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Objective: Local activation time (LAT) mapping of cardiac chambers is vital for targeted treatment of cardiac arrhythmias in catheter ablation procedures. Current methods require too many LAT observations for an accurate interpolation of the necessarily sparse LAT signal extracted from intracardiac electrograms (EGMs). Additionally, conventional performance metrics for LAT interpolation algorithms do not accurately measure the quality of interpolated maps. We propose, first, a novel method for spatial interpolation of the LAT signal which requires relatively few observations; second, a realistic sub-sampling protocol for LAT interpolation testing; and third, a new color-based metric for evaluation of interpolation quality that quantifies perceived differences in LAT maps. Methods: We utilize a graph signal processing framework to reformulate the irregular spatial interpolation problem into a semi-supervised learning problem on the manifold with a closed-form solution. The metric proposed uses a color difference equation and color theory to quantify visual differences in generated LAT maps. Results: We evaluate our approach on a dataset consisting of seven LAT maps from four patients obtained by the CARTO electroanatomic mapping system during premature ventricular complex (PVC) ablation procedures. Random sub-sampling and re-interpolation of the LAT observations show excellent accuracy for relatively few observations, achieving on average 6% lower error than state-of-the-art techniques for only 100 observations. Conclusion: Our study suggests that graph signal processing methods can improve LAT mapping for cardiac ablation procedures. Significance: The proposed method can reduce patient time in surgery by decreasing the number of LAT observations needed for an accurate LAT map. [ABSTRACT FROM AUTHOR]

In this correspondence, we study design of transceiver antenna arrays and its impact on spectral efficiency of low-power systems. Our primary motivation is construction of practical and portable multi-antenna configurations with a very small and a-priori fixed volume for placing antennas. Using spectral efficiency as a target metric for array optimization, we show that any array configuration, transmit or receive, can be characterized via a parameter that we interpret as "effective degrees of freedom." For any array configuration, effective degrees of freedom describes an equivalent uncorrelated array, which results in the same low-power behavior of spectral efficiency. Joint optimization of transmit and receive antenna configurations decouples into maximizing effective degrees of freedom for transmitter and receiver separately. To achieve this goal, we introduce and study a theoretical benchmark of "limiting degrees of freedom," which is the least upper bound on effective degrees of freedom, evaluated over all configurations with finite number of antennas. Limiting degrees of freedom therefore describes the best possible performance for any transceiver array which confines its elements inside a given space. We compute a closed-form expression for limiting degrees of freedom of a circular geometry. Finally, we present numerical procedure and examples for designing linear and square arrays with nonuniform spacing, which typically exhibit significant spectral efficiency gains over uniform arrays. Index Terms--Antenna arrays, multi-antenna communications, multiple-input-multiple-output (MIMO).

In this letter, we use power and rate adaptation to maximize the throughput in cooperative relay networks when limited feedback links to the transmitter nodes exist. We observe that, for a finite rate of feedback, the throughput maximizing outage probability can be relatively high. This suggests using higher rate codes and allowing some outages in an effort to increase the overall network throughput. Our analysis also reveals that the relaying transmission paradigm offers significant throughput gains over direct transmission for any rate of the feedback link. Our work not only demonstrates the power of cooperative coding, but also suggests the importance of network protocols incorporating feedback to allow for throughput maximization. Index Terms--Finite-rate feedback, outage probability, rate control, relay coding.

