Jumi Lee

Breadth-First Signal Decoder: A Novel Maximum-Likelihood Scheme for Multi-Input–Multi-Output Systems

A number of decoding schemes have recently been proposed to perform maximum-likelihood (ML) detection for multi-input-multi-output (MIMO) systems. In this paper, employing a ldquobreadth-firstrdquo search algorithm for closet points in a lattice, we propose a novel ML decoding scheme called the breadth-first signal decoder (BSIDE). Through analysis and computer simulations, it is shown that the BSIDE has the same bit-error-rate performance as the conventional ML decoders while allowing significantly lower computational complexity. In addition, we introduce a simple tuning scheme that allows the BSIDE to have a performance-complexity tradeoff capability as necessary.

Performance of constant modulus adaptive digital filters for interference cancellation

Abstract The constant modulus algorithm (CMA) updates its weight vector to minimize the modulus variation of the output signal. In this paper, the convergence behavior of the CMA used in interference cancellation application is studied. We first investigate the optimum weight vector that minimizes the performance index of the CMA which is defined as the mean-squared difference between the estimated and true moduli. We then analyze the convergence behavior of the squared output modulus and the performance index. Based on these analysis results, several convergence properties of the CMA are discussed.

Detection Schemes for Weak Signals in First-Order Moving Average of Impulsive Noise

In this paper, the detection of weak signals in additive noise described by the first-order moving average (FOMA) of an impulsive process is considered. Specifically, decision regions of the maximum likelihood (ML) and suboptimum ML (S-ML) detectors are derived in the FOMA noise model, and specific examples of the ML and S-ML decision regions are obtained. The ML and S-ML detectors are employed in the antipodal signaling system and compared in terms of bit error rate in an impulsive noise environment. Numerical results show that the S-ML detector, despite its reduced complexity and simpler structure, exhibits practically the same performance as the optimum ML detector. It is also observed that the performance gap between detectors for FOMA and independent and identically distributed noise becomes larger as the degree of noise impulsiveness increases

A truncated adaptive transmission scheme for hybrid multicarrier CDMA/FDM systems in forward link

A truncated adaptive transmission scheme for the hybrid multicarrier CDMA/FDM system is considered in forward link. In the proposed scheme, a data substream is transmitted over the subchannels of which the channel gains are greater than a given threshold, based on the feedback information from the mobile station. We analyze the performance of the proposed system when orthogonal and random signature sequences are used in single- and multiple-cell environment. In the single-cell environment, when orthogonal signature sequences are used, the proposed scheme outperforms the adaptive FH/DS system as well as the conventional MC DS/CDMA system, and accommodates more users than the adaptive FH/DS system while maintaining the orthogonality between users. In the multiple-cell environment also, the proposed scheme has better performance characteristics than the adaptive FH/DS system when orthogonal or random codes are used as spreading sequences.

A novel blind equalizer based on dual-mode MCMA and DD algorithm

We address a new blind equalizer incorporating both the good initial convergence characteristic of the dual-mode modified constant modulus algorithm (MCMA) and the low residual error characteristic after convergence of the decision-directed (DD) algorithm. In the proposed scheme, a convergence detector is employed to help switching from the dual-mode MCMA to the DD algorithm. We have observed that the proposed scheme exhibits a good overall performance in comparison with the CMA, MCMA, and dual-mode MCMA.

Analysis of an adaptive rate convolutionally coded multicarrier DS/CDMA system

The analysis of an adaptive rate convolutionally coded multicarrier direct sequence code division multiple-access (DS/CDMA) system is considered. In order to accommodate a number of coding rates easily and make the encoder and decoder structure simple, we use the rate-compatible punctured convolutional (RCPC) code. We obtain data throughputs at several coding rates, and choose the coding rate that has the highest data throughput in the signal-to-interference and noise ratio (SINR) sense. To achieve maximum data throughput, a rate adaptive system is proposed based on the channel state information (the SINR estimate). The SINR estimate is obtained by the soft decision Viterbi decoding metric. We show that the proposed rate adaptive convolutionally coded multicarrier DS/CDMA system can enhance the spectral efficiency and provide frequency diversity.

Explicit correlation coefficients among random variables, ranks, and magnitude ranks

In this correspondence, we address the derivation of joint distributions and correlation coefficients for seven pairs of statistics used commonly in a number of signal detection schemes. The upper and lower bounds of the correlation coefficients are obtained, and relationships among the correlation coefficients are derived. Explicit values of the correlation coefficients evaluated for some specific noise distributions are shown for easy reference.

Rapid acquisition of PN sequences with a new decision logic

In this paper, a fast acquisition scheme of pseudonoise (PN) sequences for direct-sequence spread-spectrum systems is proposed. The scheme exploits a new decision logic not only to estimate chip values, but also to check the reliability of the chip estimates. As a result, the internal state of a PN sequence generator is estimated more accurately. We derive the probability of finding a correct state estimate and show that the proposed scheme can reduce the average number of chips for acquisition when compared with the conventional scheme. It is also shown that the performance improvement is more noticeable in the moderate signal-to-noise-ratio range.

Correlation of parametric and nonparametric statistics for applications in signal detection

In this paper, we address correlation coefficients among some representative statistics of independent and identically distributed random signals. The lower and upper bounds on the correlation coefficients are obtained for random signals and their ranks, magnitudes, and magnitude ranks, which in general may or may not be correlated. Examples of specific distributions are given for the bounds, and implications of the correlation coefficients in signal detection applications are indicated.

Noncoherent sequential code acquisition based on simplified maximum likelihood ratios

In this paper, we consider the noncoherent code acquisition problem using sequential schemes. To alleviate the computational complexity of the maximum likelihood method, simplified schemes are proposed and analyzed for the truncated sequential probability ratio test. The performance of the simplified and original schemes are compared in additive white Gaussian noise and slowly varying fading channels. Numerical results show that the proposed schemes have essentially the same performance as the original schemes while allowing simpler structures.