This paper proposes a symbol-level synchronization technique for ultra-wideband (UWB) communications in networks without power control. The near-far problem dramatically degrades the performance of synchronization for UWB communications. The technique is based on an easy-to-implement procedure to suppress the interfering waveforms from high-power users without requiring knowledge of their spreading codes. The technique includes two operations, a "suppression" operation, and a subsequent dimension detection operation that determines the desired user's code phase during acquisition in the receiver. Simulation results are provided that show the improved performance of the near-far resistant synchronization procedure proposed in this paper for up to two high-power and four equal-power interfering users when compared to the best alternative from the literature.

In this paper, we investigate the multiple-access (MA) performance of transmitted reference (TR) ultra-wideband (UWB) systems employing M-ary PPM in multipath environments. Because we assume there is no power control in the network, interfering power levels from users can vary over many 10's of dB. We categorize the interfering users into two groups with respect to power levels. A new method for deriving the variance of the Gaussian random variable resulting from multiple-access interference (MAI) is developed using the power delay profile (PDP) of the channel. This makes the theoretical analysis tractable and enables us to predict the system-level performance such as the supported number of users, the achievable data rate, and the required bit-energy-to-noise ratio. Chip discrimination is applied and shown to mitigate the effect of high-power users. Performance is quantified due to the combined effects of equal-power and high-power users.

To increase the data rate for transmitted reference (TR) ultra-wideband (UWB) systems, M-ary pulse position modulation (PPM) is used in this paper. The multiple-access performance of such systems is investigated in a multipath environment. A new method to derive the variance of the Gaussian random variable resulted from multiple-access interference (MAI) is developed using the power delay profile (PDP) of the channel. By applying an upper bound, a general relationship is reached for system parameters such as the number of supported users, the bit error probability, the required Eb/No, and the data rate. Tradeoffs between system parameters are discussed as well in this paper.

To increase the transmission data rate, we propose to use M-ary pulse position modulation (PPM) for transmitted reference (TR) ultra-wideband (UWB) systems. The performance of TR UWB systems employing M-ary PPM is investigated in multipath, multiuser environments without centralized power control. The interference from high-power users is shown to significantly degrade the performance of TR UWB systems using M-ary PPM. Chip discrimination is used to mitigate the detrimental effect of high-power users. Theoretical analysis on the performance of M-ary PPM applied to TR UWB systems is derived. A tight upper bound for the symbol error probability is obtained. Analysis and numerical results show that TR UWB systems with M-ary PPM using chip discrimination is robust against high-power interfering users in wireless networks where centralized power control is infeasible, such as ad-hoc networks.

A simple chip-discrimination technique is presented for use with ultra-wideband (UWB) impulse radio (IR) that improves performance for large near-far interference power ratios. A typical spread-spectrum IR that employs a matched-filter sum for bit decisions is susceptible to small numbers of large power pulses that can dominate the bit decision-threshold statistics. This letter describes a technique for chip discrimination prior to the spreading summation, that can greatly reduce the effects of large near-far power ratios among interferers. The technique exploits the very narrow pulsewidth and resulting low-duty-cycle characteristic only achievable with ultra-wide bandwidth. A statistical model is developed that predicts bit-error performance for binary offset pulse position modulation as a function of near-far density and power for varying discrimination thresholds. An analytic solution for perfect chip blanking is developed, and is in good agreement with chip discrimination for large near-far power ratios. We find that even a small number of very near interferers can greatly reduce the performance of a system without blanking or discrimination. Results show substantial improvement using this method for near interferers with near-far power ratios greater than 20 dB.

Simulation is an important tool in evaluating the performance of computer networks. We present a technique for computationally efficient simulation of delay in networks with a number of nodes, background traffic, and a TCP protocol. The technique uses splitting based on direct probability redistribution (DPR). DPR has been shown to be a powerful technique for efficient simulation of a number of different network topologies. However, efficient simulation of delay in networks, especially those utilizing a transport layer protocol with feedback, such as TCP, has been elusive. The technique presented here solves this problem by modifying the subset indicator function associated with DPR. We demonstrate the technique by applying it to a network with four nodes, background traffic, and a TCP protocol.

