Spatio-Temporal processing for Optimum Uplink-Downlink WCDMA Systems

The capacity of a cellular system is limited by two different phenomena, namely multipath fading and multiple access interference (MAl). A Two Dimensional (2-D) receiver combats both of these by processing the signal both in the spatial and temporal domain. An ideal 2-D receiver would perform joint space-time processing, but at the price of high computational complexity. In this research we investigate computationally simpler technique termed as a Beamfom1er-Rake. In a Beamformer-Rake, the output of a beamfom1er is fed into a succeeding temporal processor to take advantage of both the beamformer and Rake receiver. Wireless service providers throughout the world are working to introduce the third generation (3G) and beyond (3G) cellular service that will provide higher data rates and better spectral efficiency. Wideband COMA (WCDMA) has been widely accepted as one of the air interfaces for 3G. A Beamformer-Rake receiver can be an effective solution to provide the receivers enhanced capabilities needed to achieve the required performance of a WCDMA system. We consider three different Pilot Symbol Assisted (PSA) beamforming techniques, Direct Matrix Inversion (DMI), Least-Mean Square (LMS) and Recursive Least Square (RLS) adaptive algorithms. Geometrically Based Single Bounce (GBSB) statistical Circular channel model is considered, which is more suitable for array processing, and conductive to RAKE combining. The performances of the Beam former-Rake receiver are evaluated in this channel model as a function of the number of antenna elements and RAKE fingers, in which are evaluated for the uplink WCDMA system. It is shown that, the Beamformer-Rake receiver outperforms the conventional RAKE receiver and the conventional beamformer by a significant margin. Also, we optimize and develop a mathematical formulation for the output Signal to Interference plus Noise Ratio (SINR) of a Beam former-Rake receiver. In this research, also, we develop, simulate and evaluate the SINR and Signal to Noise Ratio (Et!Nol performances of an adaptive beamforming technique in the WCDMA system for downlink. The performance is then compared with an omnidirectional antenna system. Simulation shows that the best perfom1ance can be achieved when all the mobiles with same Angle-of-Arrival (AOA) and different distance from base station are formed in one beam

Blind identification of acoustic systems and enhancement of reverberant speech

Imperial Users onl

Efficient channel equalization algorithms for multicarrier communication systems

Blind adaptive algorithm that updates time-domain equalizer (TEQ) coefficients by Adjacent Lag Auto-correlation Minimization (ALAM) is proposed to shorten the channel for multicarrier modulation (MCM) systems. ALAM is an addition to the family of several existing correlation based algorithms that can achieve similar or better performance to existing algorithms with lower complexity. This is achieved by designing a cost function without the sum-square and utilizing symmetrical-TEQ property to reduce the complexity of adaptation of TEQ to half of the existing one. Furthermore, to avoid the limitations of lower unstable bit rate and high complexity, an adaptive TEQ using equal-taps constraints (ETC) is introduced to maximize the bit rate with the lowest complexity. An IP core is developed for the low-complexity ALAM (LALAM) algorithm to be implemented on an FPGA. This implementation is extended to include the implementation of the moving average (MA) estimate for the ALAM algorithm referred as ALAM-MA. Unit-tap constraint (UTC) is used instead of unit-norm constraint (UNC) while updating the adaptive algorithm to avoid all zero solution for the TEQ taps. The IP core is implemented on Xilinx Vertix II Pro XC2VP7-FF672-5 for ADSL receivers and the gate level simulation guaranteed successful operation at a maximum frequency of 27 MHz and 38 MHz for ALAM-MA and LALAM algorithm, respectively. FEQ equalizer is used, after channel shortening using TEQ, to recover distorted QAM signals due to channel effects. A new analytical learning based framework is proposed to jointly solve equalization and symbol detection problems in orthogonal frequency division multiplexing (OFDM) systems with QAM signals. The framework utilizes extreme learning machine (ELM) to achieve fast training, high performance, and low error rates. The proposed framework performs in real-domain by transforming a complex signal into a single 2–tuple real-valued vector. Such transformation offers equalization in real domain with minimum computational load and high accuracy. Simulation results show that the proposed framework outperforms other learning based equalizers in terms of symbol error rates and training speeds

