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This paper describes a method for achieving highway lane differentiation without requiring expensive global navigation receivers in every vehicle. Accurate lane identification can be used to optimize transportation network safety, by improving a vehicle's ability to avoid collision and to safely complete lane- change maneuvers. Using a cooperative technique, each vehicle communicates with road infrastructure and nearby connected vehicles to achieve sub-meter lane identification. We assume that a small subset of vehicles have high-accuracy GPS localization, which we refer to as probe vehicles. Other vehicles use location information from the probe vehicles and fixed infrastructure anchors to improve their position estimates.

This paper describes a high-accuracy localization algorithm that improves the safety of roadway workers. The proposed system consists of a wireless sensor network (WSN) of smart cones that includes a centralized master node and several sensor nodes. The master cone maps the topology of all sensor cones placed along the periphery of a work zone, with the goal of providing decimeter location accuracy. The low-mobility smart cone network can detect vehicles that intrude on a work zone, alert construction workers of impending danger, and notify high-mobility vehicles approaching the work zone. The master cone creates a work zone topology by estimating angles and distances relative to the sensor cones using radio interferometric measurements (RIM) and received signal strength indication (RSSI) measurements. Computer simulations characterize the performance that can be achieved for realistic environment conditions.

A sparse reconfigurable adaptive filter (SRAF) for a photonic switch consists of a large number of input and output delays, sparse reconfigurable connections, and adaptive weights. Recently, it was shown that a modified system-based (MSB) algorithm for the SRAF is more efficient than conventional algorithms such as previously introduced cross-correlation-based (CCB) and system-based (SB) approaches. In this paper, we propose a connection constraint for the MSB algorithm that chooses the most effective elements among the entire connection matrix. The proposed method allows any input to be connected to any output with an arbitrary weight, and is more efficient than the approaches mentioned above due to its reduced computational complexity. We provide a computer simulation example to demonstrate the performance of the connection-constraint algorithm for a system identification application.

Adaptive algorithms can be an important component of a sparse reconfigurable adaptive filter (SRAF) for photonic switches. In this paper, we propose a modified system-based (MSB) algorithm that not only has good performance for white and non-white input signals, but also has a reduced computational complexity compared with conventional approaches such as the previous cross-correlation-based (CCB) and system-based (SB) algorithms. In order to improve the convergence rate of the system, the MSB algorithm separately updates each row or column of the switch weight matrix. We also consider a specific structure for the intermediate desired signals, and present a computer simulation example to demonstrate the performance of the proposed SRAF algorithm for a system identification application.

The Global Positioning System (GPS) is one of the core technologies for the Location Based Service (LBS), and has various applications from the leisure business to the military. LBS requires accurate location information of an object, which GPS estimates using at least four satellites. In order to enhance the GPS signal quality, angle-of-arrival (AOA) information is required, but these are difficult to estimate because the system operates with a low signal-to-noise ratio (SNR) and in the presence of high-power interference. In this paper, we explore an extension of a recently proposed GPS AOA estimation technique based on a modified despreader for multiple GPS signals. Since the extended estimator does not require a singular value decomposition (SVD), unlike conventional AOA estimation algorithms such as Multiple Signal Classification (MUSIC), it has a relatively low computational complexity. Also, this technique does not need to choose the GPS AOAs from all estimated AOAs because those of the interference signals are not estimated. We demonstrate the performance of the GPS AOA estimation algorithm for multiple satellites via a computer simulation example.

A practical implementation of an optical filter must have a mechanism to compensate for variations in the component parameters-especially for an infinite-impulse-response (IIR) filter which can enter lasing mode if the poles are too close to the unit circle. Temperature changes are a frequent cause of unwanted drift in the parameters of the various optical components. In this paper, we consider an equation-error method for estimating and optimizing the parameters of a recently developed photonic integrated circuit (PIC). We characterize the effect of temperature-induced changes in the frequency response of the PIC, and describe adaptive compensation algorithms to adjust the filter parameters.

A direction-finding algorithm for a uniform linear array using a reversed beamformer and pilot signal training is presented in this paper. The direction-of-arrival (DOA) estimate for a signal of interest is derived using the phase difference between the output of a conventional beamformer and that obtained by reversing the antenna signals and conjugating the weights of a second beamformer. The proposed DOA estimation algorithm has a low computational complexity and improved performance in high cochannel interference environments compared to a recent subarray approach. Properties of the estimator are evaluated via a least-squares analysis, and the results are verified with a computer simulation example using wideband code-division multiple-access signals.

