Blind adaptive multiuser detection for DS/SSMA communications withgeneralized random spreading

A new spreading scheme and an accompanying blind adaptive receiver structure are proposed for direct-sequence spread-spectrum multiple-access communications in a slowly-varying, frequency-selective fading channel. Each user's spreading sequence is given by the Kronecker product of a long-period pseudonoise (PN) sequence, which is accurately modeled by a random sequence, and a short-length deterministic signature code. This spreading scheme bridges the gap between pure PN spreading and pure short-code spreading schemes. It is shown that with this spreading scheme, the channel response to the desired signal component is easily estimated without relying on the spectral decomposition of the signal correlation matrix. With the estimate of the channel response, the receiver suppresses interference based on the maximum signal-to-interference ratio criterion. The blind adaptive receiver requires only coarse timing information and a priori knowledge of the desired user's PN sequence for adaptation. Numerical results show that the adaptive receiver significantly suppresses interference by successfully estimating the channel response and the interference statistics with a low computational complexity. An extension to spatio-temporal processing using an array antenna is also discussed     

Adaptive signal processing using FIR and IIR filters

A method is presented for designing optimal adaptive digital filters. The derivation is based upon filtering a desired signal which has been corrupted by a "noise" like signal so the least-square error between the filtered output and the desired output is minimized. The filter is contrasted with both the Levinson and Widrow filters. The greatest utility of the derived filters are in digital signal processing applications where real-time or stability are critical constraints.     

Robust adaptive beamforming for general-rank signal models

The performance of adaptive beamforming methods is known to degrade severely in the presence of even small mismatches between the actual and presumed array responses to the desired signal. Such mismatches may frequently occur in practical situations because of violation of underlying assumptions on the environment, sources, or sensor array. This is especially true when the desired signal components are present in the beamformer "training" data snapshots because in this case, the adaptive array performance is very sensitive to array and model imperfections. The similar phenomenon of performance degradation can occur even when the array response to the desired signal is known exactly, but the training sample size is small. We propose a new powerful approach to robust adaptive beamforming in the presence of unknown arbitrary-type mismatches of the desired signal array response. Our approach is developed for the most general case of an arbitrary dimension of the desired signal subspace and is applicable to both the rank-one (point source) and higher rank (scattered source/fluctuating wavefront) desired signal models. The proposed robust adaptive beamformers are based on explicit modeling of uncertainties in the desired signal array response and data covariance matrix as well as worst-case performance optimization. Simple closed-form solutions to the considered robust adaptive beamforming problems are derived. Our new beamformers have a computational complexity comparable with that of the traditional adaptive beamforming algorithms, while, at the same time, offer a significantly improved robustness and faster convergence rates.     

The tripole antenna: An adaptive array with full polarization flexibility

The performance of an adaptive array using three mutually perpendicular dipoles (a "tripole") is studied. A desired signal and an interference signal, each with arbitrary angle of arrival and polarization, are assumed incident on the array. Uncorrelated thermal noise is also assumed present on each element signal. The output desired signal-to-interference-plus-noise ratio (SINR) is computed as a function of the signal arrival angles and polarizations. It is shown that for most angles of arrival and polarizations, the array has an excellent ability to protect a desired signal from interference. Certain special cases where the performance is not good are discussed in detail.     

A linear MMSE receiver for multipath asynchronous random-CDMA with chip pulse shaping

This paper studies the design and implementation of a linear minimum mean-square error (LMMSE) receiver in asynchronous direct-sequence code-division multiple-access (DS-CDMA) systems that employ long-code pseudonoise (PN) sequences and operate in multipath environments. The receiver is shown to be capable of multiple-access interference (MAI) suppression and multipath diversity combining without the knowledge of other users' signature sequences. It maximizes output signal-to-noise ratio (SNR) with the aid of a new chip filter which exploits the cyclostationarity of the received signal and combines all paths of the desired user that fall within its supported time span. The performance of the LMMSE receiver is compared with that of the coherent selective RAKE receiver. The achieved gain is on the order of 0.6-1.8 dB in dense multipath environments of current narrow-band settings and nonuniform power distribution scenarios of next-generation CDMA systems. An example of adaptive implementation of the LMMSE receiver is presented and accompanied by complexity analysis, training curves, and quantitative performance comparisons illustrating the convergence rate and steady-state performance of the adaptive algorithms.     

