An investigation into the performance of a power-of-two coefficient transversal equalizer in a 34Mbit/s QPSK digital radio during frequency-selective fading conditions

Bibliography: leaves 82-91.Under certain atmospheric conditions, multipath propagation can occur. The interaction of radio waves arriving at a receiver, having travelled via paths of differing length, results in the phenomenon of frequency-selective fading. This phenomenon manifests as a notch in the received spectrum and causes a severe degradation in the performance of a digital radio system. As the total power in the received bandwidth may be unaffected, the Automatic Gain Control is not able to correct for this distortion, and so other methods are required. The dissertation commences with a summary of the phenomenon of multipath as this provides the context for the investigations which follow. The adaptive equalizer was developed to combat the distortion introduced by frequency-selective fading. It achieves this by applying an estimate of the inverse of the distorting channel's transfer function. The theory on adaptive equalizers has been well established, and a summary of this theory is presented in the form of Wiener Filter theory and the Wiener-Hopf equations. An adaptive equalizer located in a 34MBit/s QPSK digital radio is required to operate at very high speed, and its digital hardware implementation is not a trivial task. In order to reduce the cost and complexity, a compromise was proposed. If the tap weights of the equalizer could be represented by power-of-two binary numbers, the equalizer circuitry can be dramatically simplified. The aim of the dissertation was to investigate the performance of this simplified equalizer structure and to determine whether a power-of-two equalizer was a viable consideration

Blind equalization

An equalizer is an adaptive filter that compensates for the non-ideal characteristics of a communication channel by processing the received signal. The adaptive algorithm searches for the inverse impulse response of the channel, and it requires knowledge of a training sequence, in order to generate an error signal necessary for the adaptive process. There are practical situations where it would be highly desirable to achieve complete adaptation without the use of a training sequence, hence the the term blind . Examples of these situations are multipoint data networks, high-capacity line-of-sight digital radio, and reflection seismology. A blind adaptive algorithm has been developed, based on simplified equalization criteria. These criteria are that the second- and fourth-order moments of the input and output sequences are equalized. The algorithm is entirely driven by statistics, only requiring knowledge of the variance of the input signal. Because of the insensitivity of higher-order statistics to Gaussian processes, the algorithm performs well when additive white Gaussian noise is present in the channel. Simulations are presented in which the new blind equalizer developed is compared to other equalization algorithms

Wireless Channel Equalization in Digital Communication Systems

Our modern society has transformed to an information-demanding system, seeking voice, video, and data in quantities that could not be imagined even a decade ago. The mobility of communicators has added more challenges. One of the new challenges is to conceive highly reliable and fast communication system unaffected by the problems caused in the multipath fading wireless channels. Our quest is to remove one of the obstacles in the way of achieving ultimately fast and reliable wireless digital communication, namely Inter-Symbol Interference (ISI), the intensity of which makes the channel noise inconsequential. The theoretical background for wireless channels modeling and adaptive signal processing are covered in first two chapters of dissertation. The approach of this thesis is not based on one methodology but several algorithms and configurations that are proposed and examined to fight the ISI problem. There are two main categories of channel equalization techniques, supervised (training) and blind unsupervised (blind) modes. We have studied the application of a new and specially modified neural network requiring very short training period for the proper channel equalization in supervised mode. The promising performance in the graphs for this network is presented in chapter 4. For blind modes two distinctive methodologies are presented and studied. Chapter 3 covers the concept of multiple cooperative algorithms for the cases of two and three cooperative algorithms. The select absolutely larger equalized signal and majority vote methods have been used in 2-and 3-algoirithm systems respectively. Many of the demonstrated results are encouraging for further research. Chapter 5 involves the application of general concept of simulated annealing in blind mode equalization. A limited strategy of constant annealing noise is experimented for testing the simple algorithms used in multiple systems. Convergence to local stationary points of the cost function in parameter space is clearly demonstrated and that justifies the use of additional noise. The capability of the adding the random noise to release the algorithm from the local traps is established in several cases