In this paper, we consider practical methods to approach the theoretical performance limits in the fading relay channel under different assumptions of transmitter channel knowledge. Specifically, we consider two degrees of transmitter channel knowledge: 1) perfect feedback is available and power control is employed and 2) no channel state knowledge is available at the transmitters and only spatial power allocation is possible. First, when perfect feedback is available, the optimal power control policy determines the ultimate limits of performance for constant rate transmission in the slow fading environment. However, in practice, perfect channel knowledge is not possible at the transmitters due to the finite capacity of the feedback links. We find practical methods to approach this performance limit through the use of power control with finite rate feedback. The finite-rate feedback results are shown for the low-complexity, full-diversity amplify-and-forward (AF) protocol. Interestingly, we see that only a few feedback bits are needed to achieve most of the gains of the optimal perfect feedback power control algorithm. Second, we consider the performance limit when the transmitters have no channel state knowledge and derive the optimal spatial power allocation between the source and relay for a given sum power constraint for the AF protocol. For most practical cases of interest, equal power allocation between the source and relay is shown to be nearly optimal. Our work suggests that there is minimal power savings from using spatial power allocation at the transmitters. To obtain large performance improvements over constant power transmission, it is imperative to have feedback for each realization of the channel state to allow for temporal power control. Index Terms--Block fading, diversity methods, limited feedback, power control, relay channel.

In this paper, we study minimal power transmission of bursty sources over wireless channels with constraints on mean queuing delay. The power minimizing schedulers adapt power and rate of transmission based on the queue and channel state. We show that packet scheduling based on queue state can be used to trade queuing delay with transmission power, even on additive white Gaussian noise (AWGN) channels. Our extensive simulations show that small increases in average delay can lead to substantial savings in transmission power, thereby providing another avenue for mobile devices to save on battery power. We propose a low-complexity scheduler that has near-optimal performance. We also construct a variable-rate quadrature amplitude modulation (QAM)-based transmission scheme to show the benefits of the proposed formulation in a practical communication system. Power optimal schedulers with absolute packet delay constraints are also studied and their performance is evaluated via simulations. Index Terms--Packet scheduling, power control, queuing delay, traffic regulation, wireless channels.

This is the second in a two-part series of papers on a new form of spatial diversity, where diversity gains are achieved through the cooperation of mobile users. Part I described the user cooperation concept and proposed a cooperation strategy for a conventional code-division multiple-access (CDMA) system. Part II investigates the cooperation concept further and considers practical issues related to its implementation. In particular, we investigate the optimal and suboptimal receiver design, and present performance analysis for the conventional CDMA implementation proposed in Part I. We also consider a high-rate CDMA implementation and a cooperation strategy when assumptions about the channel state information at the transmitters are relaxed. We illustrate that, under all scenarios studied, cooperation is beneficial in terms of increasing system throughput and cell coverage, as well as decreasing sensitivity to channel variations. Index Terms--Code-division multiple access (CDMA), diversity, fading, information rates, multiuser channels.

Mobile users' data rate and quality of service are limited by the fact that, within the duration of any given call, they experience severe variations in signal attenuation, thereby necessitating the use of some type of diversity. In this two-part paper, we propose a new form of spatial diversity, in which diversity gains are achieved via the cooperation of mobile users. Part I describes the user cooperation strategy, while Part II focuses on implementation issues and performance analysis. Results show that, even though the interuser channel is noisy, cooperation leads not only to an increase in capacity for both users but also to a more robust system, where users' achievable rates are less susceptible to channel variations. Index Terms--Code-division multiple access (CDMA), diversity, fading, information rates, multiuser channels.

In this paper, we study a multiple-antenna system where the transmitter is equipped with quantized information about instantaneous channel realizations. Assuming that the transmitter uses the quantized information for beamforming, we derive a universal lower bound on the outage probability for any finite set of beamformers. The universal lower bound provides a concise characterization of the gain with each additional bit of feedback information regarding the channel. Using the bound, it is shown that finite information systems approach the perfect information case as (t - 1)2-B/t-1. where B is the number of feedback bits and t is the number of transmit antennas. The geometrical bounding technique, used in the proof of the lower bound, also leads to a design criterion for good beamformers, whose outage performance approaches the lower bound. The design criterion minimizes the maximum inner product between any two beamforming vectors in the beamformer codebook, and is equivalent to the problem of designing unitary space-time codes under certain conditions. Finally, we show that good beamformers are good packings of two-dimensional subspaces in a 2t-dimensional real Grassmannian manifold with chordal distance as the metric. Index Terms--Beamforming, feedback, multiple antennas, outage probability, transmit diversity, unitary codes.