Phase-based direction-of-arrival (DOA) techniques estimate the phase difference between the output signal of a conventional beamformer and that of a related parallel beamformer. Since the two beamformers share the same weights in a specific known manner, the DOA estimators are affected by any phase mismatch of the beamformer weights relative to the direction vector of the signal of interest. This paper investigates the sensitivity of two phase-based DOA estimators to such beamformer mismatch via a theoretical analysis, and presents an example computer simulation to illustrate their properties.

In cellular wideband code-division multiple-access (WCDMA) systems, several transmitted data sequences can be separated because of the unique spreading codes which are designed to be orthogonal. However, cochannel interference and multipath propagation usually destroy this orthogonality at the receiver. We present a composite cyclodespreader that compensates for this distortion by exploiting the cyclostationary property of WCDMA signals, and uses a minimum mean-squareerror criterion to compute a composite despreading code. A semiblind beamformer that utilizes estimated physical channels as an extended training sequence is also employed in the receiver to improve the interference rejection capability in a high interference environment.

This paper describes filter designs for converting digital bandpass filters to a photonic integrated circuit (PIC). Because the filter designs must be physically realizable in an optical system, we consider a structure that not only meets the bandpass design requirements, but yields transfer function poles that avoid lasing. We consider a combination of infinite-impulse-response and finite-impulse-response stages in a multirate implementation using a cascade of optical unit cells. In order to convert the digital designs to parameter values needed in the unit cells, we describe a method for mapping the digital filter coefficients to the corresponding optical components of the PIC.

Previous work on sparse approximations has shown that in the pursuit of a signal model using greedy iterative algorithms, the efficiency of the representation can be increased by considering the interference between selected atoms. However, in such interference-adaptive algorithms, atoms are still often selected that necessitate correction by subsequently chosen atoms. It is thus logical to remove these atoms from the representation so that they do not diminish the efficiency of the pursued signal model. In this paper, we propose to prune atoms from the model based on the degree and type of interference, and test its effectiveness in an interference-adaptive orthogonal matching pursuit algorithm.

The Global Positioning System (GPS) is designed to estimate the locations of users or objects, and has a variety of civilian and military applications. Although angles-of-arrival (AOAs) may be required to enhance the desired GPS signals, it is difficult to estimate explicit AOA information because a GPS signal has a low power relative to the noise level. In this paper, we propose a GPS AOA estimation method based on a modified despreader and the constant modulus (CM) array cost function. This technique has a low computational complexity compared with other AOA estimation methods, such as the Multiple Signal Classification (MUSIC) algorithm, because it does not require a singular value decomposition (SVD). It also has good estimation performance in low signal-to-noise ratio (SNR) environments.

A semiblind beamformer using a parallel pilot signal in the adaptive algorithm is investigated for wideband code-division multiple-access (WCDMA) systems. Although the pilot signal and traffic channels are designed to be transmitted using orthogonal codes in the downlink direction, time dispersion and frequency-selective fading in the transmission channel severely degrade this orthogonality at the receiver. As a result, the traffic signal of a target base station appears as interference coming from the same direction as the pilot signal, and causes poor performance of a pilot-only training-based beamformer. In order to mitigate this effect, we propose a semiblind beamforming algorithm that jointly exploits the pilot signal and the traffic channel signals. A modified version of the semiblind beamformer simultaneously suppresses self-interference and cochannel interference from other base stations. The proposed semiblind techniques outperform the conventional pilot-only approach as demonstrated via computer simulations.

This paper presents a semiblind adaptive antenna for the downlink of wideband code-division multiple-access (WCDMA) systems. The weight vector of the antenna array is computed using the coded-multiplexed pilot channel as well as the estimated traffic channels in an extended training sequence. This approach suppresses the self-interference from physical channels in the same base station, leads to more accurate cochannel signal separation, and thus improves the performance compared to a conventional pilot-only trained beamformer. Moreover, a constant modulus constraint with a least-squares formulation is combined with the semiblind approach to refine the antenna weights. The performance of the proposed semiblind antenna system is evaluated via computer simulations.