FPGA-based DOCSIS upstream demodulation

In recent years, the state-of-the-art in field programmable gate array (FPGA) technology has been advancing rapidly. Consequently, the use of FPGAs is being considered in many applications which have traditionally relied upon application-specific integrated circuits (ASICs). FPGA-based designs have a number of advantages over ASIC-based designs, including lower up-front engineering design costs, shorter time-to-market, and the ability to reconfigure devices in the field. However, ASICs have a major advantage in terms of computational resources. As a result, expensive high performance ASIC algorithms must be redesigned to fit the limited resources available in an FPGA. Concurrently, coaxial cable television and internet networks have been undergoing significant upgrades that have largely been driven by a sharp increase in the use of interactive applications. This has intensified demand for the so-called upstream channels, which allow customers to transmit data into the network. The format and protocol of the upstream channels are defined by a set of standards, known as DOCSIS 3.0, which govern the flow of data through the network. Critical to DOCSIS 3.0 compliance is the upstream demodulator, which is responsible for the physical layer reception from all customers. Although upstream demodulators have typically been implemented as ASICs, the design of an FPGA-based upstream demodulator is an intriguing possibility, as FPGA-based demodulators could potentially be upgraded in the field to support future DOCSIS standards. Furthermore, the lower non-recurring engineering costs associated with FPGA-based designs could provide an opportunity for smaller companies to compete in this market. The upstream demodulator must contain complicated synchronization circuitry to detect, measure, and correct for channel distortions. Unfortunately, many of the synchronization algorithms described in the open literature are not suitable for either upstream cable channels or FPGA implementation. In this thesis, computationally inexpensive and robust synchronization algorithms are explored. In particular, algorithms for frequency recovery and equalization are developed. The many data-aided feedforward frequency offset estimators analyzed in the literature have not considered intersymbol interference (ISI) caused by micro-reflections in the channel. It is shown in this thesis that many prominent frequency offset estimation algorithms become biased in the presence of ISI. A novel high-performance frequency offset estimator which is suitable for implementation in an FPGA is derived from first principles. Additionally, a rule is developed for predicting whether a frequency offset estimator will become biased in the presence of ISI. This rule is used to establish a channel excitation sequence which ensures the proposed frequency offset estimator is unbiased. Adaptive equalizers that compensate for the ISI take a relatively long time to converge, necessitating a lengthy training sequence. The convergence time is reduced using a two step technique to seed the equalizer. First, the ISI equivalent model of the channel is estimated in response to a specific short excitation sequence. Then, the estimated channel response is inverted with a novel algorithm to initialize the equalizer. It is shown that the proposed technique, while inexpensive to implement in an FPGA, can decrease the length of the required equalizer training sequence by up to 70 symbols. It is shown that a preamble segment consisting of repeated 11-symbol Barker sequences which is well-suited to timing recovery can also be used effectively for frequency recovery and channel estimation. By performing these three functions sequentially using a single set of preamble symbols, the overall length of the preamble may be further reduced

Improved multiple input multiple output blind equalization algorithms for medical implant communication

Medical implant sensor that is used to monitor the human physiology signals is helpful to improve the quality of life and prevent severe result from the chronic diseases. In order to achieve this, the wireless implant communication link that delivers the monitored signal to a multiple antennas external device is an essential portion. However, the existing conventional narrow band Medical Implant Communications System (MICS) has low data rate because of the bandlimited channel is allocated. To improve the data rate in the radio frequency communication, ultra-wide band technology has been proposed. However, the ultra-wide band technology is relatively new and requires living human to be the test subject in order to validate the technology performance. In this condition, the test on the new technology can rise ethical challenge. As a solution, we improve the data rate in the conventional narrow band MICS. The improvement of data rate on the narrow band implies the information bandwidth is larger than the allocated channel bandwidth, and therefore the high frequency components of the information can loss. In this case, the signal suffers the intersymbol-interference (ISI). Instead of that, the multiple antennas external device can receive the signal from other transmitting implant sensor which has the same operating frequency. As a result, the signal is further hampered by co-channel interference (CCI). To recover the signal from the ISI and CCI, multiple-input multiple output (MIMO) blind equalization that has source separation ability can be exploited. Cross-Correlation Constant Modulus Algorithm (CC-CMA) is the conventional MIMO blind equalization algorithm that can suppress ISI and CCI and able to perform source separation. However, CC-CMA has only been analyzed and simulated in the modulation of Phase Shift Keying (PSK). The performance of CC-CMA in multi-modulus modulation scheme such as 4-Pulse-amplitude modulation (PAM) and 16-Quadrature amplitude modulation (QAM), which has higher data rate than PSK, has not been analyzed. Therefore, our work is to analysis and optimize CC-CMA on the multi-modulus modulation scheme. From our analysis, we found that the cost function of CC-CMA is biased cost function. Instead of that, from our simulation, CC-CMA introduces an unexpected shrinking effect whereby the amplitudes of the equalizer outputs have been reduced, especially in multi-modulus modulation scheme. This shrinking effect is not severe in PSK because the decision of a PSK symbol is based on phase, but not amplitude. Unfortunately, this is severe in multi-modulus modulation scheme. To overcome this shrinking effect in multi-modulus modulation scheme, we propose Cross-Independent Constant Modulus Algorithm (CI-CMA). Based on the convergence analysis, we identify the new optimum dispersion value and mixing parameter in CI-CMA. From the simulation results, we confirm that CI-CMA is able to perform equalization and source separation in the multi-modulus modulation scheme. In order to improve the steady state performance of CI-CMA, we perform the steady state mean square error (MSE) analysis of CI-CMA using the energy preservation theorem that was developed by Mai and Sayed in 2001, and our result is more accurate than the previous work. From our analysis, only the reduction in adaptation step size can reduce the steady state MSE, but it is well known that the MSE is indeed a tradeoff with the speed of convergence. Therefore without sacrificing convergence speed, our last effort is to propose hybrid algorithms. The hybrid algorithms are done by combining a new adaptive constant modulus algorithm (ACMA), a decision directed algorithm and a cross-correlation function. From the simulation results, we found that the hybrid algorithms can show low steady state error and thereby improve the reliability of the communication link. The main achievement of this thesis is the discovery of new dispersion value through the convergence analysis