We consider the problem of digital communication in a Rayleigh flat-fading environment using a multiple-antenna system, when the channel state information is available neither at the transmitter nor at the receiver. It is known that at high signal-to-noise ratio (SNR), or when the coherence interval is much larger than the number of transmit antennas, a constellation of unitary matrices can achieve the capacity of the noncoherent system. However, at low SNR, high spectral efficiencies, or for small values of coherence interval, the unitary constellations lose their optimality and fail to provide an acceptable performance. In this work, inspired by the Stein's lemma, we propose to use the Kullback-Leibler (KL) distance between conditional distributions to design space-time constellations for noncoherent communication. In fast fading, i.e., when the coherence interval is equal to one symbol period and the unitary construction provides only one signal point, the new design criterion results in pulse amplitude moduclation (PAM)-type constellations with unequal spacing between constellation points. We also show that in this case, the new design criterion is equivalent to design criteria based on the exact pairwise error probability and the Chernoff information. When the coherence interval is larger than the number of transmit antennas, the resulting constellations overlap with the unitary constellations at high SNR, but at low SNR they have a multilevel structure and show significant performance improvement over unitary constellations of the same size. The performance improvement becomes especially more significant when an appropriately designed outer code or multiple receive antennas are used. This property, together with the facts that the proposed constellations eliminate the need for training sequences and are most suitable for low SNR, makes them a good candidate for uplink communication in wireless systems. Index Terms--Fading channels, multiple-antenna systems, noncoherent constellations, space-time modulation, wireless communications.

Progressive image transmission is difficult in the presence of a noisy channel, mainly due to the propagation of errors during the decoding of a progressive bitstream. Excellent results for this problem are made possible through combined source-channel coding, a method that matches the channel code to the source operational rate distortion as well as channel conditions. This paper focuses on the key component of combined source-channel coding: rate allocation. We develop a parametric methodology for rate allocation in progressive source-channel coding. The key to this technique is an empirical model of decoded bit-error rate as a function of the channel code rate. We investigate several scenarios. In the case of the memoryless channel, we present closed-form expressions. For the fading channel and channels with feedback, where closed-form results are elusive, our analysis leads to low-complexity algorithms. The results presented in this paper are applicable to any progressive source code, and any family of channel codes. Index Terms--Embedded coding, image compression, joint source-channel coding, progressive transmission, rate allocation.

Channel estimation techniques for code-division multiple access (CDMA) systems need to combat multiple access interference (MAI) effectively. Most existing estimation techniques are designed for CDMA systems with short repetitive spreading codes. However, current and next-generation wireless systems use long spreading codes whose periods are much larger than the symbol duration. In this paper, we derive the maximum-likelihood channel estimate for long-code CDMA systems over multipath channels using training sequences and approximate it using an iterative algorithm to reduce the computational complexity in each symbol duration. The iterative channel estimate is also shown to be asymptotically unbiased. The effectiveness of the iterative channel estimator is demonstrated in terms of squared error in estimation as well as the bit error rate performance of a multistage detector based on the channel estimates. The effect of error in decision feedback from the multistage detector (used in the absence of training sequences) is also shown to be negligible for reasonable feedback error rates using simulations. The proposed iterative channel estimation technique is also extended to track slowly varying multipath fading channels using decision feedback. Thus, an MAI-resistant multiuser channel estimation and tracking scheme with reasonable computational complexity is derived for long-code CDMA systems over multipath fading channels. Index Terms--Channel estimation, code-division multiple access, fading, long spreading codes, maximum-likelihood estimation, multipath, multiple access interference.

