The low-error-rate requirement of ultra-reliable communication poses a significant challenge to simulation-based performance evaluation of such systems, as conventional Monte Carlo (MC) simulation becomes extremely time-consuming at very low error rates. This work considers fast simulation of multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) transmission over multipath fading channels via importance sampling (IS). The efficiency of an IS simulator hinges on several key factors: 1) how sharply it can differentiate error-causing and non-error-causing subsets in the sample space, 2) how readily it can profile the probability distribution regarding these subsets, and 3) how proficiently it can generate and distribute samples over particular subsets of interest. In this perspective, we develop a novel IS method in the vein known as histogram-shaping Monte Carlo (HSMC). First, an error gauging function that is generally applicable to channel-coded MIMO-OFDM systems is proposed to highlight potentially error-causing samples in multipath fading channels. Second, we develop a sampler that not only generates random samples effectively from error-causing subsets but also facilitates fast estimation of subset-associated probabilities. New Radio (NR) link-level simulation is conducted to showcase the advantages of the proposed method, revealing approximately 10- to$10^{7}$-fold speedup compared to conventional MC simulation.

To estimate the probability Peof an error event to an accuracy in variance not exceeding ${ \in ^2}P_e^2$, conventional Monte Carlo (MC) requires approximately 1/(ε2Pe) simulation runs. Hence the low error probabilities demanded for ultra-reliable communication pose a significant issue in simulation-based evaluation of transmission performance. Advanced fast simulation techniques are therefore coveted. Conceptually, we may view a sequence of symbols transmitted by a communication system as a point in a multidimensional space. Channel distortion and noise may cause displacement of the point. The receiver commits an error if it fails to recover the transmitted point location from the received. The efficiency of a simulator depends on how sharply it can differentiate error-causing and non-error-causing displacements and how simply it can determine the probability of encountering an error-causing displacement. We consider convolutionally coded communication in which the receiver employs Viterbi decoding. We propose a corresponding noise gauging function (NGF) which can make relatively sharp differentiation between error-causing and non-error-causing noise vectors. We also propose a way to estimate the distribution of the NGF values to support error rate evaluation. The result is employed in an MC-type technique that adaptively shapes the histogram of the NGF values of the generated noise vector samples towards one that minimizes the variance in Peestimation under given number of simulation runs. Simulation considering the additive white Gaussian noise channel shows an approximately one to two orders of magnitude in speed-up compared to conventional MC.

To estimate the probability of an event, conventional Monte Carlo (MC) needs 100/Pesimulation runs to attain a 10% precision, where Peis the probability of the event. It therefore encounters difficulty in simulation-based evaluation of packet error rates for ultra-reliable communication under its stringent requirement. Many fast simulation techniques for evaluating the probability of rare events have been proposed. However, a more efficient method for coded communication systems that can adaptively exploit the code structure and concentrate the generated noise vectors to the error-prone regions is desirable. We propose a method which seeks to adaptively learn a certain optimal histogram of the noise vectors and generate the noise vectors accordingly. The said histogram is a one-dimensional function and hence is easy to work with. The adaptation mechanism is code-agnostic. Simulation with cyclic redundancy check-aided polar coding in additive white Gaussian noise shows an approximately 10-100 times speed-up compared to conventional MC.

The 3GPP LTE series of standards have made provisions for device-to-device (D2D) and vehicle- to-everything (V2X) communication in recent releases. The interface accommodating such communication is termed the sidelink (SL), which reuses some physical layer specifications originally defined for the uplink, such as single-carrier frequency-division multiple access (SC-FDMA), with some modifications. One modification is the use of doubly dense demodulation reference signals (DMRS) in the V2X setting to assist channel estimation. An SC-FDMA channel estimator typically starts with a least-squares (LS) estimation of the channel frequency response (CFR) at the DMRS. It then obtains CFR estimates for the data subcarriers by some time-frequency filtering. This work considers SL channel estimation techniques. The proposed method employs a novel linear minimum mean-square error (LMMSE) filtering mechanism in the frequency domain to reduce the noise in the LS CFR estimates and then, depending on the DMRS density, uses particularly designed LMMSE filtering or polynomial interpolation in the time domain to obtain the desired CFR estimates for the data subcarriers. Simulation results show that the method can yield superior performance over a wide range of channel conditions.