Sparse approximation attempts to find an efficient signal representation by adaptively building a signal vector space from elements of a usually redundant and over-complete dictionary of atoms. Often, however, representations produced by iterative descent methods, such as orthogonal matching pursuit (OMP), will contain atoms that are poorly chosen and might later be confused as features of the signal. Poorly selected atoms bring about the selection other atoms that serve to correct for previous choices using destructive interference. This behavior diminishes the efficiency of a representation. In this paper, we propose and study a modification of the atom selection in OMP that takes into account the aforementioned effects. We find that a pursuit adapting to the interference between atoms can create a more efficient representation than that created by OMP, and one that is more representative of the signal and its features and less a reflection of the decomposition process.

This paper presents non-classical bandpass filter designs for a reconfigurable photonic integrated circuit (PIC). Because the designs must be realizable for a high frequency range in a new optical device, we consider digital infinite-impulse response filters that avoid lasing for a specific unit cell configuration. In order to accommodate the architecture of the PIC, we describe a design procedure for bandpass filters in the 10 GHz frequency range based on a prototype filter constructed from second-order sections.

Adaptive beamforming algorithms are presented for time-division multiple-access (TDMA) systems that use Gaussian minimum-shift keying (GMSK) for the transmitted signals. A semi-blind beamforming algorithm based on a least-squares (LS) approximation for constant modulus signals leads to a relatively simple and practical receiver that suppresses cochannel interference (CCI). In order to further improve the receiver performance, filtered training sequences are used to compensate for the phase offsets of the cochannel GMSK signals. Computer simulations demonstrate that this hybrid algorithm improves the receiver performance, whereby the beampattern nulls suppress the CCI affecting the coded data of the TDMA bursts.

We describe an adaptive beamforming algorithm for time- division multiple-access (TDMA) signals that utilizes a modified least-squares (LS) cost function, and analyze its performance using a stochastic model. The beamformer weights are computed via a two-step procedure: initial weights are calculated from the training sequence, and these are refined by a semi-blind algorithm using the modified LS cost function. The main goal of the paper is to analyze this algorithm using a stochastic model and Wiener filter theory for the case when the look-direction vector is mismatched. The performance of the proposed adaptive beamformer is also evaluated using simulated TDMA data.

We present a correlation-based algorithm for the agglomerative clustering of atoms in sparse atomic decompositions of audio signals. Our goal is to demonstrate useful relationships between elements of the decomposition and the content of the original signal, for such purposes as analysis and modification. We evaluate the performance of the agglomeration algorithm using decompositions of synthetic and real audio signals, and discuss possible extensions of this work.

Currently, there is no quantitative way to ascertain how an overcomplete signal representation describes a signal and its features using terms drawn from a dictionary. Though sparsity offers a measure of optimality with respect to the number of terms used, it does not describe how a signal is represented, or how well-suited a particular dictionary is for describing the signal. Building upon work that investigates the interactions between nonorthogonal terms of overcomplete signal representations, we define and examine interference in such representations built by an overcomplete method, such as matching pursuit. This interference comes from a lack of fit between a dictionary and the signal, as well as properties of the decomposition algorithm itself. Such behavior in a representation can be detrimental to its efficiency and the "meaningfulness" of its terms. In this paper, we consider interference as a possible way to gauge such properties of overcomplete signal representations.

A sparse atomic estimation involves finding a representation of a signal that uses terms with finite support drawn from an overcomplete dictionary. These terms can constructively and destructively interfere with each other in the reconstruction, and some may even disappear. For this reason, we refer to the interference between atoms in the sparse estimation as "dark energy" (DE). Building upon our previous work, we present a short-term measure of DE (STDE) that can be used to examine the distribution of interference in the signal estimation. We present results for several signals, and discuss some applications of this measure.

An adaptive beamforming algorithm for the global system for mobile communications (GSM) is presented where the weights are updated using re-encoded data and a semi-blind technique. The receiver consists of several stages operating on the synchronization channel (SCH) in an iterative manner to improve the reliability of the cochannel signal decisions. An extension of the constant modulus algorithm (CMA) with a least-squares (LS) formulation is used to implement the semi-blind technique. Iterative semi-blind processing is introduced to further refine the beamformer weights. The performance of the enhanced GSM receiver is evaluated using real and simulated data.