Multiple antenna transmission and reception have been shown to significantly increase the achievable data rates of wireless systems. However, most of the existing analysis assumes perfect or no channel information at the receiver and transmitter. The performance gap between these extreme channel assumptions is large and most practical systems lie in between. Therefore, it is important to analyze multiple antenna Systems in the presence of partial channel information. In this paper, we upper bound the outage probability performance of multiple antenna systems with preamble-based channel estimation and quantized feedback. We design causal feedback and power control schemes to minimize this upper bound on outage probability. We consider the following practical issues in our analysis and design: 1) the channel information is imperfect both at the receiver and at the transmitter and 2) part of the total available resources for the system need to be used for estimation and feedback. Our results demonstrate that for block fading channels, sending a periodic preamble and causally receiving channel state information via a feedback channel can lead to substantial gains in the outage performance over any non-feedback scheme. Most of the gains achieved by perfect feedback can be achieved by very few bits of feedback. Furthermore, it is demonstrated that these outage probability gains can be translated into improvements in frame error rate performance of systems using space-time codes. Thus, implementing a power control, even at the cost of reduced spectral resources for the forward channel is beneficial for block fading channels. Index Terms--Beamforming, channel estimation, feedback, multiple antenna systems, outage probability, power control, space-time codes.

There exists a gap in terms of the signals provided by pacemakers (i.e., intracardiac electrogram (EGM)) and the signals doctors use (i.e., 12-lead electrocardiogram (ECG)) to diagnose abnormal rhythms. Therefore, the former, even if remotely transmitted, are not sufficient for doctors to provide a precise diagnosis, let alone make a timely intervention. To close this gap and make a heuristic step towards real-time critical intervention in instant response to irregular and infrequent ventricular rhythms, we propose a new framework dubbed RT-RCG to automatically search for (1) efficient Deep Neural Network (DNN) structures and then (2) corresponding accelerators, to enable Real-Time and high-quality Reconstruction of ECG signals from EGM signals. Specifically, RT-RCG proposes a new DNN search space tailored for ECG reconstruction from EGM signals and incorporates a differentiable acceleration search (DAS) engine to efficiently navigate over the large and discrete accelerator design space to generate optimized accelerators. Extensive experiments and ablation studies under various settings consistently validate the effectiveness of our RT-RCG. To the best of our knowledge, RT-RCG is the first to leverage neural architecture search (NAS) to simultaneously tackle both reconstruction efficacy and efficiency. [ABSTRACT FROM AUTHOR]

Multi-User Multiple-Input and Multiple-Output (MU-MIMO) is a technique that allows concurrent transmissions between one access point (AP) and multiple clients to improve spectral efficiency. In practice, however, the MU-MIMO is sensitive to client mobility and is sometimes even harmful to the performance in networks with moving clients. In this paper, we identify that it is essential to optimize the MU-MIMO performance with moving clients by jointly selecting the sounding period, the number of spatial streams, and client grouping with the consideration of the client density of the network. We develop a data-driven model that estimates client throughput with the consideration of these parameters, as well as an algorithm that jointly determines the parameters for each client with low computational complexity. Using a commodity 802.11ax network, we experimentally demonstrate the significant impact of the key factors on MU-MIMO performance. Based on experimental data, we develop an emulation model to evaluate network performance with different client densities and mobility. Emulation results show that our proposed algorithm outperforms conventional schemes by over 20% in MU-MIMO networks with moving clients. [ABSTRACT FROM AUTHOR]

A technique is presented for jointly optimizing the signaling in the two directions of transmission on a twisted-pair communications channel. It is then applied to twisted-pair channel models with monotonic channel response and crosstalk transfer functions. While the signaling strategy presented in this paper can achieve only a lower bound on the true channel capacity, it is a significant improvement over existing signaling schemes. In particular, in contrast with existing schemes, the maximum information rate for the joint signaling strategy increases without bound as the signal-to-noise ratio (SNR) approaches infinity. It is also shown through numerical results that the proposed signaling strategy generalizes naturally to more practical nonmonotonic twisted-pair channel models incorporating bridge taps and other nonidealities. Finally, the form of the optimal signaling strategy suggests a relatively straightforward implementation using multicarrier modulation. Index Terms - Capacity, crosstalk, digital subscriber loops, multicarrier modulation, twisted-pair channel.

