The design of a simplified detector for signal in Middleton's class-A noise is considered. The optimal detector is impractical due to the complexity of the probability density function of the noise. The conventional Gaussian detector (known as the matched filter or the correlator) has near-optimal performance only with relatively high SNR values. Different suboptimal detectors have been proposed to give robust performance with different levels of complexity such as the locally optimal Bayesian detector. In this paper, we propose a unified simple approach to design a near- optimal detector with considerably low complexity by linearly approximating the optimal log-likelihood ratios of the received symbols. The resultant detector has near-optimal performance with low complexity.

The design of detectors for binary signals in symmetric alpha-stable noise is considered. Since the optimal detector is impractically complex, many suboptimal detectors have been proposed such as the Gaussian, soft limiter, myriad and Cauchy detectors. However, no adequate explanation for the difference in performance between these detectors has been proposed. In this paper, we propose a novel framework, based on the optimal decision regions, that is used to justify the performance of many suboptimal detectors and compare them to the optimal one. Moreover, the analysis of the framework provides a novel method to significantly improve the performance of the soft limiter detector by employing an adaptive threshold that is a function of the signal level. As the number of samples per symbol increases, the performance of the proposed adaptive detector approaches the optimal performance at almost no additional complexity over the conventional Gaussian detector.

When passed through a high power amplifier (HPA), downlink direct sequence-code division multiple access (DS- CDMA) signals result in additional out-of-band emissions, or spectral regrowth, which could affect adjacent channels. In this paper, we explore which characteristics of the input CDMA signal, in relation to the amplifier characteristics, contribute to spectral regrowth. These characteristics represent the key features of the signal's interplay with the HPA, which give the system designer/operator the ability to minimize the spectral regrowth in the transmitted signal. The amplifier chain considered in this paper includes a predistorter (PD), namely PD- HPA. Assuming that the baseband CDMA signal is characterized as a band-limited Gaussian process, we develop analytic expressions for the characteristics contributing to spectral regrowth. Finally, simulation experiments are presented to demonstrate the effect of the established signal characteristics on spectral regrowth.

This paper evaluates the bit error rate performance of a ultra-wideband (UWB) communication system in a Lognormal flat fading channel under the impact of narrow band interference (NBI) signals. The NBI signal is approximated by the sum of independent asynchronous tone interferers with arbitrary frequencies. A closed form expression for the bit error rate performance of a UWB system in the presence of NBI is evaluated with the aid of the Gaussian Hermite quadrature expansion. The analytic results are also verified and compared with simulation results. It will be shown that the NBI signal has a noticeable impact on the performance of UWB systems in Lognormal flat fading channels.

The design of near-optimal detectors for binary signals in α-stable interference using two receive antennas is considered. The optimal detector requires more complex computation, whereas the linear (Gaussian) detector is practically simple but suffers from performance degradation with α-stable noise. In this paper, based on the optimal decision regions analysis, we propose to approximate the optimal decision boundaries by using linear segments which results in a novel piecewise detector. The proposed detector has much less complexity over the optimal detector. Also, the analytical evaluation shows near-optimal performance of the piecewise detector. Moreover, simulation results show that the proposed detector has robust performance for different values of α.

The design of detectors for binary signals in interference modeled using the symmetric α-stable distribution is considered. Since the optimal detector is impractically complex, many suboptimal detectors have been proposed such as the linear, soft limiter and Cauchy detectors. However, no adequate explanation for the difference in performance between these detectors has been proposed. In this paper, we propose a novel framework, based on the optimal decision regions, that is used to justify the performance of many suboptimal detectors and compare them to the optimal one. Moreover, the analysis of the framework provides a novel method to significantly improve the performance of the soft limiter detector by employing an adaptive threshold that is a function of the signal level and noise dispersion. As the number of samples per symbol increases, the performance of the proposed adaptive detector approaches the optimal performance at almost no additional complexity over the conventional linear (Gaussian) detector.