Adaptive Spread-Spectrum Systems Using Least-Squares Lattice Algorithms

Practical communication systems must cope with many uncertainties in addition to determining the transmitted data, e.g., the direction, timing, and distortion of the desired signal, and the spectral and spatial distribution of the interference, all of which may change with time. This paper describes exact least-squares (LS) recursive lattice algorithms which resolve these uncertainties in a direct-sequence spread-spectrum digital communication system. The adaptive LS algorithm is recursive beth in order and time, and converges rapidly to the uncertain parameters. Time-discrete algorithms may be mechanized by a receiver containing integrate-and-dump circuits operating at the chip rate of the pseudonoise (PN) sequence, one in each in-phase and each quadrature channel of each sensor array element's output. Different configurations of optimal time-discrete receivers are presented and transformed into adaptive receivers by taking advantage of the spectral properties of the different kinds of LS filters. Simulation results are presented and some guide lines are given for the architecture of an adaptive direct-sequence spread-spectrum system.     

Adaptive antenna systems

A system consisting of an antenna array and an adaptive processor can perform filtering in both the space and the frequency domains, thus reducing the sensitivity of the signal-receiving system to interfering directional noise sources. Variable weights of a signal processor can be automatically adjusted by a simple adaptive technique based on the least-mean-squares (LMS) algorithm. During the adaptive process an injected pilot signal simulates a received signal from a desired "look" direction. This allows the array to be "trained" so that its directivity pattern has a main lobe in the previously specified look direction. At the same time, the array processing system can reject any incident noises, whose directions of propagation are different from the desired look direction, by forming appropriate nulls in the antenna directivity pattern. The array adapts itself to form a main lobe, with its direction and bandwidth determined by the pilot signal, and to reject signals or noises occurring outside the main lobe as well as possible in the minimum mean-square error sense. Several examples illustrate the convergence of the LMS adaptation procedure toward the corresponding Wiener optimum solutions. Rates of adaptation and misadjustments of the solutions are predicted theoretically and checked experimentally. Substantial reductions in noise reception are demonstrated in computer-simulated experiments. The techniques described are applicable to signal-receiving arrays for use over a wide range of frequencies.     

Adaptive acquisition of PN sequences for DSSS communications

Since the received signal levels in mobile communications are unknown and the location is varying, acquisition schemes for pseudonoise (PN) sequences with fixed thresholds cannot provide satisfactory performance. This fixed-threshold scheme may cause too many false alarms or result in a low detection probability for a selected threshold value. We present an adaptive acquisition scheme for PN sequences which estimate the background power level, multiply it with a threshold coefficient to keep the false alarms constant, and use it as a threshold     

Protection of a Narrow-Band BPSK Communication System with an Adaptive Array

This paper describes the performance of an adaptive array when used with narrow-band BPSK communication signals; A previous paper [11] described the performance of an adaptive array with a standard BPSK signal when the array bandwidth is several times the signal bandwidth. These earlier results are extended to the case where the array bandwidth is as small as possible, equal to the desired signal symbol rate. To realize such a bandwidth reduction, it is necessary to reshape the BPSK signaling waveform before transmission to prevent intersymbol interference. This is done by passing the BPSK signal through a pulseshaping filter at the transmitter. The performance of the optimal detector for the narrow-band BPSK signal is determined when this detector operates behind an adaptive array that is subjected to CW interference. The bit error probability is obtained as a function of the desired signal and interference powers and arrival angles as well as the array bandwidth.     