Several linear multiuser detectors for code-division multiple access (CDMA) systems can be characterized as an inverse of some form of correlation matrices. If the correlations change, the detectors must be redesigned. An ideal computation of the decorrelating or the linear minimum mean-squared-error (LMMSE) detector requires order [K.sup.3] flops, where K is the number of users. To alleviate the computational complexity, iterative decorrelating and LMMSE detectors are proposed. The iterative detectors use steepest descent (SD), conjugate gradient (CG), and preconditioned conjugate gradient (PCG) algorithms, and require order [K.sup.2] flops per iteration. Their main advantages are the reduced number of flops and their suitability to highly parallel implementations. The correlation coefficient computation can also be embedded into the CG algorithm, which is an advantage with time-varying signature waveforms. The performance of the iterative algorithms is studied via computer simulations. Index Terms - Code-division multiple access, iterative methods, linear multiuser detector.

In this paper, we consider a direct-sequence code-division multiple-access (DS-CDMA) system in the framework of a discrete-event dynamic system (DEDS) in order to optimize the system performance. Based on this formulation, we develop infinitesimal perturbation analysis (IPA) for estimating the sensitivity of the average probability of bit error to factors ranging from near-far effects to imperfections in power control. The above estimates are shown to be unbiased, and this technique is then further incorporated into a stochastic gradient algorithm for achieving adaptive multiuser interference rejection for such systems, which is also subject to frequency nonselective slow fading. We use an IPA-based stochastic training algorithm for developing an adaptive linear detector with the average probability of error being the minimization criterion. We also develop a practical implementation of such an adaptive detector where we use a joint estimation-detection algorithm for minimizing the average probability of bit error. A sequential implementation that does not require a stochastic training sequence or a preamble is also developed. Index Terms - Adaptive detection, direct-sequence CDMA, infinitesimal perturbation analysis, stochastic gradient algorithm.

Decorrelating, linear, minimum mean-squared error (LMMSE), and noise-whitening multiuser detectors for code-division multiple-access systems (CDMA) are ideally infinite memory-length (referred to as IIR) detectors. To obtain practical detectors, which have low implementation complexity and are suitable for CDMA systems with time-variant system parameters (e.g., the number of users, the delays of users, and the signature waveforms), linear finite-memory-length (referred to as FIR) multiuser detectors are studied in this paper. They are obtained by truncating the IIR detectors or by finding optimal FIR detectors. The signature waveforms are not restricted to be time-invariant (periodic over symbol interval). Thus, linear multiuser detection is generalized to systems with spreading sequences longer than the symbol interval. Conditions for the stability of the truncated detectors are discussed. Stable truncated detectors are shown to be near-far resistant if the received powers are upper bounded, and if the memory length is large enough (but finite). Numerical examples demonstrate that moderate memory lengths are sufficient to obtain the performance of the IIR detectors even with a severe near-far problem. Index Terms - Code-division multiaccess, linear multiuser detector, spread-spectrum communication.

We consider the estimation of channel parameters for code-division multiple access (CDMA) communication systems operating over channels with either single or multiple propagation paths. The multiuser channel estimation problem is decomposed into a series of single user problems through a subspace-based approach. By exploiting the eigenstructure of the received signal's sample correlation matrix, the observation space can be partitioned into a signal subspace and a noise subspace without prior knowledge of the unknown parameters. The channel estimate is formed by projecting a given user's spreading waveform into the estimated noise subspace and then either maximizing the likelihood or minimizing the Euclidean norm of this projection. Both of these approaches yield algorithms which are near-far resistant and do not require a preamble.