In a multiple-access communication system, many users utilize the same spectral bandwidth by transmitting, for example, during assigned time slots using time-division multiple access (TDMA). The users of a cellular system based on TDMA can encounter cochannel interference because carrier frequencies are reused in nearby cells. In this paper, we investigate adaptive beamforming and equalization algorithms for cochannel signal detection in the Global System for Mobile communications (GSM). In particular, we are interested in iterative weight refinement techniques where the beamformer weights are successively adapted using re-encoded TDMA data to improve signal estimation. The data of a GSM channel are processed in two stages that include the following series of steps: frame synchronization, adaptive beamforming, signal detection, adaptive equalization, and soft-input decoding. The algorithms are evaluated using the number of frames passing the parity check as the performance measure for real GSM data collected with an array of antennas

The sparse reconfigurable adaptive filter (SRAF) consists of an input delay bank, a photonic switch with reconfigurable connections and adaptive weights, and an output delay bank. This system architecture can be used to implement a sparse tapped delay line (TDL) with a large number of adaptive weights and a wide range of time delays. In this paper, we investigate some delay properties of the SRAF and consider an adaptive algorithm based on a cross-correlation function of the pre-whitened input and a desired response signal. Computer simulations are presented to illustrate the behavior of the SRAF for a system identification application

In an aperiodic code-division multiple-access (CDMA) system, the spreading sequences are designed to span multiple symbols. Since the spreading sequences are cyclostationary, this property can be exploited to derive channel equalization and interference rejection algorithms. Multiple antenna elements can be coupled with adaptive equalization to offer significant performance gains over that achieved by a similar system with only one antenna. In this paper, we investigate a multiple antenna cyclostationary receiver with a parallel architecture for an aperiodic CDMA signal that converts an aperiodic sequence into piecewise periodic sequences. The performance of the proposed receiver is evaluated for a real downlink aperiodic CDMA signal, and it is compared with that of a conventional matched filter (MF) receiver. The number of correctly decoded paging channel messages is used as the performance measure

The Global Positioning System (GPS) requires at least four satellites to achieve the best accuracy for location estimation. Since a conventional despreader can recover only one GPS signal, multiple despreaders are usually required for separating multiple GPS signals. In this paper, we explore an extension of a recently proposed GPS receiver that consists of a conventional despreader and a so-called null despreader, along with the multistage constant modulus (CM) array, to detect multiple GPS signals. This system does not require explicit direction-of-arrival (DOA) information about the GPS signals in order to reject directional interference. We present a computer simulation example to illustrate the jammer suppression performance of the proposed system for multiple GPS signals

Antenna selection techniques can be used to increase the capacity of a wireless communication system in multipath channel scenarios. For coherent reception, antenna selection can be achieved using, for example, maximum-ratio combining (MRC) or selection combining (SC). MRC is generally too com- plex for real system implementations, whereas SC is simpler and provides a lower bound on performance. Generalized SC (GSC) selects a subset of the antenna elements with a performance that is comparable to that of MRC but with lower complexity. In this paper, we describe an antenna selection technique based on GSC for an aperiodic direct-sequence code-division multiple- access (DS/CDMA) system where the user spreading sequences span multiple information symbols. The cyclostationary property of CDMA is exploited by a parallel receiver architecture that converts the aperiodic sequence into a set of piecewise periodic sequences. A multistage interference canceler is used in the receiver to decode the messages received from multiple base stations. The performance of the receiver is evaluated for real aperiodic CDMA signals, and the number of decodable messages is used as the performance measure. I. INTRODUCTION

The Global Positioning System (GPS) utilizes low- power spread-spectrum signals and thus is vulnerable to various types of high-power interference sources. In this paper, we propose a blind adaptive GPS receiver that is based on a new despreader and the one-stage constant modulus (CM) array. The despreader consists of a conventional GPS despreader and a so- called null despreader which together modify the received signal so that the CM array can extract the GPS signal of interest. The beamformer rejects jammers without explicit direction-of- arrival (DOA) information of any of the signals. A computer simulation example is presented to illustrate the performance of the proposed receiver for different types of jammer signals.

Adaptive antenna algorithms and a multistage receiver architecture are presented for the global system for mobile communications (GSM) where the beamformer weights are successively modified using re-encoded data. Adaptive filtering of the training sequence is utilized to refine the beamformer weights and to compensate for different sampling phase offsets of the cochannel signals. A multichannel matched filter with a sliding data window is also examined for burst detection. The receiver consists of cascaded stages such that the received antenna data are processed iteratively to improve the reliability of the final bit decisions. The performance of the multistage receiver is evaluated via computer simulations using simulated and real GSM data collected by an array of eight antennas.

