Bit-Error-Rate-Minimizing Channel Shortening Using Post-FEQ Diversity Combining and a Genetic Algorithm

In advanced wireline or wireless communication systems, i.e., DSL, IEEE 802.11a/g, HIPERLAN/2, etc., a cyclic prefix which is proportional to the channel impulse response is needed to append a multicarrier modulation (MCM) frame for operating the MCM accurately. This prefix is used to combat inter symbol interference (ISI). In some cases, the channel impulse response can be longer than the cyclic prefix (CP). One of the most useful techniques to mitigate this problem is reuse of a Channel Shortening Equalizer (CSE) as a linear preprocessor before the MCM receiver in order to shorten the effective channel length. Channel shortening filter design is a widely examined topic in the literature. Most channel shortening equalizer proposals depend on perfect channel state information (CSI). However, this information may not be available in all situations. In cases where channel state information is not needed, blind adaptive equalization techniques are appropriate. In wireline communication systems (such as DMT), the CSE design is based on maximizing the bit rate, but in wireless systems (OFDM), there is a fixed bit loading algorithm, and the performance metric is Bit Error Rate (BER) minimization. In this work, a CSE is developed for multicarrier and single-carrier cyclic prefixed (SCCP) systems which attempts to minimize the BER. To minimize the BER, a Genetic Algorithm (GA), which is an optimization method based on the principles of natural selection and genetics, is used. If the CSI is shorter than the CP, the equalization can be done by a frequency domain equalizer (FEQ), which is a bank of complex scalars. However, in the literature the adaptive FEQ design has not been well examined. The second phase of this thesis focuses on different types of algorithms for adapting the FEQ and modifying the FEQ architecture to obtain a lower BER. Simulation results show that this modified architecture yields a 20 dB improvement in BER

Channel equalization to achieve high bit rates in discrete multitone systems

textMulticarrier modulation (MCM) techniques such as orthogonal frequency division multiplexing (OFDM) and discrete multi-tone (DMT) modulation are attractive for high-speed data communications due to the ease with which MCM can combat channel dispersion. With all the benefits MCM could give, DMT modulation has an extra ability to perform dynamic bit loading, which has the potential to exploit fully the available bandwidth in a slowly time-varying channel. In broadband wireline communications, DMT modulation is standardized for asymmetric digital subscribe line (ADSL) and very-high-bit-rate digital subscriber line (VDSL) modems. ADSL and VDSL standards are used by telephone companies to provide high speed data service to residences and offices. In an ADSL receiver, an equalizer is required to compensate for the channel’s dispersion in the time domain and the channel’s distortion in the frequency domain of the transmitted waveform. This dissertation proposes design methods for linear equalizers to increase the bit rate of the connection. The methods are amenable to implementation on programmable fixed-point digital signal processors, which are employed in ADSL/VDSL transceivers. A conventional ADSL equalizer consists of a time-domain equalizer, a fast Fourier transform, and a frequency domain equalizer. The time domain equalizer (TEQ) is a finite impulse response filter that when coupled with a discretized channel produces an equivalent channel whose impulse response is shorter than that of the discretized channel. This channel shortening is required by the ADSL standards. In this dissertation, I first propose a linear phase TEQ design that exploits symmetry in existing eigen-filter approaches such as minimum mean square error(MMSE), maximum shortening signal to noise ratio (MSSNR) and minimum intersymbol interference (Min-ISI) equalizers. TEQs with symmetric coefficients can reach the same performance as non-symmetric ones with much lower training complexity. Second, I improve Min-ISI design. I reformulate the cost function to make long TEQs design feasible. I remove the dependency of transmission delay in order to reduce the complexity associated with delay optimization. The quantized weighting is introduced to further lower the complexity. I also propose an iterative optimization procedure of Min-ISI that completely avoids Cholesky decomposition hence is better suited for a fixed-point implementation. Finally I propose a dual-path TEQ structure, which designs a standard singleFIR TEQ to achieve good bit rate over the entire transmission bandwidth, and designs another FIR TEQ to improve the bit rate over a subset of subcarriers. Dualpath TEQ can be viewed as a special case of a complex valued filter bank structure that delivers the best bit rate of existing DMT equalizers. However, dual-path TEQ provides a very good tradeoff between achievable bit rate vs. implementation complexity on a programmable digital signal processor.Electrical and Computer Engineerin

Algorithms for Blind Equalization Based on Relative Gradient and Toeplitz Constraints