Impulse radio (IR) is a promising ultra-wideband technique for tactical military communications. A key feature of time-hopping IR are the very narrow pulses used to convey information. Analysis of such time-hopping schemes under a variety of assumptions have been reported in the literature. However, none of these studies to date consider the effects of timing jitter and tracking on time-hopping in a ultra-wideband (UWB) setting. We consider the effects of timing jitter and tracking on the performance of binary and 4-ary UWB communications. We find that the performance of IR is very sensitive to timing jitter and tracking, at least in part due to the very narrow pulses. We also find that in the presence of timing jitter and tracking, orthogonal 4-ary pulse position modulation (PPM) out performs binary offset PPM at all jitter levels in thermal and pulse noise. Simulation results are presented that quantify the sensitivity of binary and 4-ary IR to timing jitter and tracking error.

To support the myriad of envisioned communication products of the future, there is a need to develop a network infrastructure that can provide larger bandwidth, with better control of quality of service (QoS). This activity requires performance analysis techniques that can accurately model packet-switched network protocols such as those based on TCP/IP. Due to the intractability of realistic network models, simulation is required. In this paper we present two techniques that can be used to speed up simulation of these networks, thus allowing simulation of more complex network models in the same amount of execution time as would otherwise be required. These techniques are modifications of a trajectory splitting simulation technique based on direct probability redistribution (DPR). Although DPR was originally developed to speed up simulation of networks characterized by rare events, here we consider performance indices that are based on non-rare events, such as networks that utilize TCP/IP. We develop the techniques and demonstrate their utility by applying them to: (1) a simple network model, and (2) a network model that includes a tandem connection of routers, tagged and background traffic, and a detailed TCP protocol. This network model includes a feedback path that is subject to the same network traffic as the forward path, thus incurring delay and loss. The techniques provide an order of magnitude speed-up factor when compared to standard simulation, thus allowing more design iterations or simulation of larger networks in the same amount of execution time.

The complexity of modern networks and the stringent quality of service requirements that result in very small important event probabilities can render standard Monte Carlo (MC) simulation intractable. Accelerated simulation using splitting can potentially overcome these difficulties, but conventional methods cannot be successfully applied to systems for which the occurrence of the important event does not temporally coincide with the conditions that lead to it. Cell delay experienced through single and tandem switches exhibits this behavior. We develop two enhanced splitting methods based on a splitting technique which was previously used to estimate rate delay probabilities through a single switch. The enhanced methods accurately capture the queueing behavior that leads to excessive cell delay through tandem switches. We use the enhanced methods to efficiently estimate rate delay probabilities for tagged traffic traversing tandem switches in the presence of background traffic. The enhanced methods penetrate into a significantly higher delay (lower probability) region compared to the previous method. Speedup over standard MC simulation is observed to be inversely proportional to the probability being estimated.

Importance sampling has been used as an efficient method for estimating rare probabilities (on the order of 10/sup -6/ or less) relating to the performance of communication systems and networks. Parametric importance sampling methods are not very effective in cases where the input processes are characterized by uniform probability distributions (e.g., random delays), which arise frequently. We present a conditional importance sampling scheme for systems with input processes that can be characterized by uniform distributions. The scheme adaptively modifies an initial biasing strategy as samples are taken. Changing a problem specific component enables the algorithm to be applied to a diverse set of systems. The overall approach is more effective than parametrically biasing the uniform input distributions. We use the conditional biasing algorithm to estimate rare jitter probabilities in ATM switches for CBR sources multiplexed with heterogeneous background traffic. For the experimental systems considered, we observe that the improvement in simulation efficiency is inversely proportional to the probability being estimated.

Estimating rare event probabilities in communication systems using Monte Carlo simulation can require a prohibitively large number of trials for acceptable accuracy. We develop and present a technique in this paper that provides large speedup factors over conventional Monte Carlo simulation based on the theory of "direct probability redistribution" (DPR). We show that DPR can be viewed as a type of importance sampling (IS), albeit "nontraditional", which requires little additional effort to apply. The theory of DPR is presented for systems that can be described as a discrete time Markov chain (DTMC). We show that the RESTART technique is an important special case of direct probability redistribution. An efficient simulation technique based on DPR is less restrictive than RESTART, and is much less problem specific than traditional IS techniques. We demonstrate how to use DPR to speedup Monte Carlo simulation of non-trivial systems by applying the technique to two examples: A 64/spl times/64 three-stage ATM switch, and an ATM multiplexer with internal flow control. For these systems we estimate small cell loss probabilities and show that the improvement is nearly inversely proportional to the probability estimate.