In this paper, we study the effects of joint transmit and receive antennas’ selection on full-duplex (FD) multiple-input-multiple-output (MIMO) networks’ performance. The antennas’ selection problem is, in general, a combinatorial problem whose complexity grows exponentially with the number of antennas. To fully understand the effects of antennas’ selection, we study the sum rate maximization problem in a single-cell network with an FD-MIMO base-station (BS). First, we consider a system with a normal-scale MIMO full-duplex BS, i.e., a normal-scale FD MIMO system. The sum rate maximization problem is studied for two different scenarios; in the first scenario, we consider jointly optimizing the transmit and receive antennas’ selection with the precoder and the receiver weights. A Generalized Bender's Decomposition based algorithm is proposed to solve the mixed-integer nonlinear sum rate maximization problem. In the second scenario, we consider self-interference cancellation via zero-forcing (ZF) transmission. A heuristic algorithm is proposed to solve the sum rate maximization problem by optimizing the selection of the transmit antennas, receive antennas, and the receive antennas at which self-interference is nulled. Second, in a very-large scale, i.e., massive MIMO system, we derive lower bounds for the uplink and downlink rates with ZF receiver and precoder, respectively. The sum rate is maximized by jointly optimizing the transmit to receive antennas ratio and the ratio of the receive antennas at which self-interference is nulled. Finally, via numerical analysis, we evaluate the performance of the formulated sum rate maximization problems. [ABSTRACT FROM AUTHOR]

A multiuser communication system is considered where K users share a channel with multipath propagation by using code division for multiple access. Data modulation is carried out by binary phase shift keying and direct sequence spread spectrum signaling. The microcellular communication media is modeled as a frequency selective fading channel with multipath propagation. The multipath diversity of the received signals from the K users is exploited by a bank of K Rake correlators. Algorithms based on the maximum likelihood rule have been developed for estimating the complex channel coefficients as well as for detection of the desired data packets from the sufficient statistics provided by the Rake correlators. The performance of the resulting multiuser detector is evaluated analytically and via Monte Carlo simulations. The results indicate that the estimator of the channel coefficients has a variance close to the Cramer-Rao lower bound, and that the proposed multiuser detector is capable of eliminating the near-far effect as well as processing the signals propagated through multiple paths. Keywords - Multiuser detection, code division multiple access (CDMA), Rake, Gauss-Seidel iteration, Expectation Maximization (EM).

Code division multiple access (CDMA) is a powerful multiplexing scheme, particularly suited to the optical domain with its broad spectrum. Unfortunately, analysis of optical CDMA (OCDMA) systems has been almost exclusively restricted to systems employing a correlation detector, which suffer high degradation when received user powers are dissimilar. This study examines the performance of an optimum single-user detector and two multiuser detectors for OCDMA in the presence of additive light intensity noise and Poisson detection. The optimized single-user detector is the maximum likelihood detector given the interference from other users is a random process with known distribution. One multiuser detector is based on a local search algorithm for maximizing the likelihood function. The second multiuser detector is a generalization of the optical multistage detector to accept soft-decision from the previous stage. Approximations to the error probabilities of the OCDMA system based on either random signature sequences or deterministic codes are derived for each detector using a large deviations theory approach. The asymptotic multiuser efficiency is found to be related to the large deviations rate function. The analysis shows that the correlation detector performance decreases rapidly as the number of users increases, while the optimized single-user detector and the two multiuser detectors proposed perform considerably better and show less sensitivity to unequal received user powers.

Analytical selections of the performance of optical communication systems are difficult to obtain and often, Monte Carlo simulations are used to achieve realistic estimates of the performance of such systems. However, for high performance systems, this technique requires t large number of simulation trials for the estimates to be in a reasonable interval of confidence, with the number of trials increasing linearly with the performance of the system. We apply an Importance Sampling technique to estimate the performance of direct detection optical systems, where the 'gain' of Importance Sampling over Monte Carlo simulations is shown to increase linearly with the system performance. Further, we use this technique to study the performance of optical communication systems employing avalanche photodetectors as well as fiber-optic code division multiple access systems (FO-CDMA). We also show that the quick simulation technique developed can be used for a wide variety of cooling schemes, and for the first time, we present a comparitive analysis of the performance of FO-CDMA systems employing optical orthogonal codes aid prime sequences. In all cases, it is shown that Importance Sampling simulations require less than 50-100 trials for estimating error probabilities of [10.sup.-10] and below. Keywords - Optical Code Division Multiple Access, Importance Sampling, Efficient Simulation Techniques, Exponential Tilt, Avalanche Photodetection, Fiber Optic Communications.

