International Telemetering Conference Proceedings / October 26-29, 1998 / Town & Country Resort Hotel and Convention Center, San Diego, California / In computer simulations of communication systems, linear congruential generators and shift registers are typically used to model noise and data sources. These generators are often assumed to be close to ideal (i.e. delta correlated), and an insignificant source of error in the simulation results. The samples generated by these algorithms have non-ideal autocorrelation functions, which may cause a non-uniform distribution in the data or noise signals. This error may cause the simulation bit-error-rate (BER) to be artificially high or low. In this paper, the problem is described through the use of confidence intervals. Tests are performed on several pseudo-random generators to access which ones are acceptable for computer simulation.

This research investigates robust demodulation of Gaussian Minimum Shift Keying (GMSK) signals, using demodulator diversity and real-time bit-error-rate (BER) estimation. GMSK is particularly important because of its use in promi- nent wireless standards around the world (GSM, DECT, CDPD, DCS1800, and PCS1900). The dissertation begins with a literature review of GMSK demodu- lation techniques (coherent and noncoherent) and includes an overview of single- channel interference rejection techniques in digital wireless communications. Vari- ous forms of GMSK demodulation are simulated, including the limiter discrimina- tor and di erential demodulator (i.e., twenty-five variations in all). Ten represent new structures and variations. The demodulator performances are evaluated in realistic wireless environments, such as additive white Gaussian noise, co-channel interference, and multipath environments modeled by COST207 and SMRCIM. Certain demodulators are superior to others for particular channel impairments, so that no demodulator is necessarily the best in every channel impairment. This research formally introduces the concept of demodulator diversity, a new idea which consists of a bank of demodulators which simultaneously demodulate the same signal and take advantage of the redundancy in the similar signals. The dissertation also proposes practical real-time BER estimation techniques which have tremendous ramifications for communications. Using Parzen's estimator for probability density functions (pdfs) and Gram-Charlier series approximation for pdfs, BER can be estimated using short observation intervals (10 to 500 training symbols) and, in some cases, without any training sequence. We also introduce new variations of Gram-Charlier estimation using robust estimators. BER (in place of MSE) can now drive adaptive signal processing. Using a cost function and gradient for Parzen's estimator (derived in this paper), BER estimation is applied to demodulator diversity with substantial gains of 1-10 dB in carrier- to-interference ratio over individual receivers in realistic channels (with adaptive selection and weighting). With such gains, a BER-based demodulator diversity scheme can allow the employment of a frequency reuse factor of N = 4, instead of N = 7, with no degradation in performance. A lower reuse factor means more channels are available in a cell, thus increasing overall capacity. The resulting techniques are simple and easily implemented at the mobile. BER estimation techniques can also be used in BER-based equalization and dynamic allocation of resources. / Ph. D.

It is known that a matched filter is optimal for a signal corrupted by Gaussian noise. In a wireless environment, the received signal may be corrupted by Gaussian noise and a variety of other channel disturbances: cochannel interference, multiple access interference, large and small-scale fading, etc. Adaptive filtering is the usual approach to mitigating this channel distortion. Existing adaptive filtering techniques usually attempt to minimize the mean square error (MSE) of some aspect of the received signal, with respect to the desired aspect of that signal. Adaptive minimization of MSE does not always guarantee minimization of bit error rate (BER). The main focus of this research involves estimation of the probability density function (PDF) of the received signal; this PDF estimate is used to adaptively determine a solution that minimizes BER. To this end, a new adaptive procedure called the Minimum BER Estimation (MBE) algorithm has been developed. MBE shows improvement over the Least Mean Squares (LMS) algorithm for most simulations involving interference and in some multipath situations. Furthermore, the new algorithm is more robust than LMS to changes in algorithm parameters such as stepsize and window width. / Master of Science

This thesis is related to the Bit Error Rate (BER) estimation for any digital communication system. In many designs of communication systems, the BER is a Key Performance Indicator (KPI). The popular Monte-Carlo (MC) simulation technique is well suited to any system but at the expense of long time simulations when dealing with very low error rates. In this thesis, we propose to estimate the BER by using the Probability Density Function (PDF) estimation of the soft observations of the received bits. First, we have studied a non-parametric PDF estimation technique named the Kernel method. Simulation results in the context of several digital communication systems are proposed. Compared with the conventional MC method, the proposed Kernel-based estimator provides good precision even for high SNR with very limited number of data samples. Second, the Gaussian Mixture Model (GMM), which is a semi-parametric PDF estimation technique, is used to estimate the BER. Compared with the Kernel-based estimator, the GMM method provides better performance in the sense of minimum variance of the estimator. Finally, we have investigated the blind estimation of the BER, which is the estimation when the sent data are unknown. We denote this case as unsupervised BER estimation. The Stochastic Expectation-Maximization (SEM) algorithm combined with the Kernel or GMM PDF estimation methods has been used to solve this issue. By analyzing the simulation results, we show that the obtained BER estimate can be very close to the real values. This is quite promising since it could enable real-time BER estimation on the receiver side without decreasing the user bit rate with pilot symbols for example.