The LTE-Advanced defines a way of downlink mult- input multi-output (MIMO) transmission that supports non-codebook-based precoding with minimum resource allocation consisting of two temporally consecutive physical resource blocks (PRBs). The required channel estimation is facilitated by the specifically provided ``demodulation reference signal'' (DM-RS). However, such channel estimation is challenging in doubly (time and frequency) selective fading channels under minimum resource allocation due to the fewness of DM-RS subcarriers. We propose a decision-directed channel estimation method that addresses the issue. It conducts a sequence of decision-aided averaging of various tentative channel estimates in both the frequency and time domains to arrive at the resulting channel estimate. The method has relatvely low complexity. Simulation results on multipath fading channels demonstrate the performance of the proposed channel estimation method.

There is strong recent interest in exploiting the millimeter wave (mmWave) frequencies for cellular communication. For signal transmission studies, one needs a channel model that can simulate the spatial variation of mmWave channel impulse responses (CIRs) in treated operating environments. We consider reconstruction of spatially varying CIRs by interpolation over a set of existing CIR snapshots for some randomly scattered geographical locations. Such interpolation, however, is not trivial work, as we need to handle drifting of path delays over different spatial locations as well as deal with appearing and disappearing of paths. We propose a way to address these issues, and we present some numerical results for a typical urban area.

Generalized frequency-division multiplexing (GFDM) inherits the cyclic-prefixed (CP) block signaling structure from orthogonal frequency-division multiplexing (OFDM). The feasibility of CP-based maximum-likelihood (ML) blind synchronization for GFDM systems, however, has not been assessed in the literature. We find that such synchronization is complicated by the covariance structure of the signal which, due to nonorthogonal pulse shaping, possesses a time-varying signal power and some weak self-induced interference. Neglecting the latter and approximating the former by the average power enable us to obtain an approximate-ML solution based on a recent result on OFDM synchronization in wide-sense stationary uncorrelated scattering (WSSUS) channels. Simulations show that the resulting method for GFDM yields comparable performance, under commonly considered pulse-shaping filters, to its kin for OFDM.

The LTE-Advanced wireless communication standard specifies UE-specific reference signals (short-named DM-RS) to facilitate multi-input multi-output (MIMO) downlink channel estimation. This paper presents a linear minimum mean-square error (LMMSE)-based channel estimation technique in this context. Key to LMMSE channel estimation is the acquisition of some second-order channel statistics, for which the present work adopts a previously proposed approach that employs a parametric model for the channel autocorrelation function and estimates the model parameters from the received DM-RS. While such MIMO transmission is usually considered applicable to slow motion, our results show that the channel estimation technique itself can accommodate much faster motion.

Downlink multi-user MIMO (MU-MIMO) has been adopted in some recent wireless communication standards to enhance spectral efficiency, but it requires accurate channel state information at the transmitter (CSIT) to fully exploit its potential. In a frequency-division duplex (FDD) system, the obtaining of CSIT requires receiver feedback, and various CSI compression and feedback methods have been proposed in the literature. The present work considers an LTE-like scenario where the transmitter uses implicit CSI fed back by the receivers to reconstruct the MIMO channel coefficients, where the implicit CSI includes preferred precoding matrices and channel quality indications. To solve for the channel coefficients from these implicit CSI quantities, however, requires multiple feedbacks computed using different sounding pilots. We describe the overall design of the proposed method, formulate the corresponding mathematical problem of CSIT estimation, and derive a solution to the problem considering both time-invariant and time-varying channels. And we present some numerical results to illustrate the performance of the method.

The 3GPP LTE and LTE-A standards provide for multi-user multi-input multi-output (MU-MIMO) transmission in the uplink. But the property of reference signals (RSs) is such that care must be exercised in channel estimation to minimize the interference among different antenna channels. Typical DFT- and DCT-based channel estimation methods have low complexity but may yield relatively high inter-channel interference, especially when user equipments (UEs) are allocated narrow transmission bands. Methods that can attain better channel separation often have much higher computational requirements. In this paper, we propose an MU channel estimation technique that seeks to minimize an L1norm of error. It does not need second-order statistics as the linear minimum mean-square error (LMMSE) technique, has good numerical properties, and yields a performance between the least-square (LS), the DFT, and the LMMSE techniques.

