International Telemetering Conference Proceedings / October 21, 2002 / Town & Country Hotel and Conference Center, San Diego, California / To achieve good efficiency in a space-based radio transmitter, its final amplifier must be operated near the saturation point, in its nonlinear region. Because of strict band limitations, this nonlinear operation is combined with the problem of intersymbol interference. Normally, these problems are addressed using a combination of equalization and power back-off, resulting in reduced power efficiency. Many proposed receiver-based methods, such as Volterra equalization, attempt to compensate for the nonlinearity and ISI in a single block before the detector, allowing higher efficiency operation, but introducing a great deal of complexity. We propose a receiver-based method in which the two effects are dealt with in separate blocks, an equalizer and a linearizer, resulting in considerable simplification. We go further and place the detector before the linearizer, achieving improved performance by eliminating the errors introduced by the linearizer. Simulation results compare favorably with the performance of a linear AWGN channel.

International Telemetering Conference Proceedings / October 25-28, 1993 / Riviera Hotel and Convention Center, Las Vegas, Nevada / Group delay variations are a potential problem in many communication systems. This paper is slanted towards the effects of group delay variations in analog magnetic recorder/reproducer systems but the results are applicable in general. Because it is difficult to get an arbitrary group delay profile at the output of a recorder/reproducer, a method of generating arbitrary group delays for bit error probability (BEP) testing was developed. A 32-bit pattern in which all five-bit sequences appear with equal probability was selected as the test signal. The amplitude and phase of the discrete Fourier components were calculated for both non-return-to-zero-level (NRZ-L) and biphase-level (BI -L) waveforms. Filtering and group delay variations were computer generated by varying the amplitude and phase of the Fourier components. The modified signals were then programmed into an arbitrary waveform generator. Noise was added and the composite signal was applied to a bit synchronizer and bit error detector. BEPs were measured for various noise levels and group delay profiles.

Intersymbol interference (ISI) and co-channel interference (CCI) are two major obstacles to high speed data transmission in wireless cellular communications systems. Unlike thermal noise, their effects cannot be removed by increasing the signal power and are time-varying due to the relative motion between the transmitters and receivers. Space-time processing offers a signal processing framework to optimally integrate the spatial and temporal properties of the signal for maximal signal reception and at the same time, mitigate the ISI and CCI impairments. In this thesis, we focus on the development of this emerging technology to combat the undesirable effects of ISI and CCL We first develop a convenient mathematical model to parameterize the space-time multipath channel based on signal path power, directions and times of arrival. Starting from the continuous time-domain, we derive compact expressions of the vector space-time channel model that lead to the notion of block space-time manifold, Under certain identifiability conditions, the noiseless vector-channel outputs will lie on a subspace constructed from a set. of basis belonging to the block space-time manifold. This is an important observation as many high resolution array processing algorithms Can be applied directly to estimate the multi path channel parameters. Next we focus on the development of semi-blind channel identification and equalization algorithms for fast time-varying multi path channels. Specifically. we develop space-time processing algorithms for wireless TDMA networks that use short burst data formats with extremely short training data. sequences. Due to the latter, the estimated channel parameters are extremely unreliable for equalization with conventional adaptive methods. We approach the channel acquisition, tracking and equalization problems jointly, and exploit the richness of the inherent structural relationship between the channel parameters and the data sequence by repeated use of available data through a forward- backward optimization procedure. This enables the fuller exploitation of the available data. Our simulation studies show that significant performance gains are achieved over conventional methods. In the final part of this thesis, we address the problem identifying and equalizing multi path communication channels in the presence of strong CCl. By considering CCI as stochasic processes, we find that temporal diversity can be gained by observing the channel outputs from a tapped delay line. Together with the assertion that the finite alphabet property of the information sequences can offer additional information about the channel parameters and the noise-plus-covariance matrix, we develop a spatial temporal algorithm, iterative reweighting alternating minimization, to estimate the channel parameters and information sequence in a weighted least squares framework. The proposed algorithm is robust as it does not require knowledge of the number of CCI nor their structural information. Simulation studies demonstrate its efficacy over many reported methods.

