Artificial neural networks for location estimation and co-cannel interference suppression in cellular networks

This thesis reports on the application of artificial neural networks to two important problems encountered in cellular communications, namely, location estimation and co-channel interference suppression. The prediction of a mobile location using propagation path loss (signal strength) is a very difficult and complex task. Several techniques have been proposed recently mostly based on linearized, geometrical and maximum likelihood methods. An alternative approach based on artificial neural networks is proposed in this thesis which offers the advantages of increased flexibility to adapt to different environments and high speed parallel processing. Location estimation provides users of cellular telephones with information about their location. Some of the existing location estimation techniques such as those used in GPS satellite navigation systems require non-standard features, either from the cellular phone or the cellular network. However, it is possible to use the existing GSM technology for location estimation by taking advantage of the signals transmitted between the phone and the network. This thesis proposes the application of neural networks to predict the location coordinates from signal strength data. New multi-layered perceptron and radial basis function based neural networks are employed for the prediction of mobile locations using signal strength measurements in a simulated COST-231 metropolitan environment. In addition, initial preliminary results using limited available real signal-strength measurements in a metropolitan environment are also reported comparing the performance of the neural predictors with a conventional linear technique. The results indicate that the neural predictors can be trained to provide a near perfect mapping using signal strength measurements from two or more base stations. The second application of neural networks addressed in this thesis, is concerned with adaptive equalization, which is known to be an important technique for combating distortion and Inter-Symbol Interference (ISI) in digital communication channels. However, many communication systems are also impaired by what is known as co-channel interference (CCI). Many digital communications systems such as digital cellular radio (DCR) and dual polarized micro-wave radio, for example, employ frequency re-usage and often exhibit performance limitation due to co-channel interference. The degradation in performance due to CCI is more severe than due to ISI. Therefore, simple and effective interference suppression techniques are required to mitigate the interference for a high-quality signal reception. The current work briefly reviews the application of neural network based non-linear adaptive equalizers to the problem of combating co-channel interference, without a priori knowledge of the channel or co-channel orders. A realistic co-channel system is used as a case study to demonstrate the superior equalization capability of the functional-link neural network based Decision Feedback Equalizer (DFE) compared to other conventional linear and neural network based non-linear adaptive equalizers.This project was funded by Solectron (Scotland) Ltd

Proceedings of the Fall 1995 Advanced Digital Communication Systems

Coordinated Science Laboratory was formerly known as Control Systems Laborator

Reduced Receivers for Faster-than-Nyquist Signaling and General Linear Channels

Fast and reliable data transmission together with high bandwidth efficiency are important design aspects in a modern digital communication system. Many different approaches exist but in this thesis bandwidth efficiency is obtained by increasing the data transmission rate with the faster-than-Nyquist (FTN) framework while keeping a fixed power spectral density (PSD). In FTN consecutive information carrying symbols can overlap in time and in that way introduce a controlled amount of intentional intersymbol interference (ISI). This technique was introduced already in 1975 by Mazo and has since then been extended in many directions. Since the ISI stemming from practical FTN signaling can be of significant duration, optimum detection with traditional methods is often prohibitively complex, and alternative equalization methods with acceptable complexity-performance tradeoffs are needed. The key objective of this thesis is therefore to design reduced-complexity receivers for FTN and general linear channels that achieve optimal or near-optimal performance. Although the performance of a detector can be measured by several means, this thesis is restricted to bit error rate (BER) and mutual information results. FTN signaling is applied in two ways: As a separate uncoded narrowband communication system or in a coded scenario consisting of a convolutional encoder, interleaver and the inner ISI mechanism in serial concatenation. Turbo equalization where soft information in the form of log likelihood ratios (LLRs) is exchanged between the equalizer and the decoder is a commonly used decoding technique for coded FTN signals. The first part of the thesis considers receivers and arising stability problems when working within the white noise constraint. New M-BCJR algorithms for turbo equalization are proposed and compared to reduced-trellis VA and BCJR benchmarks based on an offset label idea. By adding a third low-complexity M-BCJR recursion, LLR quality is improved for practical values of M. M here measures the reduced number of BCJR computations for each data symbol. An improvement of the minimum phase conversion that sharpens the focus of the ISI model energy is proposed. When combined with a delayed and slightly mismatched receiver, the decoding allows a smaller M without significant loss in BER. The second part analyzes the effect of the internal metric calculations on the performance of Forney- and Ungerboeck-based reduced-complexity equalizers of the M-algorithm type for both ISI and multiple-input multiple-output (MIMO) channels. Even though the final output of a full-complexity equalizer is identical for both models, the internal metric calculations are in general different. Hence, suboptimum methods need not produce the same final output. Additionally, new models working in between the two extremes are proposed and evaluated. Note that the choice of observation model does not impact the detection complexity as the underlying algorithm is unaltered. The last part of the thesis is devoted to a different complexity reducing approach. Optimal channel shortening detectors for linear channels are optimized from an information theoretical perspective. The achievable information rates of the shortened models as well as closed form expressions for all components of the optimal detector of the class are derived. The framework used in this thesis is more general than what has been previously used within the area

