Ultra-wideband Spread Spectrum Communications using Software Defined Radio and Surface Acoustic Wave Correlators

Ultra-wideband (UWB) communication technology offers inherent advantages such as the ability to coexist with previously allocated Federal Communications Commission (FCC) frequencies, simple transceiver architecture, and high performance in noisy environments. Spread spectrum techniques offer additional improvements beyond the conventional pulse-based UWB communications. This dissertation implements a multiple-access UWB communication system using a surface acoustic wave (SAW) correlator receiver with orthogonal frequency coding and software defined radio (SDR) base station transmitter. Orthogonal frequency coding (OFC) and pseudorandom noise (PN) coding provide a means for spreading of the UWB data. The use of orthogonal frequency coding (OFC) increases the correlator processing gain (PG) beyond that of code division multiple access (CDMA); providing added code diversity, improved pulse ambiguity, and superior performance in noisy environments. Use of SAW correlators reduces the complexity and power requirements of the receiver architecture by eliminating many of the components needed and reducing the signal processing and timing requirements necessary for digital matched filtering of the complex spreading signal. The OFC receiver correlator code sequence is hard-coded in the device due to the physical SAW implementation. The use of modern SDR forms a dynamic base station architecture which is able to programmatically generate a digitally modulated transmit signal. An embedded Xilinx Zynq ™ system on chip (SoC) technology was used to implement the SDR system; taking advantage of recent advances in digital-to-analog converter (DAC) sampling rates. SDR waveform samples are generated in baseband in-phase and quadrature (I & Q) pairs and upconverted to a 491.52 MHz operational frequency. The development of the OFC SAW correlator ultimately used in the receiver is presented along with a variety of advanced SAW correlator device embodiments. Each SAW correlator device was fabricated on lithium niobate (LiNbO3) with fractional bandwidths in excess of 20%. The SAW correlator device presented for use in system was implemented with a center frequency of 491.52 MHz; matching SDR transmit frequency. Parasitic electromagnetic feedthrough becomes problematic in the packaged SAW correlator after packaging and fixturing due to the wide bandwidths and high operational frequency. The techniques for reduction of parasitic feedthrough are discussed with before and after results showing approximately 10:1 improvement. Correlation and demodulation results are presented using the SAW correlator receiver under operation in an UWB communication system. Bipolar phase shift keying (BPSK) techniques demonstrate OFC modulation and demodulation for a test binary bit sequence. Matched OFC code reception is compared to a mismatched, or cross-correlated, sequence after correlation and demodulation. Finally, the signal-to-noise power ratio (SNR) performance results for the SAW correlator under corruption of a wideband noise source are presented

Techniques of detection, estimation and coding for fading channels

The thesis describes techniques of detection, coding and estimation, for use in high speed serial modems operating over fading channels such as HF radio and land mobile radio links. The performance of the various systems that employ the above techniques are obtained via computer simulation tests. A review of the characteristics of HF radio channels is first presented, leading to the development of an appropriate channel model which imposes Rayleigh fading on the transmitted signal. Detection processes for a 4.8 kbit/s HF radio modem are then discussed, the emphasis, here, being on variants of the maximum likelihood detector that is implemented by the Viterbi algorithm. The performance of these detectors are compared with that of a nonlinear equalizer operating under the same conditions, and the detector which offers the best compromise between performance and complexity is chosen for further tests. Forward error correction, in the form of trellis coded modulation, is next introduced. An appropriate 8-PSK coded modulation scheme is discussed, and its operation over the above mentioned HF radio modem is evaluated. Performance comparisons are made of the coded and uncoded systems. Channel estimation techniques for fast fading channels akin to cellular land mobile radio links, are next discussed. A suitable model for a fast fading channel is developed, and some novel estimators are tested over this channel. Computer simulation tests are also used to study the feasibility of the simultaneous transmission of two 4-level QAM signals occupying the same frequency band, when each of these signals are transmitted at 24 kbit/s over two independently fading channels, to a single receiver. A novel combined detector/estimator is developed for this purpose. Finally, the performance of the complete 4.8 kbit/s HF radio modem is obtained, when all the functions of detection, estimation and prefiltering are present, where the prefilter and associated processor use a recently developed technique for the adjustment of its tap gains and for the estimation of the minimum phase sampled impulse response

