Decision Directed Channel Estimation Aided OFDM Employing Sample-Spaced and Fractionally-Spaced CIR Estimators

Abstract—In this letter we characterize the substantial difference between two channel estimation approaches, namely the sample-spaced (SS) and the fractionally-spaced (FS) channel impulse response (CIR) estimators. The achievable performance of decision-directed channel estimation (DDCE) methods employing both the SS- and the FS-CIR estimators is analyzed in the context of an OFDM system. The performance of the two estimation methods is compared and it is shown that the DDCE scheme employing the Projection Approximation Subspace Tracking (PAST)-aided FS-CIR estimator outperforms its SS-CIR estimator-based counterpart. Index Terms—Multiuser OFDM, decision directed channel estimation, impulse response estimation SDMA

Channel estimation for SISO and MIMO OFDM communications systems.

Thesis (Ph.D.)-University of KwaZulu-Natal, Durban, 2010.Telecommunications in the current information age is increasingly relying on the wireless link. This is because wireless communication has made possible a variety of services ranging from voice to data and now to multimedia. Consequently, demand for new wireless capacity is growing rapidly at a very alarming rate. In a bid to cope with challenges of increasing demand for higher data rate, better quality of service, and higher network capacity, there is a migration from Single Input Single Output (SISO) antenna technology to a more promising Multiple Input Multiple Output (MIMO) antenna technology. On the other hand, Orthogonal Frequency Division Multiplexing (OFDM) technique has emerged as a very popular multi-carrier modulation technique to combat the problems associated with physical properties of the wireless channels such as multipath fading, dispersion, and interference. The combination of MIMO technology with OFDM techniques, known as MIMO-OFDM Systems, is considered as a promising solution to enhance the data rate of future broadband wireless communication Systems. This thesis addresses a major area of challenge to both SISO-OFDM and MIMO-OFDM Systems; estimation of accurate channel state information (CSI) in order to make possible coherent detection of the transmitted signal at the receiver end of the system. Hence, the first novel contribution of this thesis is the development of a low complexity adaptive algorithm that is robust against both slow and fast fading channel scenarios, in comparison with other algorithms employed in literature, to implement soft iterative channel estimator for turbo equalizer-based receiver for single antenna communication Systems. Subsequently, a Fast Data Projection Method (FDPM) subspace tracking algorithm is adapted to derive Channel Impulse Response Estimator for implementation of Decision Directed Channel Estimation (DDCE) for Single Input Single Output - Orthogonal Frequency Division Multiplexing (SISO-OFDM) Systems. This is implemented in the context of a more realistic Fractionally Spaced-Channel Impulse Response (FS-CIR) channel model, as against the channel characterized by a Sample Spaced-Channel Impulse Response (SS)-CIR widely assumed by other authors. In addition, a fast convergence Variable Step Size Normalized Least Mean Square (VSSNLMS)-based predictor, with low computational complexity in comparison with others in literatures, is derived for the implementation of the CIR predictor module of the DDCE scheme. A novel iterative receiver structure for the FDPM-based Decision Directed Channel Estimation scheme is also designed for SISO-OFDM Systems. The iterative idea is based on Turbo iterative principle. It is shown that improvement in the performance can be achieved with the iterative DDCE scheme for OFDM system in comparison with the non iterative scheme. Lastly, an iterative receiver structure for FDPM-based DDCE scheme earlier designed for SISO OFDM is extended to MIMO-OFDM Systems. In addition, Variable Step Size Normalized Least Mean Square (VSSNLMS)-based channel transfer function estimator is derived in the context of MIMO Channel for the implementation of the CTF estimator module of the iterative Decision Directed Channel Estimation scheme for MIMO-OFDM Systems in place of linear minimum mean square error (MMSE) criterion. The VSSNLMS-based channel transfer function estimator is found to show improved MSE performance of about -4 MSE (dB) at SNR of 5dB in comparison with linear MMSE-based channel transfer function estimator