Mixed Norm Equalization with Applications in Television Multipath Cancellation

Electrical Engineerin

Improved multiple input multiple output blind equalization algorithms for medical implant communication

Medical implant sensor that is used to monitor the human physiology signals is helpful to improve the quality of life and prevent severe result from the chronic diseases. In order to achieve this, the wireless implant communication link that delivers the monitored signal to a multiple antennas external device is an essential portion. However, the existing conventional narrow band Medical Implant Communications System (MICS) has low data rate because of the bandlimited channel is allocated. To improve the data rate in the radio frequency communication, ultra-wide band technology has been proposed. However, the ultra-wide band technology is relatively new and requires living human to be the test subject in order to validate the technology performance. In this condition, the test on the new technology can rise ethical challenge. As a solution, we improve the data rate in the conventional narrow band MICS. The improvement of data rate on the narrow band implies the information bandwidth is larger than the allocated channel bandwidth, and therefore the high frequency components of the information can loss. In this case, the signal suffers the intersymbol-interference (ISI). Instead of that, the multiple antennas external device can receive the signal from other transmitting implant sensor which has the same operating frequency. As a result, the signal is further hampered by co-channel interference (CCI). To recover the signal from the ISI and CCI, multiple-input multiple output (MIMO) blind equalization that has source separation ability can be exploited. Cross-Correlation Constant Modulus Algorithm (CC-CMA) is the conventional MIMO blind equalization algorithm that can suppress ISI and CCI and able to perform source separation. However, CC-CMA has only been analyzed and simulated in the modulation of Phase Shift Keying (PSK). The performance of CC-CMA in multi-modulus modulation scheme such as 4-Pulse-amplitude modulation (PAM) and 16-Quadrature amplitude modulation (QAM), which has higher data rate than PSK, has not been analyzed. Therefore, our work is to analysis and optimize CC-CMA on the multi-modulus modulation scheme. From our analysis, we found that the cost function of CC-CMA is biased cost function. Instead of that, from our simulation, CC-CMA introduces an unexpected shrinking effect whereby the amplitudes of the equalizer outputs have been reduced, especially in multi-modulus modulation scheme. This shrinking effect is not severe in PSK because the decision of a PSK symbol is based on phase, but not amplitude. Unfortunately, this is severe in multi-modulus modulation scheme. To overcome this shrinking effect in multi-modulus modulation scheme, we propose Cross-Independent Constant Modulus Algorithm (CI-CMA). Based on the convergence analysis, we identify the new optimum dispersion value and mixing parameter in CI-CMA. From the simulation results, we confirm that CI-CMA is able to perform equalization and source separation in the multi-modulus modulation scheme. In order to improve the steady state performance of CI-CMA, we perform the steady state mean square error (MSE) analysis of CI-CMA using the energy preservation theorem that was developed by Mai and Sayed in 2001, and our result is more accurate than the previous work. From our analysis, only the reduction in adaptation step size can reduce the steady state MSE, but it is well known that the MSE is indeed a tradeoff with the speed of convergence. Therefore without sacrificing convergence speed, our last effort is to propose hybrid algorithms. The hybrid algorithms are done by combining a new adaptive constant modulus algorithm (ACMA), a decision directed algorithm and a cross-correlation function. From the simulation results, we found that the hybrid algorithms can show low steady state error and thereby improve the reliability of the communication link. The main achievement of this thesis is the discovery of new dispersion value through the convergence analysis