to reduce to a discrete channel by means of an explicit construction. In addition, conditions are found which describe a class of continuous amplitude-limited channels for which the capacity-achieving input distribution is binary.     

A coding scheme for additive noise channels with feedback--I: No bandwidth constraint

In some communication problems, it is a good assumption that the channel consists of an additive white Gaussian noise forward link and an essentially noiseless feedback link. In this paper, we study channels where no bandwidth constraint is placed on the transmitted signals. Such channels arise in space communications. It is known that the availability of the feedback link cannot increase the channel capacity of the noisy forward link, but it can considerably reduce the coding effort required to achieve a given level of performance. We present a coding scheme that exploits the feedback to achieve considerable reductions in coding and decoding complexity and delay over what would be needed for comparable performance with the best known (simplex) codes for the one-way channel. Our scheme, which was motivated by the Robbins-Monro stochastic approximation technique, can also be used over channels where the additive noise is not Gaussian but is still independent from instant to instant. An extension of the scheme for channels with limited signal bandwidth is presented in a companion paper (Part II).     

Signal detection games with power constraints

Formulates and solves maximin and minimax detection problems for signals with power constraints. These problems arise whenever it is necessary to distinguish between a genuine signal and a spurious one designed by an adversary with the principal goal of deceiving the detector. The spurious (or deceptive) signal is subject to certain constraints, such as limited power, which preclude it from replicating the genuine signal exactly. The detection problem is formulated as a zero-sum game involving two players: the detector designer and the signal designer. The payoff is the probability of error of the detector, which the detector designer tries to minimize and the deceptive signal designer to maximize. For this detection game, saddle point solutions-whenever possible-or otherwise maximin and minimax solutions are derived under three distinct constraints on the deceptive signal power; these distinct constraints involve lower bounds on (i) the signal amplitude, (ii) the time-averaged power, and (iii) the expected power. The cases of independent and identically distributed and correlated signals are considered     

Scheduling tests for VLSI systems under power constraints

This paper considers the problem of testing VLSI integrated circuits in minimum time without exceeding their power ratings during test. We use a resource graph formulation for the test problem. The solution requires finding a power-constrained schedule of tests. Two formulations of this problem are given as follows: (1) scheduling equal length tests with power constraints and (2) scheduling unequal length tests with power constraints. Optimum solutions are obtained for both formulations. Algorithms consist of four basic steps. First, a test compatibility graph is constructed from the resource graph. Second, the test compatibility graph is used to identify a complete set of time compatible tests with power dissipation information associated with each test. Third, from the set of compatible tests, lists of power compatible tests are extracted. Finally, a minimum cover table approach is used to find an optimum schedule of power compatible tests     

Adaptive detection for unknown noise power spectral densities

The detection of a known broadband signal in colored noise of unknown power spectral density is addressed. Motivated by the consistency of the integrated periodogram, a new detector is proposed. Its asymptotic performance is proven to be only slightly poorer than the optimal but unrealizable Neyman-Pearson detector. It also possesses the CFAR property asymptotically and should therefore be quite valuable in practice. For finite data records, it is shown by computer simulation to significantly outperform the conventional matched filter (without prewhitening) under realistic conditions encountered in practice     

Concurrent detection of power supply noise

We propose a methodology for the concurrent detection of power supply noise affecting a general synchronous system and exceeding a tolerance bound to be chosen according to the system's constraints. Our solution is based on a suitable self-checking scheme which concurrently monitors a signal of the system clock distribution network and which is, by design, able to provide an output error message upon the occurrence of power supply noise. The produced error indication can then be exploited to recover from the detected noise (thus guaranteeing system's correct operation), or to accomplish diagnosis. Our scheme negligibly impacts system's performance, features self-checking ability with respect to a wide set of possible internal faults and keeps on revealing concurrently the occurrence of power supply noise, despite the possible presence of noise affecting also ground.     

Discrete-time chaotic systems synchronization performance under additive noise

In recent decades many articles have discussed the possibilities of chaos applied in communications. However, the vast majority consider in practical terms the ideal channel condition, which is clearly a restringing condition. Some papers show that when there is an additive noise, the synchronization error often disrupts communication. In this work, we present results of a comparison between synchronization error due to additive Gaussian noise when the transmitter and receiver are implemented by single or coupled maps.