A Robust and Adaptive Carrier Recovery Method for Chinese DTTB Receiver

This paper presents a robust and adaptive carrier recovery method for Chinese digital terrestrial television broadcasting (DTTB) system in which pilot signal and pseudonoise (PN) sequence are adopted to help carrier recovery. The conventional methods utilize pilot or PN sequence respectively. In this paper, we try to combine the advantage of each method together and propose a well designed state machine to control system state automatically. Moreover, as for using PN sequence, a fine PN tracking state is introduced to ensure the robustness of the proposed method. Software simulations show that the proposed method can provide large acquisition range, short acquisition time and small tracking jitter in severely distorted static and dynamic channels. Lab tests and field trials also prove its good performance in real propagation environments.     

Increasing the up-link CW interference immunity of non-coherent direct sequence pseudonoise (DSPN) reception with on-board processing

The adaptive threshold A/D converter is by now a familiar technique for increasing the CW interference immunity of coherently detected direct sequence pseudonoise (DSPN) spread-spectrum signals, especially where the frequency of the CW interferer may be changing so rapidly and over such a large portion of the signalling bandwidth that well known spectrum excision techniques prove ineffective. The present paper extends the theory to the case of non-coherent reception of direct sequence pseudonoise (DSPN) signals. The A/D converter is found to perform well in both CW and Gaussian interference. Conversion gain is seen to persist even if the interference is intentionally pulsed at an optimally reduced duty factor (from the interferer's point of view) in the attempt to confuse the adaptive threshold. The specific case of 32-chip data symbols is treated, wherein the adaptation is applied strictly to individual symbols. In some cases these restrictions will actually improve performance.     

The Calculation of the Statistical Properties of the Synchronization Times in a PN Spread Spectrum System for Minimized Acquisition Time Designs

This paper presents a method to calculate the mean acquisition time and the mean time to lose lack in a pseudonoise (PN) spread spectrum system. In addition, all the desired statistical moments of these synchronization times can be evaluated. The theory is applied to optimize the acquisition process in a system with a low time-bandwidth product of the synchronization detector. The results demonstrate the dependence of the synchronization times on the information signal and permit optimum design of the synchronization detector.     

An adaptive array for interference rejection

An adaptive array that rejects undesired or interfering signals is presented. The array pattern is controlled by an adaptive feedback system based on a steepest descent minimization of mean-square error. Error is defined as the difference between the array output and a locally generated reference signal. Minimization of mean-square error is closely related to maximization of signal-to-noise ratio (SNR). A two-element adaptive array has been built, and its experimental performance is discussed. Typical patterns for various desired and interfering signals are shown, as well as measured transient response. Finally, some experiments showing the array behavior with modulated signals are described. The results show that such an antenna system is capable of automatically rejecting interfering signals, subject only to certain basic constraints. No a priori information about the angles of arrival of the signals is required, Detailed knowledge of the waveforms of the desired and interfering signals is also not needed, although the spectral characteristics of the desired signal must be known.     

PN code acquisition using smart antenna for spread-spectrum wireless communications. I

The smart antenna (a blind adaptive antenna array) has brought much attention to its ability to improve the future code-division multiple-access (CDMA) wireless communications systems. However, Adachi et al. (1998), employed only one out of M elements that are in a smart antenna array during the pseudonoise (PN) code acquisition process due to the difficulty in obtaining the weight coefficients of the smart antenna and PN code acquisition jointly and adaptively. Yet, as the PN code is acquired, all M elements are used by Adachi et al. to improve the signal-to-noise ratio (SNR) at a reverse link. We propose an efficient PN code acquisition scheme where all elements are employed during PN code acquisition. Also, we show that by using all elements, the PN code acquisition time can be shortened by at least 40% for a given signal-to-noise ratio and M=5, compared to the single element case. Furthermore, the power of a random access user signal in the reverse link can be lowered at least 3 dB. The additional computational load and complexity to use the proposed PN code acquisition are insignificant.     