An orthogonal frequency-division multiplexing (OFDM) system transmits an information-bearing signal on several orthogonal subcarriers. Although OFDM is relatively resistant to multipath effects, its performance is affected by cochannel interference. This interference may cover the entire OFDM signal transmission bandwidth, or it might occupy only part of the bandwidth and hence affect a subset of the subcarriers, in this paper, we examine the performance of a subcarrier adaptive beamformer that places nulls on individual subcarriers instead of on the entire OFDM symbol. Each subcarrier of every antenna element is weighted by an adaptive coefficient that is updated by a blind algorithm. Since the beamformer on each subcarrier is adapted independently, it is possible that some beamformers captures an interferer instead of the signal of interest. To avoid this problem, we propose a two-stage system that has a subcarrier adaptive beamformer and a bank of signal cancelers in the first stage, followed by a constrained beamformer in the second stage. We present computer simulations to investigate the behavior of the subcarrier adaptive beamformer as the degree of subcarrier overlap and the angle of arrival (AOA) of the cochannel interference are varied.

The Global Positioning System (GPS) utilizes low-power spread-spectrum signals which are vulnerable to many kinds of high-power interference signals and jammers. We propose a low-complexity blind adaptive receiver that is based on a novel modified despreader and the one-stage constant modulus (CM) array. This system is capable of nulling directional interference and capturing the GPS signal of interest without requiring explicit angle-of-arrival (AOA) information. Computer simulations are provided to illustrate the performance of the multicomponent receiver for a combination of different types of jamming signals.

In a long-code/aperiodic direct-sequence code-division multiple-access (DS/CDMA) system, the user spreading sequences span multiple information symbols. Most interference suppression techniques have been proposed for short-code/periodic CDMA systems where the spreading sequence is confined to a single symbol interval and generally cannot be applied directly to a long-code system. In this paper, we investigate a cyclostationary receiver with a parallel architecture that converts an aperiodic CDMA signal into a set of periodic signals, one in each arm of the parallel receiver. Blind interference suppression based on Tikhonov regularization is performed by the cyclostationary receiver for real Interim Standard 95 (IS-95) signals captured inside a building and its performance is compared to that of a conventional matched filter (MF) receiver. The performance of the receiver is improved using blind recursive algorithms and a decision-directed approach.

A nonblocking photonic switch can be used to implement a tapped delay line with a large number of coefficients and a wide range of time delays. In this paper, we present a sparse reconfigurable adaptive filter (SRAF) based on a photonic switch with an input/output connection architecture that can be represented by a matrix of adaptive weights. This unique parallel structure can be reconfigured in an adaptive manner to implement a sparse filter impulse response for a variety of applications. The appropriate choice of time delays is determined from a cross-correlation function between the filter input and a desired response signal that depends on the particular application. A computer simulation example illustrates the performance of the algorithm for modeling a bandpass filter characteristic.

The design of higher-layer protocols is an active area of research for ad hoc networks that operate on multiple channels. In orthogonal frequency-division multiplexing (OFDM), symbols are transmitted on orthogonal subcarriers which can be viewed as separate transmission channels. In an orthogonal frequency-division multiple-access (OFDMA) ad hoc network, adjacent nodes operate on different sets of subcarriers. As the number of users increases in such a network, the throughput drops due to the availability of fewer subcarriers for each user and because of the increased cochannel interference between users. Multiple antenna receivers have been proposed for ad hoc networks to reduce power consumption and enhance the range of each node in the network. In this paper, we extend a frequency-domain subcarrier adaptive beamformer to an OFDMA ad hoc network that beamforms in the direction of a desired node and nulls interferers from cochannel nodes. A blind time-domain subcarrier adaptive beamformer and signal canceler are proposed that satisfy a constant-modulus criterion. Since each group of nodes in an ad hoc network communicates on a unique set of subcarriers, the optimal beamformer should ideally place nulls in the directions of the interferers only on those subcarriers and independently of other subcarriers.