In digital communication systems, several types of impairments may be introduced to the signal. These impairments result in degraded system performance; for example, high bit-error-rate or power penalty. For optical communication systems, in this thesis, these impairments are categorized into four types; that is, thermal noise, shot noise, signal-dependent noise, and intersymbol interference (ISI). By using a Gaussian approximation, effects of the first three impairments are analyzed. It is shown that signal-dependent noise introduces an error floor to the system and the bit-error-rate is considerably degraded if a nonzero-extinction ratio is applied to the system. It is shown that if the decision threshold at the decision circuit is set improperly, more received power is required to keep the bit-error-rate constant. Three main components in the system (i.e., transmitter, optical fiber, and receiver) are modeled as Butterworth filters. ISI from this model is determined by computer simulation. A high ISI is from a small system bandwidth. It is shown that a minimum power penalty can be achieved if the transmitter and receiver bandwidths are matched and fixed, and the ratio of fiber bandwidth to bit rate is 0.85. Comparing ISI from this model to ISI from raised cosine- rolloff filters, it is shown that at some particular bandwidths ISI from raised cosine-rolloff filters is much lower that that from this model. However, if the transmitter and receiver bandwidths are not matched and are not equal to these bandwidths, ISI from this model is lower than ISI from raised cosine-rolloff filters. / Master of Science

The new released 4G standard wireless communication reminds us that higher transmission data rate and more reliable service are required urgently. However, to fulfill the demand can face problems in a complex environment like mines. In this thesis, characterization of underground tunnel mines with the idea of combating intersymbol interference effect is presented.            Ray tracing simulation method is applied to characterize channel impulse response in different positions of an underground tunnel. From this channel impulse response, we can obtain how intersymbol interference affects different wireless systems. Intersymbol interference occurs due to multipath propagation of time dispersion channel.           Adaptive Equalization is the most effective way to compensate intersymbol interference. Adaptive filter adapts filter coefficients to compensate the channel so that the combination of the filter and channel offers a flat frequency response and linear phase. The bit error rate performance without using adaptive equalization is compared with using equalizer. Moreover, adaptive equalization approaches using RLS and LMS algorithms are compared with each other. The tradeoff between convergence rate, computation cost instability and ensemble averaged minimum squared errors are analyzed to determine how to select the optimum adaptive equalizer.

"In modern wireless communication systems, intersymbol interference (ISI) introduced by frequency selective fading is one of the major impairments to reliable data communication. In ISI channels, the receiver observes the superposition of multiple delayed reflections of the transmitted signal, which will result errors in the decision device. As the data rate increases, the effect of ISI becomes severe. To combat ISI, equalization is usually required for symbol detectors. The optimal maximum-likelihood sequence estimation (MLSE) based on the Viterbi algorithm (VA) may be used to estimate the transmitted sequence in the presence of the ISI. However, the computational complexity of the MLSE increases exponentially with the length of the channel impulse response (CIR). Even in channels which do not exhibit significant time dispersion, the length of the CIR will effectively increase as the sampling rate goes higher. Thus the optimal MLSE is impractical to implement in the majority of practical wireless applications. This dissertation is devoted to exploring practically implementable symbol detectors with near-optimal performance in wireless ISI channels. Particularly, we focus on the design and implementation of an iterative detector based on the belief propagation (BP) algorithm. The advantage of the BP detector is that its complexity is solely dependent on the number of nonzero coefficients in the CIR, instead of the length of the CIR. We also extend the work of BP detector design for various wireless applications. Firstly, we present a partial response BP (PRBP) symbol detector with near-optimal performance for channels which have long spanning durations but sparse multipath structure. We implement the architecture by cascading an adaptive linear equalizer (LE) with a BP detector. The channel is first partially equalized by the LE to a target impulse response (TIR) with only a few nonzero coefficients remaining. The residual ISI is then canceled by a more sophisticated BP detector. With the cascaded LE-BP structure, the symbol detector is capable to achieve a near-optimal error rate performance with acceptable implementation complexity. Moreover, we present a pipeline high-throughput implementation of the detector for channel length 30 with quadrature phase-shift keying (QPSK) modulation. The detector can achieve a maximum throughput of 206 Mb/s with an estimated core area of 3.162 mm^{2} using 90-nm technology node. At a target frequency of 515 MHz, the dynamic power is about 1.096 W. Secondly, we investigate the performance of aforementioned PRBP detector under a more generic 3G channel rather than the sparse channel. Another suboptimal partial response maximum-likelihood (PRML) detector is considered for comparison. Similar to the PRBP detector, the PRML detector also employs a hybrid two-stage scheme, in order to allow a tradeoff between performance and complexity. In simulations, we consider a slow fading environment and use the ITU-R 3G channel models. From the numerical results, it is shown that in frequency-selective fading wireless channels, the PRBP detector provides superior performance over both the traditional minimum mean squared error linear equalizer (MMSE-LE) and the PRML detector. Due to the effect of colored noise, the PRML detector in fading wireless channels is not as effective as it is in magnetic recording applications. Thirdly, we extend our work to accommodate the application of Advanced Television Systems Committee (ATSC) digital television (DTV) systems. In order to reduce error propagation caused by the traditional decision feedback equalizer (DFE) in DTV receiver, we present an adaptive decision feedback sparsening filter BP (DFSF-BP) detector, which is another form of PRBP detector. Different from the aforementioned LE-BP structure, in the DFSF-BP scheme, the BP detector is followed by a nonlinear filter called DFSF as the partial response equalizer. In the first stage, the DFSF employs a modified feedback filter which leaves the strongest post-cursor ISI taps uncorrected. As a result, a long ISI channel is equalized to a sparse channel having only a small number of nonzero taps. In the second stage, the BP detector is applied to mitigate the residual ISI. Since the channel is typically time-varying and suffers from Doppler fading, the DFSF is adapted using the least mean square (LMS) algorithm, such that the amplitude and the locations of the nonzero taps of the equalized sparse channel appear to be fixed. As such, the channel appears to be static during the second stage of equalization which consists of the BP detector. Simulation results demonstrate that the proposed scheme outperforms the traditional DFE in symbol error rate, under both static channels and dynamic ATSC channels. Finally, we study the symbol detector design for cooperative communications, which have attracted a lot of attention recently for its ability to exploit increased spatial diversity available at distributed antennas on other nodes. A system framework employing non-orthogonal amplify-and-forward half-duplex relays through ISI channels is developed. Based on the system model, we first design and implement an optimal maximum-likelihood detector based on the Viterbi algorithm. As the relay period increases, the effective CIR between the source and the destination becomes long and sparse, which makes the optimal detector impractical to implement. In order to achieve a balance between the computational complexity and performance, several sub-optimal detectors are proposed. We first present a multitrellis Viterbi algorithm (MVA) based detector which decomposes the original trellis into multiple parallel irregular sub-trellises by investigating the dependencies between the received symbols. Although MVA provides near-optimal performance, it is not straightforward to decompose the trellis for arbitrary ISI channels. Next, the decision feedback sequence estimation (DFSE) based detector and BP-based detector are proposed for cooperative ISI channels. Traditionally these two detectors are used with fixed, static channels. In our model, however, the effective channel is periodically time-varying, even when the component channels themselves are static. Consequently, we modify these two detector to account for cooperative ISI channels. Through simulations in frequency selective fading channels, we demonstrate the uncoded performance of the DFSE detector and the BP detector when compared to the optimal MLSE detector. In addition to quantifying the performance of these detectors, we also include an analysis of the implementation complexity as well as a discussion on complexity/performance tradeoffs."

