Ed Shwedyk

Detection of bandlimited signals over frequency selective Rayleigh fading channels

Presents sequence estimation for the frequency selective Rayleigh fading channel. Maximum likelihood estimation using the Viterbi algorithm (MLSE-VA) and sequential sequence estimation (SSE) are developed. Both MLSE-VA and SSE consist of a set of Kalman filters which estimate the fading channel as time evolves. Computer simulations for two different channel models show that the error performance of the two approaches is essentially the same. SSE however has considerably less computational complexity than MLSE-VA. To improve the error performance, diversity is combined with both MLSE-VA and SSE. The simulations show that diversity results in a signal to noise ratio gain of greater than 10 dB. >

Blind Spectrum Sensing for OFDM-Based Cognitive Radio Systems

Given the ever-growing demand for radio spectrum, cognitive radio has recently emerged as an attractive wireless technology. Since orthogonal frequency-division multiplexing (OFDM) is one of the major wideband transmission techniques, detection of OFDM signals in low-signal-to-noise-ratio scenario is an important research problem. In this paper, it is shown that cyclic prefix (CP) correlation coefficient (CPCC)-based spectrum sensing, which was previously introduced as a simple and computationally efficient spectrum-sensing method for OFDM signals, is a special case of the constrained generalized likelihood ratio test (GLRT) in the absence of multipath. As such, the performance of this algorithm degrades in a multipath scenario, where OFDM is usually implemented. Furthermore, by considering multipath correlation in the GLRT algorithm and employing the inherent structure of OFDM signals, a simple and low-complexity algorithm called the multipath-based constrained-GLRT (MP-based C-GLRT) algorithm is obtained. The MP-based C-GLRT algorithm is shown to outperform the CPCC-based algorithm in a rich multipath environment. Further performance improvement can be achieved by simply combining both the CPCC- and MP-based C-GLRT algorithms. A simple GLRT-based detection algorithm is also developed for unsynchronized OFDM signals, whose performance is only slightly degraded when compared with the synchronized detection in a rich multipath environment.

Sequence detection and channel state estimation over finite state Markov channels

A useful model for general time-varying channels is a finite state Markov chain. In this paper, maximum likelihood sequence estimation (MLSE) for signals over finite state Markov channels (FSMCs) is studied. Also studied is the maximum a posteriori (MAP) channel state estimation. When coded signals with interleaving are transmitted, the channel estimates can be used to make soft-decision decoding. The error performance of the proposed sequence and channel state estimation schemes are evaluated through computer simulations. The effect of channel modeling error is also discussed.

Some Aspects of Nonstationary Myoelectric Signal Processing

Nonstationary myoelectric signal processing is considered. A midpoint moving average estimator for the signal variance is developed. The performance of the estimator is analyzed and optimum window size criteria are derived. Comparison of the theoretical performance to experimental performance shows good agreement. The resultant estimation error is only moderately (2-3 percent) degraded from the equivalent stationary case. Finally, the developed estimator is compared to a typical squarer followed by a low-pass filter myoelectric processor. Provided that the low-pass filter has a linear phase characteristic in the passband, the two systems have essentially the same error performance.

A quasi-optimum receiver for continuous phase modulation

A simple receiver structure for any continuous phase modulation (CPM) scheme is introduced. Its front end is just the ordinary linear receiver followed by a subinterval sampler, eliminating the need for the standard analog matched filters. Its design is based on the decomposition of the CPM signal in the Walsh signal space. This brings the hardware requirement to a minimum, and near-optimum performance can be easily obtained.

On error probabilities of DS-CDMA systems with arbitrary chip waveforms

The error probabilities of asynchronous DS-CDMA systems using random signature sequences depend on the number of users, the processing gain and the chip waveforms employed. The exact calculation of the error probabilities is computationally difficult and therefore approximations and bounds are more commonly used. In this article, the improved Gaussian approximation proposed by Holtzman (1992) is extended to include arbitrary chip waveforms. Comparisons to the exact calculation and the standard Gaussian approximation are also made to evaluate the accuracy of the improved Gaussian approximation.

On channel estimation and sequence detection of interleaved coded signals over frequency nonselective Rayleigh fading channels

Due to the receiver complexity introduced by interleaving, the implementation of maximum likelihood (IML) decoding of interleaved coded signals transmitted over frequency nonselective Rayleigh fading channels has been shown to be practically impossible. As an alternative, a two-stage receiver structure has been proposed, where the channel estimation and sequence decoding are done separately. The channel estimation issue in a two-stage receiver is examined in detail in this paper. It is shown that although an optimum (maximum a posteriori (MAP)) channel estimation is not possible in practice, it can be approached asymptotically by joint MAP estimation of the channel and the coded data sequence. The implementation of the joint MAP estimation is shown to be an ML sequence estimator followed by an minimum mean-square error (MMSE) channel estimator. Approximate fill sequence estimation using pilot symbol interpolation is also studied, and through computer simulations, its performance is compared to receivers using hit sequence estimation. The effect of decision delay (DD), prediction order, and pilot insertion rate (PIR) on the reduced complexity ML sequence estimation is investigated as well. Finally, a practical receiver is proposed that makes the best compromise among the error performance, receiver complexity, DD, and power (or bandwidth) expansion due to pilot insertion.

Bandwidth-constrained signature waveforms for maximizing the network capacity of synchronous CDMA systems

Synchronous code-division multiple-access systems where each receiver is a minimum mean-squared-error receiver and each user has the same received power, signaling rate, and required signal-to-interference ratio are considered. Based on the results Viswanath, Anantharam and Tse (see IEEE Trans. Inform. Theory, vol.45, p.1968-83, 1999), the optimal signature waveforms under both fractional out-of-band energy and root-mean-square bandwidth constraints that maximize the network capacity are determined. Comparison to various suboptimal signature waveforms, including the ones constructed from rectangular pulses, is also made to quantify the gain achieved by the optimal signature waveforms.

ML estimation of symbol timing and carrier phase for CPM in Walsh signal space

An algorithm to estimate jointly the symbol timing and carrier phase for continuous-phase modulation (CPM) is described. It is designed to optimize the steady-state performance of the CPM synchronizer and exhibits excellent performance, very close to the optimum maximum-likelihood estimate. The algorithm is simple and practical and may be employed with any CPM scheme. It is based on a signal space decomposition of the CPM signal in the Walsh signal space.

Dielectric measurement of cerebral water content using a Network Analyzer

At present, no practical method exists for monitoring the progression and severity of cerebral oedema in a clinical setting on a continuous basis. In search for such a method, we investigated the electrical characteristics of cerebral tissue at microwave frequencies to quantify cerebral oedema. The dielectric constants of normal and oedematous canine cerebral white matter were measured using a Network Analyzer and then compared to the tissues water content. In addition, salt infiltration and time elapsed after excision of the tissue were examined to determine their effects on the measurements. The water content and dielectric constant of the white matter were linearly related (correlation coefficient, r = 0.903), comparable to results obtained with a Time Domain Reflectometer in previous research. The Network Analyzer, however, is a more robust measurement device and, because of this, can potentially be used for long term measurements. Further, it was found that neither an increased tissue salt content nor the amount of time after excision of the tissue significantly affected the results. This indicates that the dielectric constant of cerebral white matter is mainly a function of the tissues water content.