The Global Positioning System (GPS) was designed to provide location estimates for various civilian and military applications using at least four satellites. Since GPS signals have a low signal-to-noise ratio, they also have a low signal-to-jammer ratio, and thus the accuracy of these estimates is influenced by cochannel interference and intentional jammers. In this paper, we explore an extension of a recently proposed blind multicomponent jammer rejection system, which is based on a modified despreader, to extract multiple GPS signals. This extended system also operates blindly to null directional interference and capture all GPS signals of interest without requiring explicit knowledge of their angles-of-arrival. A representative computer simulation example is presented Io illustrate the performance of the multicomponent system for the suppression of different jammer types.

Orthogonal frequency-division multiplexing (OFDM) has been utilized in various communication systems because of its ability to compensate for multipath channels using simple low-complexity equalizers. However, the performance of OFDM systems can still be compromised due to adjacent channel and cochannel interference. In this paper, we investigate the performance of an adaptive beamforming algorithm for an OFDM system based on the constant modulus (CM) array. We consider this blind technique for a wireless local area network such as the IEEE 802.11a standard. The algorithm exploits the constant modulus property of the low-rate OFDM data carriers, and we show that it can also be used for the nonconstant modulus constellations at higher data rates. We consider the case where cochannel users become active part way into the transmitted packet such that new beamformer weights should be computed to null these interfering signals.

The Global Positioning System (GPS) is a satellite-based navigation network employing spread-spectrum techniques that is widely used for commercial and military applications. Although the large spreading gain of GPS allows for operation in very low signal-to-noise ratio environments, the received signals are vulnerable to various types of narrowband and wideband interference. In this paper, we propose a blind multi-component adaptive receiver based on the constant modulus (CM) array that cancels the high-power interference and recovers the GPS signal of interest without using a priori direction-of-arrival information or training data. The performance of the system at the output of each component is illustrated via computer simulations for an example signal scenario. Expressions for the output signal-to-interference-plus-noise ratio are also provided in order to investigate the steady-state properties of the system.

In this paper, we describe amplitude estimation algorithms for the Walsh traffic channels in the downlink of Interim Standard 95 (IS-95). The parameter estimate is designed to improve the performance of a successive interference canceller (SIC) by providing greater reconstruction accuracy. A feature of the IS-95 downlink that makes amplitude estimation difficult is that during lowered voice activity levels, bit repetition occurs with a corresponding drop in the symbol energy for a frame of data. As a result, the amplitude level cannot be assumed to remain constant and should be taken into account during signal reconstruction in the SIC. We explore various algorithms for estimating the nominal Walsh traffic channel amplitude level. The distinguishing characteristic of the different techniques is the type of a priori knowledge employed in the estimation. For example, one parameter that may need to be estimated is the bit repetition multiple using a rate determination algorithm.

The Global Positioning System (GPS) is a one-way satellite communication system that is widely used for both civilian and military applications. Because of the relatively low power of the received signals, GPS is highly susceptible to a variety of intentional and unintentional interferers. In this paper we examine a multistage space-time adaptive-processor (STAP) that is used to improve the detection capability of a GPS receiver for a wide range of jamming scenarios. Depending on the type of interference, the stages incorporate structures such as a notch filter, a beamformer and a blind linear interference canceler. Computer simulations are provided to illustrate the performance of the multistage receiver for wideband and narrowband interferers.

Several techniques have been introduced to enhance the signal-to-interference-plus-noise ratio (SINR) of the nonlinear successive interference canceler (SIC). Some of these improvements are specific to the downlink (base station to mobile) of Interim Standard 95 (IS-95) for code-division multiple-access (CDMA) cellular systems. We extend this previous work by investigating how inclusion of these enhancements affects the probability of error for a weaker base station being demodulated. In addition to evaluating how SINR enhancement removes additional interference from stronger base station signals, we also discuss a joint detector designed to mitigate the interference of weaker base station signals. By using this joint approach, near-far effects can be reduced further for certain channels in the primary base station. Computer simulations are presented to verify the SINR model and demonstrate the performance gains.

We examine the performance of methods that increase the accuracy of demodulating and reconstructing a strong base station signal such that it can be canceled prior to demodulating weaker base station signals. This successive interference cancellation (SIC) process is used to increase the signal-to-interference-plus-noise ratio (SINR) of a weaker base station being demodulated above the threshold needed to achieve a desired bit error rate. However the parameters of the stronger base station must be estimated with enough accuracy for successful signal reconstruction, otherwise, the SINR may not be sufficiently enhanced. We provide an analysis that determines how much interference can be removed from the received signal, in the form of the stronger base station, given a specific SINR. The methods we address to increase the effective SINR include features unique to the downlink of Interim Standard 95 (IS-95), such as bit repetition and properties of the power control bits.