Spontaneous and explicit estimation of time delays in the absence/presence of multipath propagation.

by Hing-cheung So.Thesis (Ph.D.)--Chinese University of Hong Kong, 1995.Includes bibliographical references (leaves 133-141).Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Time Delay Estimation (TDE) and its Applications --- p.1Chapter 1.2 --- Goal of the Work --- p.6Chapter 1.3 --- Thesis Outline --- p.9Chapter 2 --- Adaptive Methods for TDE --- p.10Chapter 2.1 --- Problem Description --- p.11Chapter 2.2 --- The Least Mean Square Time Delay Estimator (LMSTDE) --- p.11Chapter 2.2.1 --- Bias and Variance --- p.14Chapter 2.2.2 --- Probability of Occurrence of False Peak Weight --- p.16Chapter 2.2.3 --- Some Modifications of the LMSTDE --- p.17Chapter 2.3 --- The Adaptive Digital Delay-Lock Discriminator (ADDLD) --- p.18Chapter 2.4 --- Summary --- p.20Chapter 3 --- The Explicit Time Delay Estimator (ETDE) --- p.22Chapter 3.1 --- Derivation and Analysis of the ETDE --- p.23Chapter 3.1.1 --- The ETDE system --- p.23Chapter 3.1.2 --- Performance Surface --- p.26Chapter 3.1.3 --- Static Behaviour --- p.28Chapter 3.1.4 --- Dynamic Behaviour --- p.30Chapter 3.2 --- Performance Comparisons --- p.32Chapter 3.2.1 --- With the LMSTDE --- p.32Chapter 3.2.2 --- With the CATDE --- p.34Chapter 3.2.3 --- With the CRLB --- p.35Chapter 3.3 --- Simulation Results --- p.38Chapter 3.3.1 --- Corroboration of the ETDE Performance --- p.38Chapter 3.3.2 --- Comparative Studies --- p.44Chapter 3.4 --- Summary --- p.48Chapter 4 --- An Improvement to the ETDE --- p.49Chapter 4.1 --- Delay Modeling Error of the ETDE --- p.49Chapter 4.2 --- The Explicit Time Delay and Gain Estimator (ETDGE) --- p.52Chapter 4.3 --- Performance Analysis --- p.55Chapter 4.4 --- Simulation Results --- p.57Chapter 4.5 --- Summary --- p.61Chapter 5 --- TDE in the Presence of Multipath Propagation --- p.62Chapter 5.1 --- The Multipath TDE problem --- p.63Chapter 5.2 --- TDE with Multipath Cancellation (MCTDE) --- p.64Chapter 5.2.1 --- Structure and Algorithm --- p.64Chapter 5.2.2 --- Convergence Dynamics --- p.67Chapter 5.2.3 --- The Generalized Multipath Cancellator --- p.70Chapter 5.2.4 --- Effects of Additive Noises --- p.73Chapter 5.2.5 --- Simulation Results --- p.74Chapter 5.3 --- TDE with Multipath Equalization (METDE) --- p.86Chapter 5.3.1 --- The Two-Step Algorithm --- p.86Chapter 5.3.2 --- Performance of the METDE --- p.89Chapter 5.3.3 --- Simulation Results --- p.93Chapter 5.4 --- Summary --- p.101Chapter 6 --- Conclusions and Suggestions for Future Research --- p.102Chapter 6.1 --- Conclusions --- p.102Chapter 6.2 --- Suggestions for Future Research --- p.104Appendices --- p.106Chapter A --- Derivation of (3.20) --- p.106Chapter B --- Derivation of (3.29) --- p.110Chapter C --- Derivation of (4.14) --- p.111Chapter D --- Derivation of (4.15) --- p.113Chapter E --- Derivation of (5.21) --- p.115Chapter F --- Proof of unstablity of A°(z) --- p.116Chapter G --- Derivation of (5.34)-(5.35) --- p.118Chapter H --- Derivation of variance of αs11(k) and Δs11(k) --- p.120Chapter I --- Derivation of (5.40) --- p.123Chapter J --- Derivation of time constant of αΔ11(k) --- p.124Chapter K --- Derivation of (5.63)-(5.66) --- p.125Chapter L --- Derivation of (5.68)-(5.72) --- p.129References --- p.13