Blind Equalization (BE) refers to the problem of recovering the source symbol sequence from a signal received through a channel in the presence of additive noise and channel distortion, when the channel response is unknown and a training sequence is not accessible. To achieve BE, statistical or constellation properties of the source symbols are exploited. In BE algorithms, two main concerns are convergence speed and computational complexity. In this dissertation, we explore the application of relative gradient for equalizer adaptation with a structure constraint on the equalizer matrix, for fast convergence without excessive computational complexity. We model blind equalization with symbol-rate sampling as a blind source separation (BSS) problem and study two single-carrier transmission schemes, specifically block transmission with guard intervals and continuous transmission. Under either scheme, blind equalization can be achieved using independent component analysis (ICA) algorithms with a Toeplitz or circulant constraint on the structure of the separating matrix. We also develop relative gradient versions of the widely used Bussgang-type algorithms. Processing the equalizer outputs in sliding blocks, we are able to use the relative gradient for adaptation of the Toeplitz constrained equalizer matrix. The use of relative gradient makes the Bussgang condition appear explicitly in the matrix adaptation and speeds up convergence. For the ICA-based and Bussgang-type algorithms with relative gradient and matrix structure constraints, we simplify the matrix adaptations to obtain equivalent equalizer vector adaptations for reduced computational cost. Efficient implementations with fast Fourier transform, and approximation schemes for the cross-correlation terms used in the adaptation, are shown to further reduce computational cost. We also consider the use of a relative gradient algorithm for channel shortening in orthogonal frequency division multiplexing (OFDM) systems. The redundancy of the cyclic prefix symbols is used to shorten a channel with a long impulse response. We show interesting preliminary results for a shortening algorithm based on relative gradient

Development of the Readout Electronics for the Beam Loss Monitors of the LHC

The Large Hadron Collider (LHC) of the European Laboratory for Particle Physics will be the largest particle accelerator in the world. It requires a large number of installations for its operation. One of these installations are the beam loss monitors which measure the particle losses. If these losses exceed a certain level, the beam must be extracted, otherwise the superconducting magnets could be damaged. For this reason, ionization chambers are installed outside the cryostat to transform the losses into an electric current. A wide dynamic range front end was developed to measure this current. The circuit consists of a current-to-frequency converter that works on the principle of balanced charge. Its output frequency is evaluated by counters and the data is serially transmitted from the tunnel to the surface, where the final data processing is performed. The data transmission suffers from the long cabling distance of up to 2 km. Using Manchester Code and line equalizers enables a data rate of 2 Mbit/s over a common twisted pair cable. This transmission problems lead to a detailed analysis of transmission lines in the frequency and time domain

Blind M-FSK Modulation in the ISI Channel

Channel estimation has received considerable attention over the years for its contribution to more reliable signal decoding. General wireless communication environment would cause multi-path fading for signals that propagate through them. Multi-path fading has two major effects on the system; causing inter symbol interference (ISI) and reshaping signal constellation. Estimating the channel would enable us to combat these two effects. Channel estimation can be done either blindly or with the help of training sequences. In this thesis, we propose a new blind channel estimation technique for M-FSK modulation systems. Our method can decrease the effect of signal reshaping and thus decreasing the probability of error. It also has the ability to track the channel variations in a time-variant environment. In our method, an initial estimation is assumed as the channel impulse response. Utilizing this channel, received signals are demodulated and decoded. Based on output of the demodulator, a new estimation is generated for the channel. Consequently, a new output can be produced by exploiting the new channel estimate. This process can be done iteratively $n$ times to reach the minimum possible probability of error

Blind channel identification/equalization with applications in wireless communications

Ph.DDOCTOR OF PHILOSOPH

Advanced OFDM Receivers for Underwater Acoustic Communications

In underwater acoustic (UWA) communications, an emerging research area is the high data rate and robust transmission using multi-carrier modulation, such as orthogonal frequency-division multiplexing (OFDM). However, difficulties in the OFDM communications include Doppler estimation/compensation, beamforming, and channel estimation/equalization. In this thesis, to overcome these difficulties, advanced low complexity OFDM receivers of high performance are developed. A novel low complexity Doppler estimation method based on computing multi-channel autocorrelation is proposed, which provides accurate Doppler estimates. In simulations and sea trials with guard-free OFDM signal transmission, this method outperforms conventional single-channel autocorrelation method, and shows a less complexity than the method based on computing the cross-ambiguity function between the received and pilot signals with a comparable performance. Space-time clustering in UWA channels is investigated, and a low complexity multi-antenna receiver including a beamformer that exploits this channel property is proposed. Various space-time processing techniques are investigated and compared, and the results show that the space-time clustering demonstrates the best performance. Direction of arrival (DOA) fluctuations in time-varying UWA channels are investigated, and a further developed beamforming technique with DOA tracking is proposed. In simulation and sea trials, this beamforming is compared with the beamforming without DOA tracking. The results show that the tracking beamforming demonstrates a better performance. For the channel estimation, two low complexity sparse recursive least squares adaptive filters, based on diagonal loading and homotopy, are presented. In two different UWA communication systems, the two filters are investigated and compared with various existing adaptive filters, and demonstrate better performance. For the simulations, the Waymark baseband UWA channel model is used, to simulate the virtual signal transmission in time-varying UWA channels. This model is modified from the previous computationally efficient Waymark passband model, improving the computational efficiency further