Two-way relaying via the amplify-and-forward technique has received much recent attention. A modulo-and-forward (MF) variant of it has recently been proposed for single-antenna transmission, which can significantly reduce the peak and average relay transmission powers. The present work considers two-way relaying for multi-input multi-output (MIMO) signal transmission. We propose an MF technique for Alamouti space-time coding and spatial multiplexing. Simulation results confirm the advantage of the proposed technique in enhancing the peak and average power efficiency of the relay.

Cooperative communication can yield spatial diversity gains, but its performance can also suffer severely from the multiple carrier frequency offsets (MCFOs) induced by high-speed relative motion, in addition to Doppler spread. In orthogonal frequency-division multiplexing (OFDM) systems, such performance degradation arises as a result of intercarrier interference (ICI). We have shown previously that, in conventional non-cooperative communication, certain ICI components (called residual ICI) display high normalized autocorrelation and a partial whitening of the residual ICI can significantly benefit OFDM signal detection. In this work, we show that similar whitening can also be employed in cooperative communication to address the MCFO issue mentioned above. As an illustration, we simulate a distributed spatial-frequency block coding (SFBC) OFDM system subject to highly disparate MCFOs, where in the receiver we perform partial whitening of the residual ICI followed by maximum-likelihood sequence estimation (MLSE). The results show that the proposed method can comfortably accommodate a maximum MCFO span well exceeding one subcarrier spacing.

Orthogonal frequency-division multiplexing (OFDM) is a popular broadband wireless transmission technique, but its performance can suffer severely from the intercarrier interference (ICI) induced by fast channel variation arising from high-speed motion. Existing ICI countermeasures usually address a few dominant ICI terms only and treat the residual similar to white noise. We show that the residual ICI has high normalized autocorrelation and that this normalized autocorrelation is insensitive to the multipath channel profile as well as a variety of other system and channel conditions. Consequently, the residual ICI plus noise can be whitened in a nearly channel-independent manner, leading to significantly improved detection performance. Simulation results confirm the theoretical analysis. In particular, they show that the proposed technique can significantly lower the ICI-induced error floor in maximum-likelihood sequence estimation (MLSE) designed to address a few dominant ICI terms.

In this paper, a bit-interleaved coded modulation (BICM) scheme with an iterative receiver is proposed for asynchronous cooperative communications. In such environments, synchronous errors may be severe because relays experience different environments. Rather than treating synchronous errors as impairments, this study focuses on exploiting possible benefits of them, particularly of the possible multiple carrier frequency offsets (MCFOs). With the proposed scheme, potential space diversity of multiple relays with MCFOs is manifested as time diversity, which in turn is harvested through the carefully-designed iterative receiver. The system achieves improved diversity gain and is extremely robust even when all asynchronous parameters, including multiple Doppler effects, are considered.

We consider the design of a multi-input multi-output (MIMO) transmission system equipped with distributed, single-antenna amplify-and-forward relays. In particular, we consider how to optimize the complex forwarding coefficients of the relays to maximize the system capacity. Existing studies on MIMO relay network designs mostly concentrate on the case of single relay with multiple antennas, whose results are not applicable to distributed networks. We first analyze how the system capacity relates to the relay transmission powers and the channel coefficients. An upper bound on the asymptotic capacity at high relay powers is derived. Aided by the capacity results, we consider the optimization of relay coefficients under two noise conditions: that where the destination noise dominates the total noise and that where the relay noise dominates the total noise. It turns out that no simple analytic solutions can be found for all relay network sizes. Therefore, we propose suboptimal solutions that involve computation of optimal relay coefficients with optimal selection of relays for network sizes that can be solved analytically. The results on diversity order are found to show resemblance to that for single-hop MIMO systems employing antenna selection. Simulation results also verify the superior performance of the proposed technique.

Orthogonal frequency-division multiplexing (OFDM) transmission in time-varying channels suffers from intercarrier interference (ICI). Existing ICI countermeasures usually address a few dominant ICI terms only and treat the residual as similar to white noise. We show that the residual ICI has high normalized autocorrelation and that this normalized autocorrelation is insensitive to the maximum Doppler frequency and the multipath channel profile, among other things. The residual ICI can thus be whitened in a largely channel-independent manner, leading to significantly improved detection performance. Simulation results confirm the theoretical analysis. In particular, they show that the proposed technique can lower the ICI-induced error floor by several orders of magnitude in maximum-likelihood sequence estimation (MLSE) designed to address a few dominant ICI terms.