The advancements of semiconductor processing technology have led to the ability for computing platforms to operate on large amounts of data at very high clock speeds. To fully utilize this processing power the components must have data continually available for operation upon and transport to other system components. To enable this data requirement, high speed serial links have replaced slower parallel communication protocols. Serial interfaces inherently require fewer signals for communication and thus reduce the device pin count, area and cost. A serial communication interface can also be run at a higher frequency because the clock skew between channels is no longer an issue since the data transmitted on various channels is independent. Serial data transmission also comes with a set of drawbacks when signal integrity is considered. The data must propagate through a channel that induces unwanted effects onto the signals such as intersymbol interference. These channel effects must be understood and mitigated to successfully transmit data without creating bit errors upon reception at the target component. Previously developed adaptive equalization techniques have been used to filter the effects of intersymbol interference from the transmitted data in the signal. This report explores the modeling and implementation of a system comprised of a transmitter, channel, and receiver to understand how intersymbol interference can be removed through a decision-feedback equalizer realized in hardware. The equalizer design, implementation, and measurements are the main focus of this report and are based on previous works in the areas of integrated circuit testing, channel modeling, and equalizer design. Simulation results from a system modeled in Simulink are compared against the results from a hardware model implemented with an FPGA, analog to digital converter and discrete circuit elements. In both the software and hardware models, bit errors were eliminated for certain amounts of intersymbol interference when a receiver with decision-feedback equalization was used instead of a receiver without equalization. / text