UNDERWATER COMMUNICATIONS WITH ACOUSTIC STEGANOGRAPHY: RECOVERY ANALYSIS AND MODELING

In the modern warfare environment, communication is a cornerstone of combat competence. However, the increasing threat of communications-denied environments highlights the need for communications systems with low probability of intercept and detection. This is doubly true in the subsurface environment, where communications and sonar systems can reveal the tactical location of platforms and capabilities, subverting their covert mission set. A steganographic communication scheme that leverages existing technologies and unexpected data carriers is a feasible means of increasing assurance of communications, even in denied environments. This research works toward a covert communication system by determining and comparing novel symbol recovery schemes to extract data from a signal transmitted under a steganographic technique and interfered with by a simulated underwater acoustic channel. We apply techniques for reliably extracting imperceptible information from unremarkable acoustic events robust to the variability of the hostile operating environment. The system is evaluated based on performance metrics, such as transmission rate and bit error rate, and we show that our scheme is sufficient to conduct covert communications through acoustic transmissions, though we do not solve the problems of synchronization or equalization.Lieutenant, United States NavyApproved for public release. Distribution is unlimited

Spatio-Temporal processing for Optimum Uplink-Downlink WCDMA Systems

The capacity of a cellular system is limited by two different phenomena, namely multipath fading and multiple access interference (MAl). A Two Dimensional (2-D) receiver combats both of these by processing the signal both in the spatial and temporal domain. An ideal 2-D receiver would perform joint space-time processing, but at the price of high computational complexity. In this research we investigate computationally simpler technique termed as a Beamfom1er-Rake. In a Beamformer-Rake, the output of a beamfom1er is fed into a succeeding temporal processor to take advantage of both the beamformer and Rake receiver. Wireless service providers throughout the world are working to introduce the third generation (3G) and beyond (3G) cellular service that will provide higher data rates and better spectral efficiency. Wideband COMA (WCDMA) has been widely accepted as one of the air interfaces for 3G. A Beamformer-Rake receiver can be an effective solution to provide the receivers enhanced capabilities needed to achieve the required performance of a WCDMA system. We consider three different Pilot Symbol Assisted (PSA) beamforming techniques, Direct Matrix Inversion (DMI), Least-Mean Square (LMS) and Recursive Least Square (RLS) adaptive algorithms. Geometrically Based Single Bounce (GBSB) statistical Circular channel model is considered, which is more suitable for array processing, and conductive to RAKE combining. The performances of the Beam former-Rake receiver are evaluated in this channel model as a function of the number of antenna elements and RAKE fingers, in which are evaluated for the uplink WCDMA system. It is shown that, the Beamformer-Rake receiver outperforms the conventional RAKE receiver and the conventional beamformer by a significant margin. Also, we optimize and develop a mathematical formulation for the output Signal to Interference plus Noise Ratio (SINR) of a Beam former-Rake receiver. In this research, also, we develop, simulate and evaluate the SINR and Signal to Noise Ratio (Et!Nol performances of an adaptive beamforming technique in the WCDMA system for downlink. The performance is then compared with an omnidirectional antenna system. Simulation shows that the best perfom1ance can be achieved when all the mobiles with same Angle-of-Arrival (AOA) and different distance from base station are formed in one beam