Current wireless multicarrier systems commonly adopt pilot-aided channel estimation, for which a simplest and least restrictive technique is polynomial interpolation in the frequency domain. For channels with large delay spreads, however, the performance of low-order polynomial interpolation suffers from modeling error. The problem may be remedied by adding a linear phase shift to the interpolator, or equivalently, a "window shift" in the time domain. We derive a method to estimate the optimal window shift, in the minimum mean-square error (MMSE) sense, for polynomial-interpolative channel estimation of arbitrary order. As a practical application, we show how to apply the resultant technique to Mobile WiMAX downlink channel estimation. In addition, we propose a method to automatically select the interpolation order based on some estimated MSE.

In linear minimum mean-square error (LMMSE) channel estimation for multicarrier transmission, how to estimate the needed channel correlation function remains a problem for systems with small number of pilots operating in time varying channels. We consider approximating the channel power delay profile by a shape characterized fully by the mean delay and the root-mean-square (RMS) delay spread. We present a novel, simple way to estimate these parameters in systems with distributed pilots. The ensuing channel estimation method is also applicable to multi-access communication. As a practical example, we also specialize the proposed technique to mobile WiMAX signals and investigate the resulting performance.

Orthogonal frequency division multiplexing (OFDM) and multiple access (OFDMA) signal receivers often employ pilot-aided channel estimation. For it, an often considered technique is frequency-domain polynomial interpolation, due to its simplicity. However, the performance of polynomial interpolators suffers in channels with large delay spreads due to modeling error. The problem can be remedied by including a linear phase to the interpolator. In this paper, we derive a method to estimate the optimal phase shift that minimizes the mean-square channel estimation error. We further consider adaptive selection of the interpolation order for best performance. As a practical application, we adapt the proposed channel estimation technique to mobile WiMAX downlink transmission and examine the resulting performance.

We consider the phase-rotated linearly interpolative channel estimation technique for multicarrier transmission. The technique models the channel frequency response between two nearby subcarriers as the product of a linear function and a linear-phase factor, where the linear-phase factor may be equivalently modeled in the time domain as a reference delay dubbed the anchor delay in this work. We show that the performance of the technique is a fourth-order function of the channel path delays and the anchor delay. We derive a method to estimate the optimal anchor delay. Analysis and simulation in a context of Mobile WiMAX downlink transmission show that, with the proposed anchor delay estimate, we can attain better performance in channel estimation than conventional linear interpolation and a previously proposed method of phase-compensated linear interpolation.

Initial downlink synchronization in orthogonal frequency-division multiple access (OFDMA)-based WiMAX transmission involves carrier frequency synchronization, timing synchronization, and preamble index identification. Due to the structure of the preamble signal, it is reasonable to take a two-stage approach in which one first estimates and compensates the timing offset and the so-called fractional carrier frequency offset (CFO) and then deals with the integral CFO and the preamble index. This paper considers joint detection of integral CFO and preamble index, under the assumption that timing and fractional CFO have been acquired to reasonable accuracy. Based on an optimization formulation, we derive a number of detection methods of different complexity and suboptimality. The methods exploit the quasi-orthogonality among the OFDMA WiMAX preamble sequences as well as the organization of the nonzero subcarriers in the preambles. Simulation results are presented to illustrate the performance of the methods.

Time-domain channel estimation techniques have been proposed for OFDM systems for their ability to yield relatively accurate estimates with only a few pilots. Key information needed in such techniques is the multipath delays of the channel. Prior approaches to estimation of multipath delays require regular pilot structures and may not work in slow fading. We propose a group matching pursuit technique for channel estimation. The technique is an extension of the orthogonal matching pursuit technique. It employs the pilots in several OFDM symbols to estimate the multipath delays in a sequential manner, where the pilots can have an arbitrary structure. Simulation results show that the proposed algorithm has superior performance.