This paper addresses the issue of employing a parametric class of nonlinear models to describe nonlinear systems. This model class consists of a subclass of artificial neural networks, multilayer perceptrons. Specifically, we discuss the application of a 'globally' convergent optimization scheme to the training of the multilayer perceptron. The algorithm discussed is termed the conjugate gradients-trust regions algorithm (CGTR) and combines the merits of two well known 'global' algorithms - the conjugate gradients and the trust region algorithms. In this paper we investigate the potential of the multilayer perceptron, trained using the CGTR algorithm, towards function approximation in two diverse scenarios: i) signal classification in a multiuser communication system, and ii) approximating the inverse kinematics of a robotic manipulator. Until recently, the most widely used training algorithm has been the backpropagation algorithm, which is based on the linearly convergent steepest descent algorithm. It is seen that the multilayer perceptron trained with the CGTR algorithm is able to approximate the desired functions to a greater accuracy than when trained using backpropagation. Specifically, in the case of the multiuser communication problem, we obtain lower probabilities of error in demodulating a given user's signal; and in the robotics problem, we observe lower root mean square errors in approximating the inverse kinematics function. Index Terms - Multilayer Perceptrons, Data Driven Modeling, Optimization Algorithms, Function Approximation, Multiuser Detection

This paper considers a multiuser detection scheme for optical direct sequence code division multiple access (OCDMA) systems, referred to as the multistage detector. Previous works in this area have proposed two detectors: the correlation detector that is simple, but has poor performance for large number of users, and the optimal (minimum probability of error) detector that has exponential complexity in the number of users. Efficient multiuser detection algorithms consider the interfering user codes at the expense of electronic speed processing, unlike the optical processing achievable with the correlation detector. The multiple access system using the proposed multistage detector is shown to be of high performance and low complexity, compared to the conventional correlation detector and the optimal detector. The model studied includes multiple access interference as well as the Poisson characteristics of the optical direct detection process. An approximation to the probability of error is derived for the multistage detector, and it is compared to the actual error probability of the correlation detector, to a lower bound to the error probability of the optimal detector, and to simulation results for the multistage detector. The probability of error is calculated using a characteristic function method. Results are presented for a random code case that show a significant improvement in the performance of the OCDMA system using this detector over the correlation detector.

A method based on recursive computation of the expected number of attempts and successes during the collision resolution phase of an access control algorithm is introduced for the design of near-optimum control strategies for multiple access collision channels with ternary and binary feedback With this approach it is possible to circumvent the extremely difficult and still unsolved problem of finding the access control algorithm which achieves the highest throughput by settling for a near-optimum solution. The key to the design of our algorithms is to approximate the originally infinite dimensional optimization problem by a one dimensional optimization problem. In the ternary feedback case, our proposed algorithm achieves a throughput virtually identical to the highest throughput reported today. Several forms of binary feedback are considered and algorithms are introduced that achieve the highest throughput reported today.

Artificial neural networks are employed for demodulation of spread-spectrum signals in a multiple-access environment. This paper is motivated in large part by the fact that, in a multiuser system, the conventional (matched filter) receiver suffers sever performance degradation as the relative powers of the interfering signals become large (the "near-far" problem). Furthermore, in many cases the optimum receiver, which alleviates the near-far problem, is too complex to be of practical use. Two simple structures employing multilayer perceptrons are proposed for demodulation of spread-spectrum signals in both synchronous and asynchronous Gaussian channels. The optimum receiver is used to benchmark the performance of the proposed receiver; in particular, it is proven to be instrumental in identifying the decision regions for the neural networks. The neural networks are trained for the demodulation of signals via back-propagation type algorithms. In particular, a modified back-propagation algorithm is introduced for single-user and multiuser detection with near-optimum performance that could have applications in other classification and pattern recognition problems. A comparative performance analysis of the three receivers, optimum, conventional and the one employing neural networks, is carried out via Monte Carlo simulations. An importance sampling technique is employed to reduce the number of simulations necessary to evaluate the performance of these receivers in a multiuser environment. In all examples considered, the proposed neural net receiver significantly outperforms the conventional receiver.