For ATM networks with heterogeneous input traffic, namely constant bit rate (CBR) and variable bit rate (VBR) traffic, we consider the aggregate probability that the cell transfer delay exceeds a given threshold (delay threshold probability). We use the connection traffic descriptors standardized by the ATM Forum to characterize the input traffic. In this paper, we extend our importance sampling simulation model, which was previously used for homogeneous traffic, to heterogeneous traffic. Again, we observe that the improvement in simulation efficiency is inversely proportional to the probability being estimated.

We present an IS stochastic technique for the efficient simulation of adaptive systems which employ diversity in the presence of frequency nonselective slow Rayleigh fading and additive, white, Gaussian noise. The computational efficiency is achieved using techniques based on importance sampling (IS). We utilize a stochastic gradient descent (SGD) algorithm to determine the near-optimal IS parameters that characterize the dominant fading process. After accounting for the overhead of the optimization algorithm, average speed-up factors of up to six orders of magnitude [over conventional Monte Carlo (MC)] were attained for error probabilities as low as 10/sup -11/ for a fourth-order diversity model.

Importance sampling (IS) techniques offer the potential for large speed-up factors for bit error rate (BER) estimation using Monte Carlo (MC) simulation. To obtain these speed-up factors, the IS parameters specifying the simulation probability density function (PDF) must be carefully chosen. With the increased complexity in communication systems, analytical optimization of the IS parameters can be virtually impossible. We present a new IS optimization algorithm based on stochastic gradient techniques. The formulation of the stochastic gradient descent (SGD) algorithm is more general and system-independent than other existing IS methodologies, and its applicability is not restricted to a specific PDF or biasing scheme. The effectiveness of the SGD algorithm is demonstrated by two examples of communication systems where the IS techniques have not been applied before. The first example is a communication system with diversity combining, slow nonselective Rayleigh fading channel, and noncoherent envelope detection. The second example is a binary baseband communication system with a static linear channel and a recursive least square (RLS) linear equalizer in the presence of additive white Gaussian noise (AWGN).

Two importance sampling (IS) methodologies for Monte Carlo simulation of communication links characterized by time-varying channels and adaptive equalizers are presented. One methodology is denoted as the twin system (TS) method. A key feature of the TS method is that biased noise samples are input to the adaptive equalizer, but the equalizer is only allowed to adapt to these samples for a time interval equal to the memory of the system. In addition to the TS technique, the IA method, a statistically biased, but simpler, technique for using IS with adaptive equalizers that is based on the independence assumption between equalizer input and equalizer taps is presented. Experimental results show run-time speedup factors of two to seven orders of magnitude for a static linear channel with memory, and of two to almost five orders of magnitude for a slowly-varying random linear channel with memory for both the IA and TS methods.>

Importance sampling is recognized as a potentially powerful method for reducing simulation runtimes when estimating the bit error rate (BER) of communications systems using Monte Carlo simulation. Analytically, minimizing the variance of the importance sampling (IS) estimator with respect to the biasing parameters has typically yielded solutions for systems for which the BER could be found analytically. A technique for finding an asymptotically optimal set of biasing parameter values, in the sense that as the resolution of the search and the number of runs used both approach infinity, the algorithm converges to the true optimum, is proposed. The algorithm determines the amount of biasing that minimizes a statistical measure of the variance of the BER estimate and exploits a theoretically justifiable relationship, for small sample sizes, between the BER estimate and the amount of biasing. The translation biasing scheme is considered, although the algorithm is applicable to other parametric IS techniques. Only mild assumptions are required of the noise distribution and system. Experimentally, improvement factors ranging from two to eight orders of magnitude are obtained for a number of distributions for both linear and nonlinear systems with memory.>