The performance of conventional DS-CDMA systems is greatly affected by asynchronous or multipath propagation. We show that, with a certain way of multicode assignment, chip-interleaved DS-CDMA (CIDS-CDMA) can perform better in such a condition thanks to its ability to preserve the synchronous correlations among the spreading codes. Compared to the recently proposed chip-interleaved block-spread CDMA (CIBS-CDMA) that requires a single-user equalizer, the presented scheme can attain better or comparable performance in channel-coded transmission with a rake receiver that has lower complexity

We develop an adaptive decision-feedback equalization algorithm that combines blind adaptation and decision-directed LMS in a dynamic manner according to the amount of equalizer output error. By observing how the mean-square blind equalization error depends on the adaptation step size, we obtain a way of continuously varying the adaptation speed of the overall algorithm with the equalizer output error as well as a way to shift the relative emphasis between blind and decision-directed LMS operation. We also describe the way to estimate the amount of equalizer output error in the algorithm. Simulation results show that the proposed algorithm can achieve faster convergence at a lower complexity than some recently proposed hybrid adaptation algorithms.

The multimodulus algorithm (MMA) for blind equalization has good performance, but can only tolerate small carrier frequency offsets under high-order QAM. We propose a structure for joint carrier recovery (CR) and blind decision-feedback equalization (DFE), where the DFE is MMA-based. It turns out that a key point is the design and analysis of reduced-constellation phase detectors (PD) that can facilitate a wide frequency lock range and make the CR loop converge in severe intersymbol interference and noise. Based on this, we design a multistage startup procedure for joint blind DFE and CR. Simulations show that the procedure can yield fast convergence in large carrier frequency errors under high-order QAM.

We consider blind decision-feedback equalization (DFE) under high-order modulation, which presents more difficult operating requirements than lower-order modulation. We base our design on the multimodulus algorithm (MMA). To attain fast convergence speed and low steady-state mean-square error (MSE), we consider varying the adaptation step size according to the presently achieved MSE. For this we investigate the properties of the MSE under blind MMA-based DFE and, based on the results, propose a method to estimate its value. The estimate is obtained by analyzing those equalizer filter outputs whose values fall outside the boundary of the modulation's constellation. Simulation results demonstrate the effectiveness of the proposed scheme.

Multiple access interference (MAI) is a major limiting factor of DS-CDMA system capacity. Parallel interference cancellation (PIC) is an effective means to mitigate MAI. However, if the initial decisions on which the PIC is based have high error probabilities, then PIC cannot perform well. To improve the performance of PIC, we propose chip-interleaving to provide intra-bit diversity. Then the initial decisions can be more accurate so as to enhance the PIC's performance. We design a chip-interleaving scheme based on some 3GPP WCDMA system features, such as the use of the Q-branch to transmit control bits and the I-branch to transmit data bits in a QPSK-like modulation scheme. Simulation results show that the proposed chip-interleaved WCDMA (CI-WCDMA) transmission can have significant performance advantage compared to simple WCDMA in transmission over fading multipath channels with MAI.

Two important topics in equalizer design are its complexity and its training. We present a family of blind equalizers which, by incorporating a decomposition finite-impulse response filtering technique, can reduce the complexity of the convolution operation therein by about one half. The prototype algorithm in this equalizer family employs the prevalent Godard cost function. Several simplified algorithms are proposed, including a sign algorithm which eliminates multiplications in coefficient adaptation and a few delayed versions. We also study the convergence properties of the algorithms. For the prototype algorithm, we show that, in the limit of an infinitely long equalizer and under mild conditions on signal constellations and channel characteristics, there are only two sets of local minima on the performance surface. One of the sets is undesirable and is characterized by a null equalized channel response. The other corresponds to perfect equalization, which can be reached with proper equalizer initialization. For the simplified algorithms, corresponding cost functions may not exist. Some understanding of their convergence behaviors are obtained via examination of their adaptation equations. Simulation results are presented to demonstrate the performance of the algorithms.