We investigate the steady-state properties of the adaptive successive interference canceler (ASIC) for direct-sequence code division multiple access (DS/CDMA) signals. The ASIC is a multistage structure that sequentially detects and removes cochannel users from the received signal impinging on a single antenna element. In order to reliably remove a user, the corresponding multiple access interference (MAI) must be regenerated and subtracted from the received signal. This requires an accurate estimate of the user's signal amplitude, which is provided by an adaptive weight that is updated at the chip rate.

The authors present a novel blind equalization algorithm for coded waveforms received in the presence of intersymbol interference (ISI). The algorithm is an approximation to the optimum maximum a posteriori (MAP), symbol-by-symbol detector for a priori unknown channels, and consists of a bank of Kalman filter channel estimators, each conditioned on a subsequence of code symbols. For convolutional codes, a separate channel estimate is computed for every effective state in the convolution of the encoder and channel. It is shown that the MAP decoding metrics can be computed using the Kalman filter innovations, which are combined in a suboptimum Bayesian formula. The performance of the algorithm is evaluated using simulations and comparisons of channel estimation error. >

An adaptive equalizer based on a multilayer perceptron and the backpropagation training algorithm is presented for M-ary PAM (pulse amplitude modulation) digital communication systems. The configuration is an extension of the conventional adaptive FIR (finite impulse response) equalizer whereby the linear filter is replaced by a nonlinear feedforward network with nodes that saturate at +or-1. The training signal is derived by encoding the PAM signals via a bit-mapping strategy such that the output layer of the perceptron requires log/sub 2/ (M) nodes. A corresponding number of error signals is generated, and these are used to drive the backpropagation algorithm. Computer simulations are presented to illustrate the performance of the equalizer for two different bit mappings. >

The optimal blind maximum a posteriori symbol detection (MAPSD) algorithm for spatial diversity combining is derived. This diversity MAPSD (DMAPSD) algorithm is applied to a time division multiple access (TDMA) system for the recovery of mobile radio signals. Lower complexity DMAPSD algorithms are described, and their error rate performance for fast fading channels is studied via computer simulations. The results indicate that the proposed MAP detectors provide SNR gains of 6-13 dB over a zero-forcing decision-feedback equalizer (DFE). >

The authors present an improved version of a previous 8-kb/s low-delay VXC (vector excitation coding) algorithm, which has been enhanced to maintain high-quality results under clean conditions while adding robustness to channel errors. Periodic resetting of the pitch predictor makes the coder more robust to channel errors but sacrifices some of the advantages of interframe coding in clean channels. A novel adaptive mean-removed pitch tracking scheme was introduced that provides robustness to bit errors while avoiding significant quality degradation under error-free conditions. >

In this paper, we present a stochastic analysis of the constant modulus (CM) array for time-varying channels. An expression for the mean-square error is derived, which is based on a recursion for the weight-error correlation matrix. The analysis yields an accurate model of the tracking behavior of the CM array provided the array maintains capture on the same source. Computer simulations are presented to illustrate the tracking behavior of the CM array and to verify the theoretical model.

The multistage CMA adaptive beamformer is a blind adaptive antenna system capable of recovering several narrowband cochannel signals. Each stage of the system captures one source (without using a training signal), removes it before processing by subsequent stages, and provides an estimate of its direction of arrival. This system would be useful in frequency reuse applications, such as cellular radio or personal communication networks, where cochannel interference is an important consideration. We present the steady-state convergence properties of the first stage of the multistage CMA adaptive beamformer. Computer simulations are presented to verify the analytical results. >

This paper describes a blind adaptive algorithm for the recovery of cochannel data signals in the presence of intersymbol interference. Assuming unknown finite impulse response channel characteristics, the principle of maximum a posteriori symbol detection (MAPSD) is employed to jointly estimate the channels and the transmitted data. In order to reduce the complexity of this joint blind MAPSD algorithm, a cascaded multistage structure is proposed whereby each stage recovers one of the cochannel sources. This suboptimal approach is expected to perform well when the cochannel signals have sufficiently different power levels. Computer simulations for a primary signal and a single interferer illustrate the rapid convergence properties of the algorithm. >