Performance evaluation of spread spectrum system with cochannel interference through a nonlinear channel

This thesis deals with the problem of more than one subscriber transmitting data signals through a common satellite repeater using code division multiplexing to separate the signals. We are concerned with the problem of amplifying two DS spread spectrum signals, both QPSK or BPSK modulated, in a common device in which limiting occurs. One signal is considered the signal we desire to receive, and the other, having the same nominal carrier frequency with a small random offset, is considered to be a cochannel interferer. The case of a cochannel interferer on the uplink and downlink in QPSK signalling and BPSK signalling systems is analyzed in detail. This is an important practical problem in code division multiple access satellite communication systems, which usually contain limiting in the satellite amplifier, often in the form of a saturated traveling wave tube amplifier. The satellite repeater is modeled using a bandpass hard limiter. The inverse Fourier transform method, which is applicable to the analysis of PN spread spectrum systems is applied to calculate the output of the bandpass hard limiter. The limiter output plus AWGN is taken to be the input of a correlation receiver for which we calculate the probability of error as function of the signal to noise and, signal to interference ratios. From these results we can determine the effect on error performance due to the inclusion of a bandpass limiter in the transmission path. The assumptions made in deriving the theoretical performance of the system have been checked by simulating the entire system using the BOSS software package. The results of the simulation show good agreement with the theoretical calculations within 1 to 2 dB in SNR. In addition by means of simulation we were able to explore some features of the system that could not be addressed analytically, such as the effect of unbalanced codes on system performance

Optimal sampling and quantization of synthetic aperture radar signals

Some theoretical and experimental results on optimal sampling and quantization of synthetic aperture radar (SAR) signals are presented. It includes a description of a derived theoretical relationship between the pixel signal to noise ratio of processed SAR images and the number of quantization bits per sampled signal, assuming homogeneous extended targets. With this relationship known, a solution may be realized for the problem of optimal allocation of a fixed data bit-volume (for specified surface area and resolution criterion) between the number of samples and the number of bits per sample. The results indicate that to achieve the best possible image quality for a fixed bit rate and a given resolution criterion, one should quantize individual samples coarsely and thereby maximize the number of multiple looks. The theoretical results are then compared with simulation results obtained by processing aircraft SAR data

Compressive Sensing of Analog Signals Using Discrete Prolate Spheroidal Sequences

Compressive sensing (CS) has recently emerged as a framework for efficiently capturing signals that are sparse or compressible in an appropriate basis. While often motivated as an alternative to Nyquist-rate sampling, there remains a gap between the discrete, finite-dimensional CS framework and the problem of acquiring a continuous-time signal. In this paper, we attempt to bridge this gap by exploiting the Discrete Prolate Spheroidal Sequences (DPSS's), a collection of functions that trace back to the seminal work by Slepian, Landau, and Pollack on the effects of time-limiting and bandlimiting operations. DPSS's form a highly efficient basis for sampled bandlimited functions; by modulating and merging DPSS bases, we obtain a dictionary that offers high-quality sparse approximations for most sampled multiband signals. This multiband modulated DPSS dictionary can be readily incorporated into the CS framework. We provide theoretical guarantees and practical insight into the use of this dictionary for recovery of sampled multiband signals from compressive measurements