Abstract The 3GPP WCDMA is a widely accepted third‐generation cellular system standard. By using nonorthogonal codes for different users, the multiple access interference (MAI) can be a limiting factor for system performance, as for other CDMA systems. Multiuser detection (MUD) is known to reduce MAI and improve CDMA system performance, but many such techniques have high complexity. Successive interference cancellation (SIC) is an effective MUD technique with relatively low complexity. We consider the software implementation of an SIC receiver for WCDMA uplink transmission on a commercially available general‐purpose multi digital signal processor (DSP) platform. This also goes in line with the recent interest in software‐defined radio. Issues addressed in this work include job partitioning and signal routing for multiprocessor implementation, design of SIC components (especially the channel estimator and the signal regenerator), determination of the precision of fixed‐point computations, consideration of the receiver's error performance and analysis of the implementation's complexity and efficiency. These issues are tightly coupled with the 3GPP WCDMA specifications. Because the employed platform only contains four DSPs, the implementation only considers up to three users. But this is sufficient for us to appreciate various DSP implementation issues of an SIC receiver. Moreover, by the nature of SIC, it is easy to extend the implementation to handle more users with an enlarged platform. Our present implementation achieves real‐time speed in the RAKE receiver part of the complete receiver. Due to the complexity in signal regeneration, the overall SIC receiver still falls short of the real‐time requirement when interference cancellation is activated. In fact, the platform employed presently cannot support real‐time processing when the number of multipaths is four or more, unless either the system architecture or the SIC algorithm is redesigned. Such and other ways of improvement are relegated to potential future work. Copyright © 2003 John Wiley & Sons, Ltd.

Several ways of 2D shape (or contour) description in terms of Fourier and wavelet transform coefficients have been proposed. They provide data compression capability, and some of the descriptors are invariant under scaling, rotation, and choice of the starting point for contour tracing. Several methods for 3D shape description also exist. However, they lack either the simplicity, the generality, or the data compression ability comparable to the 2D methods. We propose a generalized sampling method for efficient description of free-form 3D shape surfaces. The key idea is to warp a 3D spherical coordinate system onto the 3D surface, so that the spatial coordinates of each point on the surface may be represented parametrically as {x(/spl alpha/,/spl beta/), y(/spl alpha/,/spl beta/), z(/spl alpha/,/spl beta/)}, where /spl les//spl alpha//spl les/2/spl pi/ and 0/spl les//spl beta//spl les//spl pi/ with /spl alpha/ and /spl beta/ giving normalized arc lengths on the 3D surface. Fourier, wavelet, or other 2D transforms can then be applied to the three coordinate functions for purposes of data compression, database storage, or indexing. Simulations show that wavelet-based method yields efficient 3D shape compression based on this generalized sampling approach.

We consider space-time Viterbi equalization in nonspread-spectrum mobile communication at high data rates (over 1 Mbps). A specially designed sequence called the min-norm training sequence is used for channel estimation. The design is such that the mean-square estimation error is minimized in an AWGN environment. In addition, a channel estimation method using reduced channel length is proposed. The method can reduce the channel estimation error in low SNR environments. A Viterbi equalizer employing the proposed channel estimation method can perform better than employing least-squares channel estimation with nonreduced channel length.

We consider joint rate-distortion (R-D) coding of multiple videos over multiple frames for transmission over a shared channel, where the videos may have different frame rates. We present a solution approach under channel rate and buffer size constraints. The approach is demonstrably suboptimal theoretically in several respects. Nevertheless, simulation results show a significant reduction in distortion compared to coding without such regard for the relative R-D characteristics of the multiple videos.

Bit loading is a key issue in digital subscriber line transmission employing discrete multitone (DMT) modulation. We demonstrate that most existing algorithms are suboptimal. We present a solution based on the Lagrange multiplier approach. Numerical results are presented to illustrate the solution's performance.

We consider optimal coding of video sequences in the sense of employing an optimal selection of quantization scales under buffer and channel constraints. As a result of the delayed-coding framework, multiple rate constraints emerge, leading to the appearance of multiple Lagrange multipliers in a Lagrangian solution approach. We review the applicable Lagrangian optimization theory developed to-date, and present an efficient new solution algorithm.