Design and analysis of short word length DSP systems for mobile communication

Recently, many general purpose DSP applications such as Least Mean Squares-Like single-bit adaptive filter algorithms have been developed using the Short Word Length (SWL) technique and have been shown to achieve similar performance as multi-bit systems. A key function in SWL systems is sigma delta modulation (ΣΔM) that operates at an over sampling ratio (OSR), in contrast to the Nyquist rate sampling typically used in conventional multi-bit systems. To date, the analysis of SWL (or single-bit) DSP systems has tended to be performed using high-level tools such as MATLAB, with little work reported relating to their hardware implementation, particularly in Field Programmable Gate Arrays (FPGAs). This thesis explores the hardware implementation of single-bit systems in FPGA using the design and implementation in VHDL of a single-bit ternary FIR-like filter as an illustrative example. The impact of varying OSR and bit-width of the SWL filter has been determined, and a comparison undertaken between the area-performance-power characteristics of the SWL FIR filter compared to its equivalent multi-bit filter. In these experiments, it was found that single-bit FIR-like filter consistently outperforms the multi-bit technique in terms of its area, performance and power except at the highest filter orders analysed in this work. At higher orders, the ΣΔ approach retains its power and performance advantages but exhibits slightly higher chip area. In the second stage of thesis, three encoding techniques called canonical signed digit (CSD), 2’s complement, and Redundant Binary Signed Digit (RBSD) were designed and investigated on the basis of area-performance in FPGA at varying OSR. Simulation results show that CSD encoding technique does not offer any significant improvement as compared to 2’s complement as in multi-bit domain. Whereas, RBSD occupies double the chip area than other two techniques and has poor performance. The stability of the single-bit FIR-like filter mainly depends upon IIR remodulator due to its recursive nature. Thus, we have investigated the stability IIR remodulator and propose a new model using linear analysis and root locus approach that takes into account the widely accepted second order sigma-delta modulator state variable upper bounds. Using proposed model we have found new feedback parameters limits that is a key parameter in single-bit IIR remodulator stability analysis. Further, an analysis of single-bit adaptive channel equalization in MATLAB has been performed, which is intended to support the design and development of efficient algorithm for single-bit channel equalization. A new mathematical model has been derived with all inputs, coefficients and outputs in single-bit domain. The model was simulated using narrowband signals in MATLAB and investigated on the basis of symbol error rate (SER), signal-to-noise ratio (SNR) and minimum mean squared error (MMSE). The results indicate that single-bit adaptive channel equalization is achievable with narrowband signals but that the harsh quantization noise has great impact in the convergence

Adaptive equalizers for multipath compensation in digital microwave communications

