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

Estimation and detection techniques for doubly-selective channels in wireless communications

A fundamental problem in communications is the estimation of the channel. The signal transmitted through a communications channel undergoes distortions so that it is often received in an unrecognizable form at the receiver. The receiver must expend significant signal processing effort in order to be able to decode the transmit signal from this received signal. This signal processing requires knowledge of how the channel distorts the transmit signal, i.e. channel knowledge. To maintain a reliable link, the channel must be estimated and tracked by the receiver. The estimation of the channel at the receiver often proceeds by transmission of a signal called the 'pilot' which is known a priori to the receiver. The receiver forms its estimate of the transmitted signal based on how this known signal is distorted by the channel, i.e. it estimates the channel from the received signal and the pilot. This design of the pilot is a function of the modulation, the type of training and the channel. [Continues.

Partial update blind adaptive channel shortening algorithms for wireline multicarrier systems

In wireline multicarrier systems a cyclic prefix is generally used to facilitate simple channel equalization at the receiver. The choice of the length of the cyclic prefix is a trade-off between maximizing the length of the channel for which inter-symbol interference is eliminated and optimizing the transmission efficiency. When the length of the channel is greater than the cyclic prefix, adaptive channel shorteners can be used to force the effective channel length of the combined channel and channel shortener to be within the cyclic prefix constraint. The focus of this thesis is the design of new blind adaptive time-domain channel shortening algorithms with good convergence properties and low computational complexity. An overview of the previous work in the field of supervised partial update adaptive filtering is given. The concept of property-restoral based blind channel shortening algorithms is then introduced together with the main techniques within this class of adaptive filters. Two new partial update blind (unsupervised) adaptive channel shortening algorithms are therefore introduced with robustness to impulsive noise commonly present in wireline multicarrier systems. Two further blind channel shortening algorithms are proposed in which the set of coefficients which is updated at each iteration of the algorithm is chosen deterministically. One of which, the partial up-date single lag autocorrelation maximization (PUSLAM) algorithm is particularly attractive due to its low computational complexity. The interaction between the receiver matched filter and the channel shortener is considered in the context of a multi-input single-output environment. To mitigate the possibility of ill-convergence with the PUSLAM algorithm an entirely new random PUSLAM (RPUSLAM) algorithm is proposed in which randomness is introduced both into the lag selection of the cost function underlying SLAM and the selection of the particular set of coefficients updated at each algorithm. This algorithm benefits from robust convergence properties whilst retaining relatively low computational complexity. All algorithms developed within the thesis are supported by evaluation on a set of eight carrier serving area test loop channels.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Partial update blind adaptive channel shortening algorithms for wireline multicarrier systems.

In wireline multicarrier systems a cyclic prefix is generally used to facilitate simple channel equalization at the receiver. The choice of the length of the cyclic prefix is a trade-off between maximizing the length of the channel for which inter-symbol interference is eliminated and optimizing the transmission efficiency. When the length of the channel is greater than the cyclic prefix, adaptive channel shorteners can be used to force the effective channel length of the combined channel and channel shortener to be within the cyclic prefix constraint. The focus of this thesis is the design of new blind adaptive time-domain channel shortening algorithms with good convergence properties and low computational complexity. An overview of the previous work in the field of supervised partial update adaptive filtering is given. The concept of property-restoral based blind channel shortening algorithms is then introduced together with the main techniques within this class of adaptive filters. Two new partial update blind (unsupervised) adaptive channel shortening algorithms are therefore introduced with robustness to impulsive noise commonly present in wireline multicarrier systems. Two further blind channel shortening algorithms are proposed in which the set of coefficients which is updated at each iteration of the algorithm is chosen deterministically. One of which, the partial up-date single lag autocorrelation maximization (PUSLAM) algorithm is particularly attractive due to its low computational complexity. The interaction between the receiver matched filter and the channel shortener is considered in the context of a multi-input single-output environment. To mitigate the possibility of ill-convergence with the PUSLAM algorithm an entirely new random PUSLAM (RPUSLAM) algorithm is proposed in which randomness is introduced both into the lag selection of the cost function underlying SLAM and the selection of the particular set of coefficients updated at each algorithm. This algorithm benefits from robust convergence properties whilst retaining relatively low computational complexity. All algorithms developed within the thesis are supported by evaluation on a set of eight carrier serving area test loop channels

Advanced receiver structures for mobile MIMO multicarrier communication systems

Beyond third generation (3G) and fourth generation (4G) wireless communication systems are targeting far higher data rates, spectral efficiency and mobility requirements than existing 3G networks. By using multiple antennas at the transmitter and the receiver, multiple-input multiple-output (MIMO) technology allows improving both the spectral efficiency (bits/s/Hz), the coverage, and link reliability of the system. Multicarrier modulation such as orthogonal frequency division multiplexing (OFDM) is a powerful technique to handle impairments specific to the wireless radio channel. The combination of multicarrier modulation together with MIMO signaling provides a feasible physical layer technology for future beyond 3G and fourth generation communication systems. The theoretical benefits of MIMO and multicarrier modulation may not be fully achieved because the wireless transmission channels are time and frequency selective. Also, high data rates call for a large bandwidth and high carrier frequencies. As a result, an important Doppler spread is likely to be experienced, leading to variations of the channel over very short period of time. At the same time, transceiver front-end imperfections, mobility and rich scattering environments cause frequency synchronization errors. Unlike their single-carrier counterparts, multi-carrier transmissions are extremely sensitive to carrier frequency offsets (CFO). Therefore, reliable channel estimation and frequency synchronization are necessary to obtain the benefits of MIMO OFDM in mobile systems. These two topics are the main research problems in this thesis. An algorithm for the joint estimation and tracking of channel and CFO parameters in MIMO OFDM is developed in this thesis. A specific state-space model is introduced for MIMO OFDM systems impaired by multiple carrier frequency offsets under time-frequency selective fading. In MIMO systems, multiple frequency offsets are justified by mobility, rich scattering environment and large angle spread, as well as potentially separate radio frequency - intermediate frequency chains. An extended Kalman filter stage tracks channel and CFO parameters. Tracking takes place in time domain, which ensures reduced computational complexity, robustness to estimation errors as well as low estimation variance in comparison to frequency domain processing. The thesis also addresses the problem of blind carrier frequency synchronization in OFDM. Blind techniques exploit statistical or structural properties of the OFDM modulation. Two novel approaches are proposed for blind fine CFO estimation. The first one aims at restoring the orthogonality of the OFDM transmission by exploiting the properties of the received signal covariance matrix. The second approach is a subspace algorithm exploiting the correlation of the channel frequency response among the subcarriers. Both methods achieve reliable estimation of the CFO regardless of multipath fading. The subspace algorithm needs extremely small sample support, which is a key feature in the face of time-selective channels. Finally, the Cramér-Rao (CRB) bound is established for the problem in order to assess the large sample performance of the proposed algorithms.reviewe