Performance of the Adaptive A/D Converter in Combined CW and Gaussian Interference

Previous analyses are extended to give the performance of the adaptive 2 bit A/D converter in combined CW and Gaussian interference. The converter is seen to give substantial conversion gain even when the direct sequence pseudonoise (DSPN) spread signal is much weaker than the Gaussian component of interference. The upper bound on conversion gain depends primarily on the relative strengths of the Gaussian and CW components of interference. The relevant relationships are given in graphical form.     

Robust cyclic adaptive beamforming using a compensation method

This paper deals with the problem of robust adaptive array beamforming using signal cyclostationarity. The constrained cyclic adaptive beamforming (C-CAB) algorithm presented by Wu and Wong (1996) [6] has been shown to be effective in performing adaptive beamforming without requiring the direction vector or the waveform of the desired signal. However, this algorithm suffers from severe performance degradation even if there is a small mismatch in the cycle frequency of the desired signal. In this paper, we first evaluate the performance degradation of the C-CAB algorithm in the presence of cycle frequency error (CFE). A novel compensation method in conjunction with the subspace projection is then proposed to tackle the problem due to CFE. We reconstruct the required cyclic conjugate correlation matrix by using a compensation matrix to cope with the deterioration of its dominant singular value when CFE exists. Finally, several simulation examples are provided to show the effectiveness of the proposed algorithm.     

An adaptive array utilizing an adaptive spatial averaging technique for multipath environments

When the interference is coherent with the desired signal, the conventional adaptive arrays working under the guiding principle of output power minimization tend to cancel the desired signal by using the coherent interference. A technique is described which enables the adaptive array to function even under such an environment. The array is divided into subarrays, whose input correlation matrices are adaptively averaged so as to produce a Toeplitz matrix which would be obtained when the interference did not correlate with the desired signal. The averaged matrix is now free from correlation terms between the desired signal and interference, and therefore may be used to derive the optimum weight for the array element just as in the ordinary radio environment of incoherent interference. Numerical examples show that the new adaptive array is highly capable to suppress the coherent interferences as well as incoherent ones.     

基于SMI－CMA联合自适应算法的性能分析

恒模算法(CMA)被广泛地应用到盲自适应波束形成中，除了传输信号波形具有恒定的包络外．CMA不需要先验知识。基于SMI—CMA算法的恒模(CM)阵列级联的结构，由SMI算法决定CMA的初始权向量．系统可以分离多个同信道信源，在干扰信号较强时，仍有稳定的SINR输出，具有较好的收敛速度。仿真结果也证明了SMI—CMA算法具有较强的稳健型和较快的收敛速度。     

IIR array processing based fast adaptive null steering algorithm using shift-invariant subarrays

This paper presents and investigates a fast adaptive null steering system employing infinite impulse response (IIR) array processing. The new algorithm is of considerable interest in communications where the desired signal is weak compared with the interfering signals or where the desired signal can be easily separated out. With the proposed algorithm, the nulls of the array system are repetitively updated one by one in a cyclical manner through a sequence of adjustment cycles. In each adjustment cycle, a particular null is updated by using the least mean square (LMS) algorithm and the update of each particular null will not affect other null positions. The proposed method is very effective and useful in the sense that it will result in a nearly flat gain in the antenna pattern, except zero gains at the null directions. Moreover, as will be demonstrated later from both analysis and simulation results, the convergence behavior of the new algorithm is significantly faster than the linearly constrained minimum variance (LCMV) method and is almost independent of the external noise environment.     

A new solution to adaptive control

A new solution to adaptive control for a linear time-variant multivariable process with unknown parameters is presented. The proposed method requires knowledge of only input and output data and, consequently, no state estimation is necessary. The control signal is generated by a control block placed in series with the process. The control block behaves as the "adaptive" inverse of the process, and has as its input the desired output of the process. The whole control system is asymptotically hyperstable. The control system can solve the main problems encountered in process control: structural differences and parameter variations. In addition, it behaves satisfactorily under the influence of perturbations. The method is extremely simple to implement and quite general in scope. Various examples are included for illustration.