Optimal decision directed equalization techniques for time dispersive communication channels are often too complex to implement. This thesis considers reduced complexity decision directed equalization that lowers complexity demands yet retains close to optimal performance. The first part of this dissertation consists of three reduced complexity algorithms based on the Viterbi Algorithm (VA) which are: the Parallel Trellis VA (PTVA); Time Reverse Reduced State Sequence Estimation (TR-RSSE); and Forward-Backward State Sequence Detection (FBSSD). The second part of the thesis considers structural modifications of the Decision Feedback Equalizer (DFE), which is a special derivative of the VA, specifically, optimal vector quantization for fractionally spaced DFEs, and extended stability regions for baud spaced DFEs using passivity analysis are investigated.¶ For a special class of sparse channels the VA can be decomposed over a number of independent parallel trellises. This decomposition will be called the Parallel Trellis Viterbi Algorithm and can have lower complexity than the VA yet it retains optimal performance. By relaxing strict sparseness constraints on the channel a sub-optimal approach is proposed which keeps complexity low and obtains good performance.¶ Reduced State Sequence Estimation (RSSE) is a popular technique to reduce complexity. However, its deficiency can be the inability to adequately equalize non-minimum phase channels. For channels that have energy peaks in the tail of the impulse response (post-cursor dominant) RSSE's complexity must be close to the VA or performance will be poor. Using a property of the VA which makes it invariant to channel reversal, TR-RSSE is proposed to extend application of RSSE to post-cursor dominant channels.¶ To further extend the class of channels suitable for RSSE type processing, FBSSD is suggested. This uses a two pass processing method, and is suited to channels that have low energy pre and post-cursor. The first pass generates preliminary estimates used in the second pass to aid the decision process. FBSSD can range from RSSE to TR-RSSE depending on parameter settings.¶ The DFE is obtained when the complexity of RSSE is minimized. Two characterizing properties of the DFE, which are addressed in this thesis, are feedback and quantization. A novel fractionally spaced (FS) DFE structure is presented which allows the quantizer to be generalized relative to the quantizer used in conventional FS-DFEs. The quantizer can be designed according to a maximum a posteriori criterion which takes into account a priori statistical knowledge of error occurrences. A radically different quantizer can be obtained using this technique which can result in significant performance improvements.¶ Due to the feedback nature of the DFE a form of stability can be considered. After a decision error occurs, a stable DFE will, after some finite time and in the absence of noise, operate error free. Passivity analysis provides sufficient conditions to determine a class of channels which insures a DFE will be stable. Under conditions of short channels and small modulation alphabets, it is proposed that conventional passivity analysis can be extended to account for varying operator gains, leading to weaker sufficient conditions for stability (larger class of channels).

Advances in CMOS technology have resulted in increased clock fre-quencies, even exceeding 3GHz. At the same time, frequencies on most board wires are 125-800MHz. It is especially problematic in modern computer mem-ory buses and high speed telecommunication devices, such as switches and routers operating at 10Gb/s on its ports. It is believed that circuit board buses can be used up to about 20GHz, but there is a problem with Intersymbol Inter-ference (ISI) causing distortion of transmitted symbols by multiple reflections. Actually, the circuit board bus behaves like a passive low pass filter with unknown (perhaps changing) transfer characteristic. The problem of ISI was solved some time ago in the telecommunication area. With use of adaptive equalizers it is possible to increase throughput of a long distance communication channel dramatically. But the microprocessor bus has certain differences from telecommunica-tion devices such as modems. First of all, the clock frequency on a bus is much higher than in modems. Secondly, a bus has a much more complex structure than a telecommunication channel. At the same time, we can’t use a lot of re-sources for bus maintaining. The aim of the thesis work is to investigate the possibility of using adap-tive equalization on a bus, and the construction of a reasonable mathematical model of such an equalizer. Also limits of equalizationare examined and de-pendencies are derived.

<p>Advances in CMOS technology have resulted in increased clock fre-quencies, even exceeding 3GHz. At the same time, frequencies on most board wires are 125-800MHz. It is especially problematic in modern computer mem-ory buses and high speed telecommunication devices, such as switches and routers operating at 10Gb/s on its ports. It is believed that circuit board buses can be used up to about 20GHz, but there is a problem with Intersymbol Inter-ference (ISI) causing distortion of transmitted symbols by multiple reflections. </p><p>Actually, the circuit board bus behaves like a passive low pass filter with unknown (perhaps changing) transfer characteristic. The problem of ISI was solved some time ago in the telecommunication area. With use of adaptive equalizers it is possible to increase throughput of a long distance communication channel dramatically. </p><p>But the microprocessor bus has certain differences from telecommunica-tion devices such as modems. First of all, the clock frequency on a bus is much higher than in modems. Secondly, a bus has a much more complex structure than a telecommunication channel. At the same time, we can’t use a lot of re-sources for bus maintaining. </p><p>The aim of the thesis work is to investigate the possibility of using adap-tive equalization on a bus, and the construction of a reasonable mathematical model of such an equalizer. Also limits of equalizationare examined and de-pendencies are derived.</p>