We consider optimal encoding of video sequences for ATM networks. Two cases are investigated. In one, the video units are coded independently (e.g., motion JPEG), while in the other, the coding quality of a later picture may depend on that of an earlier picture (e.g., H.26x and MPEGx). The aggregate distortion-rate relationship for the latter case exhibits a tree structure, and its solution commands a higher degree of complexity than the former. For independent coding, we develop an algorithm which employs multiple Lagrange multipliers to find the constrained bit allocation. This algorithm is optimal up to a convex-hull approximation of the distortion-rate relations in the case of CBR (constant bit-rate) transmission. It is suboptimal in the case of VBR (variable bit-rate) transmission by the use of a suboptimal transmission rate control mechanism for simplicity. For dependent coding, the Lagrange-multiplier approach becomes rather unwieldy, and a constrained tree search method is used. The solution is optimal for both CBR and VBR transmission if the full constrained tree is searched. Simulation results are presented which confirm the superiority in coding quality of the encoding algorithms. We also compare the coded video quality and other characteristics of VBR and CBR transmission.

We consider optimal encoding of video sequences (for ATM networks) under buffer and channel constraints. For independent coding, we develop an algorithm which employs multiple Lagrange multipliers to find the constrained optimal bit allocation, Simulation results are presented. We also compare the coded video quality and other characteristics of variable bit-rate and constant bit-rate transmission.

We consider enhancement of the North American IS-54/136 vector sum excited linear prediction (VSELP) speech coding in the sense of reducing complexity or improving speech quality. For complexity reduction, we find a few techniques which can reduce, respectively, the pitch and excitation search complexities by approximately 40-50% at a moderate SSNR loss of roughly 0.5 dB. For quality improvement, we consider tree-structured pitch and excitation search. Aside from demonstrating a roughly 0.3-1 dB SSNR gain, we present a technique which can significantly reduce tree-search complexity. And we analyze the simulation results to obtain rule-of-thumb formulas for quasi-optimal determination of the tree parameters under different complexity and performance conditions.

We study video coding in the ATM environment under the constraints of finite encoder and decoder buffer sizes. ATM allows flexible transmission rates which can be tuned to better match picture property variation over time. We consider the leaky bucket policing mechanism and obtain the rate constraints on encoded video. We then address the optimization of video coding under the constraints. Two cases are investigated. In one the pictures are coded independently (e.g., motion JPEG), while in the other the coding quality of a later picture may depend on that of an earlier picture (e.g., MPEG). The aggregate distortion-rate relationship for the latter case exhibits a tree structure and its solution commands a higher degree of complexity than the former. We derive an efficient solution for distortion-rate relations which display certain monotonic and hierarchical characteristics. These characteristics are assumed to hold for most distortion-rate relations. Realistic nonconvex distortion-rate relations can be handled with a minor modification of the algorithm.

This paper reviews the telephone loop plant characteristics, current DSL (digital subscriber line) technologies, recent efforts in video coding standards, and the interrelationship between DSL technologies and visual communications over subscriber lines. In overview of the loop plant characteristics we examine its physical makeup and transmission properties, where for the latter we discuss frequency and time responses of wire-pair lines and the impairments of echo, crosstalk, impulse noise, and radio frequency interference. We trace the historical development of various DSL technologies and comment on possible future evolution. Transmission technologies used in the ISDN basic-access DSL, the high bit-rate DSL, and the asymmetric DSL are portrayed. And the issue of spectrum compatibility among different transmission systems is explained. Several important video coding standards are briefly described, including ITU-T's H.261 and ISO's JPEG and MPEG series, which are either completed or emerging. The synergistic relationship between these standards and the DSL technologies is elucidated. As a result, DSL technologies provide the potential of delivering certain broadband services well in advance of direct fiber access for telephone subscribers.>

We point out that a prevalent form of fractal image coding can be viewed as a kind of generalized predictive coding. Several key issues in predictive coding are the prediction gain, the design of codebooks for predictors and prediction residuals, shaping of reconstruction errors, and codec complexity. Fractal coding can yield higher prediction gains than conventional predictive coding by its use of noncausal predictors and long-term predictors. However, noncausal prediction necessitates iterative decoding and long-term predictors require search over a large area, both of which increase codec complexity. Design of predictors and prediction codebooks for fractal coding has relied much on heuristics. Drawing on known results about predictive coding, we outline several directions for codec design, among which are short-term prediction and transform coding or vector quantization of prediction residuals. Shaping of reconstruction errors by noise-feedback or analysis-by-synthesis coding may also be beneficial.>

A video encoder has the task of producing lowest-distortion coded video subject to some constraints on delay, rate, and buffer conditions. We present a general optimization approach to this problem in a framework of delayed coding and we motivate a certain formulation of the optimization objective. Two forms of distortion measures are considered, namely, the maximum distortion and the total distortion, each defined over a segment of the video to be coded. These distortion measures are chosen for their mathematical tractability and practical importance. A solution (computational algorithm) for each case is described. Subject to some conditions, the solutions may be suboptimal. Simulation results show an improved performance with this approach compared to a simple typical approach which varies the quantization scale linearly with the encoder buffer level.