Nonlinear receivers for DS-CDMA

The growing demand for capacity in wireless communications is the driving force behind improving established networks and the deployment of a new worldwide mobile standard. Capacity calculations show that the direct sequence code division multiple access (DS-CDMA) technique has more capacity than the time division multiple access technique. Therefore, most 3rd generation mobile systems will incorporate some sort of DS-CDMA. In this thesis DS-CDMA receiver structures are investigated from the view point of pattern recognition which leads to new DS-CDMA receiver structures. It is known that the optimum DS-CDMA receiver has a nonlinear structure with prohibitive complexity for practical implementation. It is also known that the currently implemented receiver in 2nd generation DSCDMA mobile handsets has poor performance, because it suffers from multiuser interference. Consequently, this work focuses on sub-optimum nonlinear receivers for DS-CDMA in the downlink scenario. First, the thesis reviews DS-CDMA, established equalisers, DS-CDMA receivers and pattern recognition techniques. Then the new receivers are proposed. It is shown that DS-CDMA can be considered as a pattern recognition problem and hence, pattern recognition techniques can be exploited in order to develop DS-CDMA receivers. Another approach is to apply known equaliser structures for DS-CDMA. One proposed receiver is based on the Volterra series expansion and processes the received signal at the chip rate. Another receiver is a symbol rate radial basis function network (RBFN) receiver with reduced complexity. Subsequently, a receiver is proposed based on linear programming (LP) which is especially tailored for nonlinearly separable scenarios. The LP based receiver performance is equivalent to the known decorrelating detector in linearly separable scenarios. Finally, a hybrid receiver is proposed which combines LP and RBFN and which exploits knowledge gained from pattern recognition. This structure has lower complexity than the full RBF and good performance, and has a large potential for further improvements. Monte-Carlo simulations compare the proposed DS-CDMA receivers against established linear and nonlinear receivers. It is shown that all proposed receivers outperform the known linear receivers. The Volterra receiver’s complexity is relatively high for the performance gain achieved and might not suit practical implementation. The other receiver’s complexity was greatly reduced but it performs nearly as well as an optimum symbol by symbol detector. This thesis shows that DS-CDMA is a pattern recognition problem and that pattern recognition techniques can simplify DS-CDMA receiver structures. Knowledge is gained from the DSCDMA signal patterns which help to understand the problem of a DS-CDMA receiver. It should be noted that from the large number of known techniques, only a few pattern recognition techniques are considered in this work, and any further work should look at other techniques. Pattern recognition techniques can reduce the complexity of existing DS-CDMA receivers while maintaining performance, leading to novel receiver structures

Reliability information in channel decoding : practical aspects and information theoretical bounds

This thesis addresses the use of reliability information in channel decoding. The considered transmission systems comprise linear binary channel encoders, symmetric memoryless communication channels, and non-iterative or iterative symbol-by-symbol soft-output channel decoders. The notions of accurate and mismatched reliability values are introduced, and the measurement and improvement of the quality of reliability values are discussed. A criterion based on the Kullback-Leibler distance is proposed to assess the difference between accurate and mismatched reliability values. Accurate reliability values may be exploited to estimate transmission quality parameters, such as the bit-error probability or the symbol-wise mutual information between encoder input and decoder output. The proposed method is unbiased, does not require knowledge of the transmitted data, and has a smaller estimation variance than the conventional method. Symbol-by-symbol soft-output decoding may be interpreted as processing of mutual information. The behavior of a decoder may be characterized by information transfer functions, such as information processing characteristics (IPCs) or extrinsic information transfer (EXIT) functions. Bounds on information transfer functions are derived using the concept of bounding combined information. The resulting bounds are valid for all binary-input symmetric memoryless channels. Single parity-check codes, repetition codes, and the accumulator are addressed. Based on such bounds, decoding thresholds for low-density parity-check codes are analytically determined

Graphical model driven methods in adaptive system identification

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2016Identifying and tracking an unknown linear system from observations of its inputs and outputs is a problem at the heart of many different applications. Due to the complexity and rapid variability of modern systems, there is extensive interest in solving the problem with as little data and computation as possible. This thesis introduces the novel approach of reducing problem dimension by exploiting statistical structure on the input. By modeling the input to the system of interest as a graph-structured random process, it is shown that a large parameter identification problem can be reduced into several smaller pieces, making the overall problem considerably simpler. Algorithms that can leverage this property in order to either improve the performance or reduce the computational complexity of the estimation problem are developed. The first of these, termed the graphical expectation-maximization least squares (GEM-LS) algorithm, can utilize the reduced dimensional problems induced by the structure to improve the accuracy of the system identification problem in the low sample regime over conventional methods for linear learning with limited data, including regularized least squares methods. Next, a relaxation of the GEM-LS algorithm termed the relaxed approximate graph structured least squares (RAGS-LS) algorithm is obtained that exploits structure to perform highly efficient estimation. The RAGS-LS algorithm is then recast into a recursive framework termed the relaxed approximate graph structured recursive least squares (RAGSRLS) algorithm, which can be used to track time-varying linear systems with low complexity while achieving tracking performance comparable to much more computationally intensive methods. The performance of the algorithms developed in the thesis in applications such as channel identification, echo cancellation and adaptive equalization demonstrate that the gains admitted by the graph framework are realizable in practice. The methods have wide applicability, and in particular show promise as the estimation and adaptation algorithms for a new breed of fast, accurate underwater acoustic modems. The contributions of the thesis illustrate the power of graphical model structure in simplifying difficult learning problems, even when the target system is not directly structured.The work in this thesis was supported primarily by the Office of Naval Research through an ONR Special Research Award in Ocean Acoustics; and at various times by the National Science Foundation, the WHOI Academic Programs Office and the MIT Presidential Fellowship Program