The design of Viterbi decoders for signals in noise modeled using the symmetric α-stable distribution is considered. The traditional Viterbi decoder, which has a branch metric optimized for Gaussian noise, performs poorly in symmetric α-stable noise. Since the optimal maximum likelihood branch metric is impractically complex, many suboptimal metrics have been proposed, such as the hard decision, p-norm and absolute (1-norm) metric. A Viterbi decoder that uses the absolute branch metric has better performance and lower complexity, however, its performance degrades when α decreases. In this paper, the effects of the suboptimal metrics on the performance of the Viterbi decoder are analyzed, and a clear justification for the performance of the decoder that uses the Gaussian and absolute metrics is provided. Moreover, this analysis is used to design a low complexity suboptimal branch metric that improves the performance of the Viterbi decoder by about 0.75 to 2 dB compared to the absolute branch metric for different values of α, at almost no additional complexity.

This paper proposes a robust near-field adaptive beamformer for microphone array applications in small rooms. Robustness against location errors is crucial for near-field adaptive beamforming due to the difficulty in estimating near-field signal locations especially the radial distances. A near-field regionally constrained adaptive beamformer is proposed to design a set of linear constraints by filtering on a low rank subspace of the near-field signal over a spatial region and frequency band such that the beamformer response over the designed spatial-temporal region can be accurately controlled by a small number of linear constraint vectors. The proposed constraint design method is a systematic approach which guarantees real arithmetic implementation and direct time domain algorithms for broadband beamforming. It improves the robustness against large errors in distance and directions of arrival, and achieves good distance discrimination simultaneously. We show with a nine-element uniform linear array that the proposed near-field adaptive beamformer is robust against distance errors as large as /spl plusmn/32% of the presumed radial distance and angle errors up to /spl plusmn/20/spl deg/. It can suppress a far field interfering signal with the same angle of incidence as a near-field target by more than 20 dB with no loss of the array gain at the near-field target. The significant distance discrimination of the proposed near-field beamformer also helps to improve the dereverberation gain and reduce the desired signal cancellation in reverberant environments.

This paper discusses eigenvector constraint design for broadband adaptive array beam forming. The constraint equations are constructed using the real and imaginary parts of the steering vectors and the response vectors, thus perm its real arithmetic and guarantees real outputs. A simple and elegant structure is developed for implementing the designed beam former by a Generalized Sidelobe Canceler (GSC). This structure reduces the computational complexity from O (N2) to O (N), where N being the dimension of the weight vector.

The design and performance of a high data rate modem that transmits asynchronous transfer mode (ATM) packets over indoor radio channels is discussed. A discrete Fourier transform (DFT)-based multicarrier modulation technique is used to mitigate intersymbol interface (ISI) caused by a multipath spread of up to 250 ns. A rate one-half channel code is used to combat fading. Computer simulation is performed to investigate the system performance for five different multipath intensity profiles. The system performance is compared using a differentially coherent scheme and a coherent scheme based on channel estimation. The effects of carrier frequency offset and some of the hardware nonlinearities are discussed. Using various channel codes, an signal-to-noise ratio (SNR) of 14-21 dB is required at an average bit error rate (BER) of 10/sup -5/ to transmit a total of 155 Mb/s data over a bandwidth of 280 MHz.

An examination is made of the performance of a squaring loop and a fourth-power loop used for tracking the received carrier phase of binary continuous-phase modulated (CPM) signals with index 1/2. Noise-free analysis is performed first and a simple relationship between the phase error and the control voltage is obtained for each case, with the premodulation filter response as a parameter. Linearized analysis of the phase error variance is then conducted in the presence of additive white Gaussian noise. It is shown that the phase variance in both cases contains a self-noise component that sets a lower bound on the synchronizer's performance at very high signal-to-noise ratios. Numerical results are presented for a number of popular CPM signals. It is found that the squaring loop performs best with MSK (minimum shift keying), while the fourth-power loop performs best with duobinary MSK.>

Detection of continuous phase modulation (CPM) signals can be accomplished using quadrature coherent detectors which include a pair of linear and time-invariant postdetection filters. Performance of the quadrature detectors is highly sensitive to the postdetection filters response. This paper presents a rigorous derivation of an optimum postdetection filter response. The derivation is based on minimizing the mean-square interference subject, to the constraint that the filter noise bandwidth is held constant. The amount of computations involved is fairly small and increases linearly with the receiver observation interval. Performance analysis results for several modulation techniques are presented.