Smart Antenna-Aided Multicarrier Transceivers for Mobile Communications

In spite of an immense interest from both the academic and the industrial communities, a practical multipleinput multiple-output (MIMO) transceiver architecture, capable of approaching channel capacity boundaries in realistic channel conditions remains largely an open problem. Consequently, in this treatise I derive an advanced iterative, so called turbo multi-antenna-multi-carrier (MAMC) receiver architecture. Following the philosophy of turbo processing, our turbo spacial division multiplexed (SDM)-orthogonal frequency division multiplexed (OFDM) receiver comprises a succession of soft-input-soft-output detection modules, which iteratively exchange soft bit-related information and thus facilitate a substantial improvement of the overall system performance. In this treatise, I explore two major aspects of the turbo wireless mobile receiver design. Firstly, I consider the problem of soft-decision-feedback aided acquisition of the propagation conditions experienced by the transmitted signal and secondly, I explore the issue of the soft-input-soft-output detection of the spatially-multiplexed information-carrying signals

Iterative joint channel and data estimation for rank-deficient MIMO-OFDM

In this paper we propose a turbo-detected multi-antenna-multi-carrier receiver scheme. Following the philosophy of the turbo processing, our turbo MIMO-OFDM receiver comprises a succession of detection modules, namely the channel estimator, the space-time detector and the decoder, which iteratively exchange soft bit-related information and thus facilitate a substantial improvement of the overall system performance. In this paper we analyze the achievable performance of the iterative system proposed with the aim of documenting the various design trade-offs, such as the achievable error-rate performance, the attainable data-rate as well as the associated computational complexity. Specifically, we report a virtually error-free performance for a rate-1/2 turbo-coded 8x8-QPSK-OFDM system, exhibiting an effective throughput of 8*2/2=8 bits/sec/Hz and having a pilot overhead of only 10%, at SNR of 7.5dB and normalized Doppler frequency of 0.003, which corresponds to a mobile terminal speed of about 65 km/h

Parallel-Interference-Cancellation-Assisted Decision-Directed Channel Estimation for OFDM Systems using Multiple Transmit Antennas

The number of transmit antennas that can be employed in the context of least-squares (LS) channel estimation contrived for orthogonal frequency division multiplexing (OFDM) systems employing multiple transmit antennas is limited by the ratio of the number of subcarriers and the number of significant channel impulse response (CIR)-related taps. In order to allow for more complex scenarios in terms of the number of transmit antennas and users supported, CIR-related tap prediction-filtering-based parallel interference cancellation (PIC)-assisted decision-directed channel estimation (DDCE) is investigated. New explicit expressions are derived for the estimator’s mean-square error (MSE), and a new iterative procedure is devised for the offline optimization of the CIR-related tap predictor coefficients. These new expressions are capable of accounting for the estimator’s novel recursive structure. In the context of our performance results, it is demonstrated, for example, that the estimator is capable of supporting L = 16 transmit antennas, when assuming K = 512 subcarriers and K0 = 64 significant CIR taps, while LS-optimized DDCE would be limited to employing L = 8 transmit antennas. Index Terms—Decision-directed channel estimation (DDCE), multiple transmit antennas, orthogonal frequency division multiplexing (OFDM), parallel interference cancellation (PIC)

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

Low-Complexity Algorithms for Channel Estimation in Optimised Pilot-Assisted Wireless OFDM Systems