The author presents a theory on MMSE (minimum mean-squared error) decision-feedback equalization which augments previously published results by allowing both a correlated symbol sequence and a fractionally spaced DFE (decision-feedback equalizer) forward filter. This theory facilitates calculating the potential DSL (digital subscriber line) transmission performance in cases of correlated line codes, especially for situations where one or both of the DFE filters are infinite in length. The situation of an infinite-length DFE is of interest because it provides information on the limit of MMSE equalization and can thus serve as a benchmark against which the performance of a finite-length DFE may be compared. The author also presents a few numerical examples of the performance of MMSE decision-feedback equalization in DSL transmission at ISDN (integrated services digital network) basic access rates with several well-known line codes.>

An integral part of an ISDN (integrated services digital network) is the provision of full-duplex digital transmission capability over voice-grade metallic subscriber lines with all the associated disturbances from echo, intersymbol interference, and crosstalk, among other things. The author presents a theory for analyzing the optimal performance, in the MMSE (minimum-mean-squared error) sense, of full-duplex transceiver structures incorporating echo cancelers and decision-feedback equalizers. The theory augments previously published results by allowing a colored input signal and a fractionally spaced multitap MMSE forward filter in the decision-feedback equalizer. The properties of and efficient ways of calculating the MMSE solutions for various types of line codes, including the precoded partial-response codes and the block codes, are investigated. The author discusses how the MMSE is related to the ubiquitous SNR (signal-to-noise ratio) measure and the concerns associated with using it to gauge the transmission performance.>

For pt.I see ibid., vol.38, no.1, p.31-8 (1990). A comparison is made of the transmission performance of various line codes in the subscriber line environment and at a line rate around 260 kb/s. The simulated transmission environment includes transhybrid echo, intersymbol interference, and near-end crosstalk from identical digital-subscriber-line transmission systems. The simulated transceiver incorporates an echo canceller and a decision-feedback equalizer that are optimal in the minimum-mean-squared-error sense. Both the echo canceller and the decision-feedback equalizer have a tap spacing equal to the symbol period. The line codes investigated include five block codes that offer reduced baud rates and five codes that do not reduce the baud rate. Under the conditions of this study, block codes do show an advantage over nonblock codes, with the 2B1Q block code yielding the best performance.>

The authors present a real-time single DSP prototype of a 16-kb/s subband speech coder, using a single digital signal processor, for application to digital portable radio communications. The system architecture, coding algorithm, firmware, and hardware of this coder are addressed. Careful attention has been given to the many special design requirements for interfacing to a time-division multiple-access radio link. The coder uses nonlinear quantization improvement in speech quality with negligible added complexity. A single-board full-duplex prototype, based on a TMS320C25, has been designed and delivers good speech quality.>

The author investigates the potential transmission performance of pair-wire subscriber lines at the higher rate of 800 kb/s, with particular reference to digital subscriber line transmission for ISDN (integrated services digital network) basic access. Block modulation schemes of 1-4 dimensions, at a rate of 2 bits per dimension, are considered. Time-division multiplexing is used to combine the multiple dimensions for transmission over a single-waveform channel, namely, the subscriber line. The channel noise is assumed to be additive and dominated by near-end crosstalk. MMSE (minimum mean-squared error) decision-feedback equalization is used to deal with the noise and the intersymbol interference. Using the theory developed, the potential performance of some simple lines is calculated. The coding gain of a multidimensional modulation scheme is found to be fully preserved after transmission if the equalizer is infinite in length. However, the gain realized can be much lower, or none at all, if the equalizer is only moderate in length. This latter phenomenon is due to the fact that the noise at the decision point is coloured, due to the inability of the equalizer to whiten it sufficiently.>