Timing and Carrier Synchronization in Wireless Communication Systems: A Survey and Classification of Research in the Last 5 Years

Timing and carrier synchronization is a fundamental requirement for any wireless communication system to work properly. Timing synchronization is the process by which a receiver node determines the correct instants of time at which to sample the incoming signal. Carrier synchronization is the process by which a receiver adapts the frequency and phase of its local carrier oscillator with those of the received signal. In this paper, we survey the literature over the last 5 years (2010–2014) and present a comprehensive literature review and classification of the recent research progress in achieving timing and carrier synchronization in single-input single-output (SISO), multiple-input multiple-output (MIMO), cooperative relaying, and multiuser/multicell interference networks. Considering both single-carrier and multi-carrier communication systems, we survey and categorize the timing and carrier synchronization techniques proposed for the different communication systems focusing on the system model assumptions for synchronization, the synchronization challenges, and the state-of-the-art synchronization solutions and their limitations. Finally, we envision some future research directions

Distributed Quasi-Orthogonal Space-Time coding in wireless cooperative relay networks

Cooperative diversity provides a new paradigm in robust wireless re- lay networks that leverages Space-Time (ST) processing techniques to combat the effects of fading. Distributing the encoding over multiple relays that potentially observe uncorrelated channels to a destination terminal has demonstrated promising results in extending range, data- rates and transmit power utilization. Specifically, Space Time Block Codes (STBCs) based on orthogonal designs have proven extremely popular at exploiting spatial diversity through simple distributed pro- cessing without channel knowledge at the relaying terminals. This thesis aims at extending further the extensive design and analysis in relay networks based on orthogonal designs in the context of Quasi- Orthogonal Space Time Block Codes (QOSTBCs). The characterization of Quasi-Orthogonal MIMO channels for cooper- ative networks is performed under Ergodic and Non-Ergodic channel conditions. Specific to cooperative diversity, the sub-channels are as- sumed to observe different shadowing conditions as opposed to the traditional co-located communication system. Under Ergodic chan- nel assumptions novel closed-form solutions for cooperative channel capacity under the constraint of distributed-QOSTBC processing are presented. This analysis is extended to yield closed-form approx- imate expressions and their utility is verified through simulations. The effective use of partial feedback to orthogonalize the QOSTBC is examined and significant gains under specific channel conditions are demonstrated. Distributed systems cooperating over the network introduce chal- lenges in synchronization. Without extensive network management it is difficult to synchronize all the nodes participating in the relaying between source and destination terminals. Based on QOSTBC tech- niques simple encoding strategies are introduced that provide compa- rable throughput to schemes under synchronous conditions with neg- ligible overhead in processing throughout the protocol. Both mutli- carrier and single-carrier schemes are developed to enable the flexi- bility to limit Peak-to-Average-Power-Ratio (PAPR) and reduce the Radio Frequency (RF) requirements of the relaying terminals. The insights gained in asynchronous design in flat-fading cooperative channels are then extended to broadband networks over frequency- selective channels where the novel application of QOSTBCs are used in distributed-Space-Time-Frequency (STF) coding. Specifically, cod- ing schemes are presented that extract both spatial and mutli-path diversity offered by the cooperative Multiple-Input Multiple-Output (MIMO) channel. To provide maximum flexibility the proposed schemes are adapted to facilitate both Decode-and-Forward (DF) and Amplify- and-Forward (AF) relaying. In-depth Pairwise-Error-Probability (PEP) analysis provides distinct design specifications which tailor the distributed- STF code to maximize the diversity and coding gain offered under the DF and AF protocols. Numerical simulation are used extensively to confirm the validity of the proposed cooperative schemes. The analytical and numerical re- sults demonstrate the effective use of QOSTBC over orthogonal tech- niques in a wide range of channel conditions

Minimum-mean-output-energy blind adaptive channel shortening for multicarrier SIMO transceivers

In this paper, we propose a blind adaptive channel shortening method for designing finite-impulse response time-domain equalizers (TEQs) in single-input multiple-output (SIMO) systems employing multicarrier modulations. The proposed algorithm, which relies on a constrained minimization of the mean-output-energy at the TEQ output, does not require neither a priori knowledge of the channel impulse response nor transmission of training sequences, and admits an effective and computationally-efficient adaptive implementation. Moreover, the proposed TEQ is narrowband-interference resistant and its synthesis only requires an upper bound (rather than the exact knowledge) of the channel order. Numerical simulations are provided to illustrate the advantages of the proposed technique over a recently developed blind channel shortener