3:30, SPCOM-L8.1
OPTIMAL SIGNAL DESIGN AND DETECTION FOR FAST FADING CHANNELS
C. LO, T. MOON
In this paper, we characterize optimal detection and signaling (in terms of signal-to-noise ratio) for a fast fading channel when the autocorrelation function of the channel variation is known. We find that the well known matched filter and Rake receiver are limiting cases of our result. Also, we provide a procedure that finds a pair of signals for digital communication. With land mobile fading channel, the signals obtained with our procedure have a performance significantly better than traditional flat-top pulse in terms of probability of error rate.

3:50, SPCOM-L8.2
JOINT BLIND EQUALIZATION AND ESTIMATION OF THE SYMBOL PERIOD: A CONTRAST FUNCTION APPROACH.
S. HOUCKE, A. CHEVREUIL, P. LOUBATON
The blind estimation of the symbol period of an unknown linearly modulated signal is addressed. We propose an original methodology relying on the concept of blind deconvolution, which does not suffer from the drawbacks of the classical approaches relying upon the cyclostatinarity of the received signal. Under suitable technical conditions, we show that the optimization of certain cost functions leads to the identification of the symbol rate. Simulation results illustrate the excellent performance of the method.

4:10, SPCOM-L8.3
SUBSPACE DETECTORS FOR STOCHASTIC PROCESS SHIFT KEYING
A. SALBERG, A. HANSSEN
We present a new digital modulation technique that introduces covertness in digital communications in a simple fashion. The basic principle is to transmit realizations of a stochastic process in such a manner that the transmitted waveform appears noiselike. The transmitted waveform is expressed in a subspace formalism, allowing for an elegant geometrical interpretation of the waveform, and a simple and accurate subspace detector for the receiver. The effect of inter-symbol-interference (ISI) is also studied, an a simple zero-forcing subspace detector is suggested. The technique is demonstrated by numerical simulations, and it shows that our simple subspace detectors yield high-quality and reliable receivers.

4:30, SPCOM-L8.4
CLASSIFICATION OF DIGITAL MODULATION BY MCMC SAMPLING
S. LESAGE, J. TOURNERET, P. DJURIC
This paper addresses the problem of classification of digital modulations by MCMC sampling and the maximum-likelihood 'plug-in' classifier. The main idea of this classifier consists of replacing the unknown parameters appearing in the likelihood of the observed data by their estimated values. In the proposed implementation, classifications in the presence of phase and frequency offsets as well as residual filtering effects coming from imperfect channel equalization are considered. These parameters are estimated by averaging the samples generated by the Metropolis-Hastings algorithm. The proposed scheme has been tested for many scenarios and its performance has been compared with two well known classification methods. The obtained results show that our classifier outperforms the other methods considerably.

4:50, SPCOM-L8.5
CRAMER-RAO LOWER BOUND FOR FREQUENCY ESTIMATION IN MULTIPATH RAYLEIGH FADING CHANNELS.
Y. ZAKHAROV , V. BARONKIN , T. TOZER
This paper concerns the estimation of a frequency offset of a known (pilot) signal propagated through a slowly fading multipath channel, such that channel parameters are considered to be constant over the observation interval. We derive a Cramer-Rao Lower Bound (CRLB) and maximum likelihood (ML) frequency estimation algorithm for additive Gaussian noise and path amplitudes having complex zero-mean Gaussian distribution when covariance matrices of the fading and noise are known. In particular, we consider the scenarios with white noise, independent fading of path amplitudes and pilot signals with a diagonal correlation matrix. We compare simulation results for the ML estimator with the CRLB. We also show that the results obtained can be extended to scenarios with fast fading channels.

5:10, SPCOM-L8.6
PARAMETER ESTIMATION OF BINARY CPM SIGNALS
J. RIBA-SAGARRA, G. VAZQUEZ-GRAU
Estimation of frequency and symbol timing in Continuous Phase Modulated (CPM) signals is investigated in this paper. Several well-known statistical approaches, classically applied to the sensor array problem, are used to derive non-data-aided algorithms under a unifying general framework (estimation-directed). A new cost function is proposed which is shown to provide a good compromise between additive and pattern noise cancellation, when the additive noise power is unknown.