The problem of simulating error rates in direct sequence spread-spectrum multiple-access systems is examined. Due to the computational complexity required to simulate these systems, an importance sampling technique is developed based upon previous work by the authors. A conditional weighting function is derived such that the linear shift class of biasing densities can be employed. Results are given for a variety of detector structures and background noise distributions. It is shown that this biasing scheme can dramatically reduce the run time of realistic multiple-access simulations.

Multi-user MIMO (MU-MIMO) is a technique that improves spectral efficiency by allowing concurrent communication between one access point (AP) and multiple clients. In practice, the expected gain is not always achieved and is sometimes even negative. We experimentally demonstrate that the downlink MU-MIMO performance in a practical network not only depends on the client’s channel but is also influenced by factors that are not captured by conventional models, such as client motion and device type. We propose a data-driven algorithm with a low computational complexity that determines whether a client should operate in MU mode and the MU-MIMO group for clients in MU mode. Such a mode and group selection algorithm is based on a sequence of channel state information (CSI), SNR, and client device type. The algorithm can automatically adapt to the motion and characteristics of individual clients. Experimental results using implementation on a commodity 802.11ac AP show that the proposed data-driven mode and group selection algorithm can improve network throughput by up to 35% over existing algorithms based on conventional models. We also show that the proposed data-driven algorithm has limited sensitivity to environmental changes and can be deployed into new environments without retraining. [ABSTRACT FROM AUTHOR]

Objective: This paper presents a data-driven method for estimating the memory order (the average length of the statistical dependence of a given sample on previous samples) of a recorded electrocorticography (ECoG) sequence. Methods: The proposed inference method is based on the relationship between the loss in predicting the next sample in a time-series and the dependence of this sample on the previous samples. Specifically, the memory order is estimated to be the number of past samples that minimize the least squares error (LSE) in predicting the next sample. To deal with the lack of an analytical model for ECoG recordings, the proposed method combines a collection of different predictors, thereby achieving LSE at least as low as the LSE achieved by each of the different predictors. Results: ECoG recordings from six patients with epilepsy were analyzed, and the empirical cumulative density functions (ECDFs) of the memory orders estimated from these recordings were generated, for rest as well as pre-ictal time intervals. For pre-ictal time intervals, the electrodes corresponding to the seizure-onset-zone were separately analyzed. The estimated ECDFs were different between patients and between different types of blocks. For all the analyzed patients, the estimated memory orders were on the order of tens of milliseconds (up to 100 ms). Significance: The proposed method facilitates the estimation of the causal associations between ECoG recordings, as these associations strongly depend on the recordings’ memory. An improved estimation of causal associations can improve the performance of algorithms that use ECoG recordings to localize the epileptogenic zone. Such algorithms can aid doctors in their pre-surgical planning for the surgery of patients with epilepsy. [ABSTRACT FROM AUTHOR]

This paper focuses on the design of a multiuser receiver structure for the reverse link of a code-division multiple-access communication system, in the presence of multipath effects and using an antenna array at the base station receiver. The algorithm presented in this paper solves the complex multidimensional problem of channel estimation in this complex scenario using a maximum-likelihood approach. This channel estimation technique requires the transmission of a training sequence or feedback of detected data. Once a composite channel-impulse response of each user is estimated, it is directly used in the detection process instead of first extracting the individual channel parameters, such as path delays and attenuation factors. The paper presents a framework that facilitates a computationally efficient solution to the combined problem of channel estimation and detection in a scenario involving multiple users, multiple paths, and multiple sensors at the receiver. Index Terms--CDMA, channel estimation, multipath, multiple sensors.