Importance sampling (IS) is a powerful method for reducing simulation run times when estimating the probabilities of rare events in communication systems using Monte Carlo simulation and is made feasible and effective for the simulation of networks of queues by regenerative techniques. However, using the most favorable IS settings very often makes the length of regeneration cycles infinite or impractically long. To address this problem, a methodology that uses IS dynamically within each regeneration cycle to drive the system back to the regeneration state after an accurate estimate has been obtained is discussed. A statistically based technique for optimizing IS parameter values for simulations of queueing systems, including complex systems with bursty arrival processes, is formulated. A deterministic variant of stochastic simulated annealing (SA), called mean field annealing (MFA), is used to minimize statistical estimates of the IS estimator variance. The technique is demonstrated by evaluating blocking probabilities.>

A technique is presented for finding transmitter and receiver filters for a wide class of data transmission systems which minimize the bit error rate (BER). The techniques uses Monte Carlo simulation to estimate the BER, coupled with mean field annealing (MFA) to optimize the pulse shapes. Modeling of the link can be as complex as simulation will allow, while MFA is resistant to the statistical scatter in the BER estimate from the simulation. In a complex example, MFA is coupled with Monte Carlo simulation techniques to find near optimal transmit and receive filters for a satellite communications link, taking 6 CPU hours on a DECstation 3100. The bit error rate of the link is found to be as much as three orders of magnitude lower when using the MFA-constructed optimal filters than when using filters constructed by gradient descent and simulated annealing.>

Three results on Sigma Delta modulation are presented. First, a change of variables is presented that demonstrates that two of the parameters in a Sigma Delta modulator do not affect the system performance. Second, a successive parameterization approach is used to determine the probability density function (PDF) at the input to the quantizer of a second-order Sigma Delta modulator. Third, this calculated PDF is used to determine the minimum mean-square error linearizing gains for a second-order Sigma Delta modulator and an expression for the variance of the noise at the input to the quantizer.>

A technique for finding transmitter and receiver filters for a wide class of digital communication systems which minimize the bit-error rate (BER) is presented. The technique uses Monte Carlo simulation to estimate the BER and mean field annealing (MFA) to optimize the pulse shapes. Modeling of the link can be as complex as simulation will allow, while MFA is resistant to the statistical variation in the BER estimate from the simulation. Initially, the MFA technique was applied to a binary symmetric channel in a nonsimulation environment, and an approximate analysis of the behavior of MFA for this problem was performed. In a more complex example, MFA was coupled with Monte Carlo simulation techniques to find near-optimal transmit and receive filters for a satellite communications link, taking 6 CPU hours on a DECstation 3100. The BER of the link was found to be as much as three orders of magnitude lower when using the MFA-constructed optimal filters than when using filters from other comparison results. For this example, the pulse shapes obtained using MFA exhibit a low BER even as the parameter controlling the nonlinearity of the satellite-link model is varied over a wide range, thus showing the solution is robust.>

Monte Carlo simulation can be used to estimate the bit error rate (BER) in digital lightwave communication links. However, when the link includes an avalanche photodetector (APD) receiver and is operating at a low BER, Monte Carlo simulation requires excessive execution time unless assumptions are made about the APD statistics. Techniques are presented that reduce the computational resources required to estimate the BER for these systems by two orders of magnitude. The speed-up is achieved by developing anew, more efficient random number generation algorithm for APD shot noise and by applying a tail extrapolation technique to the conditional distributions at the sample-and-decide input in the receiver. Receiver thermal noise is handled analytically. Accurate BER estimates for an NRZ direct-detection system are obtained in approximately 1.5 CPU hours on a VAXstation II using a combination of these techniques.>

A hybrid approach is presented for evaluating the performance of single-mode digital lightwave communication links efficiently. The hybrid approach combines simulation with analysis to provide greater accuracy and flexibility than that available with analytical calculations alone. Because simulation is used, models can be made as detailed as necessary and computed waveforms can be compared directly to measured waveforms. Measured data can be used to characterize functional components, such as sources, fibers, and detectors, accurately. Simulation models and techniques for evaluating system degradations caused by the optical-source waveforms, fiber attenuation and dispersion, and receiver noise are provided. The end-to-end performance of typical digital lightwave links with broad- and narrow-spectrum sources (light-emitting diodes and laser), using both p-i-n and avalanche photodiode detectors, is evaluated and compared to experimental results.>