SIGLEAvailable from British Library Document Supply Centre- DSC:D82998 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Physical layer network coding based communication systems in frequency selective channels

PhD ThesisThe demand for wireless communications is growing every day which requiresmore speed and bandwidth. In two way relay networks (TWRN), physical layer network coding (PLNC) was proposed to double the bandwidth. A TWRN is a system where two end users exchange data through a middle node called the relay. The two signals are allowed to be physically added before being broadcasted back to the end users. This system can work smoothly in flat fading channels, but can not be applied straightforward in frequency selective channels. In a multipath multi-tap FIR channel, the inter-symbol interference (ISI) spreads through several symbols. In this case, the symbols at the relay are not just an addition of the sent symbols but also some of the previous symbols from both sides. This not only causes a traditional PLNC to fail but also a simple one equalizer system will not solve the problem. Three main methods have been proposed by other researchers. The OFDM based PLNC is the simplest in terms of implementation and complexity but suffers from the disadvantages of the OFDMlike cyclic prefix overhead and frequency offset. The main disadvantage, however is the relatively low BER performance because it is restricted to linear equalizers in the PLNC system. Another approach is pre-filtering or pre-equalization. This method also has some disadvantages like complexity, sensitivity to channel variation and the need of a feedback channel for both end nodes. Finally, the maximum likelihood sequence detector was also proposed but is restricted to BPSK modulation and exponentially rising complexity are major drawbacks. The philosophy in this work is to avoid these disadvantages by using a time domain based system. The DFE is the equalizer of choice here because it provides a non-trivial BER performance improvement with very little increase in complexity. In this thesis, the problem of frequency selective channels in PLNC systems can be solved by properly adjusting the design of the system including the DFE. The other option is to redesign the equalizer to meet that goal. An AF DFE system is proposed in this work that provides very low complexity especially at the relay with little sensitivity to channel changes. A multi-antenna DNF DFE system is also proposed here with an improved performance. Finally, a new equalizer is designed for very low complexity and cost DNF approach with little sacrifice of BER performance. Matlab was used for the simulations with Monte Carlo method to verify the findings of this work through finding the BER performance of each system. This thesis opens the door for future improvement on the PLNC system. More research needs to be done like testing the proposed systems in real practical implementation and also the effect of adding channel coding to these systems.Iraqi Government, Ministry of Higher Educatio

Interference cancellation for shot-code DS-CDMA in the presence of channel fading

Interference from other adjacent users in wireless applications is a major problem in direct-sequence code-division multiple-access (DS-CDMA). This is also known as the near-far problem where a strong signal from one user interferes with other users. The current approach to deal with the near-far problem in DS-CDMA systems is to use strict transmitter power control. An alternative approach is to use near-far resistant receivers. The practical near-far resistance receiver structure is the adaptive decorrelating detectors since it avoids complex matrix inversion. The existing CDMA standard known as IS-95 uses a long signature code sequence. However for simplicity, the adaptive multi-user receiver uses short signature code sequence. The problem is that adaptive receivers lose near-far resistance as the number of users increases in the system. This thesis describes a novel method of multistage decision feedback cancellation (DFC) scheme immune from the near-far problem. The performance of the new DFC structure is constructed using three different adaptive algorithms: the least mean squared (LMS), the recursive least squared (RLS) and the linearly constraint constant modulus (LCCM) adaptive algorithms. It is found that LMS adaptive algorithm provides the best result considering its simple hardware complexity. It is also found that the LMS adaptive receiver along with the DFC structure provides a better bit synchronization capability to the over all system. Since the receiver is near-far resistant, the LMS adaptive receiver along with the decision feedback cancellation structure also performs better in the presence of Rayleigh fading

Investigation of coding and equalization for the digital HDTV terrestrial broadcast channel

Includes bibliographical references (p. 241-248).Supported by the Advanced Telecommunications Research Program.Julien J. Nicolas