Orthogonal frequency division multiplexing (OFDM) has recently become a dominant transmission technology considered for the next generation fixed and mobile broadband wireless communication systems. OFDM has an advantage of lessening the severe effects of the frequency-selective (multipath) fading due to the band splitting into relatively flat fading subchannels, and allows for low-complexity transceiver implementation based on the fast Fourier transform algorithms. Combining OFDM modulation with multilevel frequency-domain symbol mapping (e.g., QAM) and spatial multiplexing (SM) over the multiple-input multiple-output (MIMO) channels, can theoretically achieve near Shannon capacity of the communication link. However, the high-rate and spectrumefficient system implementation requires coherent detection at the receiving end that is possible only when accurate channel state information (CSI) is available. Since in practice, the response of the wireless channel is unknown and is subject to random variation with time, the receiver typically employs a channel estimator for CSI acquisition. The channel response information retrieved by the estimator is then used by the data detector and can also be fed back to the transmitter by means of in-band or out-of-band signalling, so the latter could adapt power loading, modulation and coding parameters according to the channel conditions. Thus, design of an accurate and robust channel estimator is a crucial requirement for reliable communication through the channel, which is selective in time and frequency. In a MIMO configuration, a separate channel estimator has to be associated with each transmit/receive antenna pair, making the estimation algorithm complexity a primary concern. Pilot-assisted methods, relying on the insertion of reference symbols in certain frequencies and time slots, have been found attractive for identification of the doubly-selective radio channels from both the complexity and performance standpoint. In this dissertation, a family of the reduced-complexity estimators for the single and multiple-antenna OFDM systems is developed. The estimators are based on the transform-domain processing and have the same order of computational complexity, irrespective of the number of pilot subcarriers and their positioning. The common estimator structure represents a cascade of successive small-dimension filtering modules. The number of modules, as well as their order inside the cascade, is determined by the class of the estimator (one or two-dimensional) and availability of the channel statistics (correlation and signal-to-noise power ratio). For fine precision estimation in the multipath channels with statistics not known a priori, we propose recursive design of the filtering modules. Simulation results show that in the steady state, performance of the recursive estimators approaches that of their theoretical counterparts, which are optimal in the minimum mean square error (MMSE) sense. In contrast to the majority of the channel estimators developed so far, our modular-type architectures are suitable for the reconfigurable OFDM transceivers where the actual channel conditions influence the decision of what class of filtering algorithm to use, and how to allot pilot subcarrier positions in the band. In the pilot-assisted transmissions, channel estimation and detection are performed separately from each other over the distinct subcarrier sets. The estimator output is used only to construct the detector transform, but not as the detector input. Since performance of both channel estimation and detection depends on the signal-to-noise power vi ratio (SNR) at the corresponding subcarriers, there is a dilemma of the optimal power allocation between the data and the pilot symbols as these are conflicting requirements under the total transmit power constraint. The problem is exacerbated by the variety of channel estimators. Each kind of estimation algorithm is characterised by its own SNR gain, which in general can vary depending on the channel correlation. In this dissertation, we optimise pilot-data power allocation for the case of developed low-complexity one and two-dimensional MMSE channel estimators. The resultant contribution is manifested by the closed-form analytical expressions of the upper bound (suboptimal approximate value) on the optimal pilot-to-data power ratio (PDR) as a function of a number of design parameters (number of subcarriers, number of pilots, number of transmit antennas, effective order of the channel model, maximum Doppler shift, SNR, etc.). The resultant PDR equations can be applied to the MIMO-OFDM systems with arbitrary arrangement of the pilot subcarriers, operating in an arbitrary multipath fading channel. These properties and relatively simple functional representation of the derived analytical PDR expressions are designated to alleviate the challenging task of on-the-fly optimisation of the adaptive SM-MIMO-OFDM system, which is capable of adjusting transmit signal configuration (e.g., block length, number of pilot subcarriers or antennas) according to the established channel conditions

Implementation of a testbed for MISO OFDM communication systems.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2012.The thesis presents an implementation of a multiple input single output orthogonal frequency division multiplex (MISO OFDM) communication system testbed. The project was developed in order to evaluate whether the channel estimation algorithms developed by Dr Oyerinde [1] could be implemented in a real time communication system that uses today’s technology. This implementation based validation would help determine the practicality of algorithms and methods that promise better performance for communication systems from a simulation point of view. The benefits of using multiple orthogonal carriers are discussed as well as how an OFDM system works. The benefits of using multiple antennas at the transmitter, as opposed to using just one, are also discussed. The Alamouti scheme which allows space diversity to be achieved without the cost of having a lower data rate is presented. Modules common to all communication systems, such as those dedicated to synchronization, channel estimation, symbol detection and channel coding, are discussed. The different methods of synchronization for OFDM communication systems are presented and compared. The channel estimation algorithm developed by Dr Oyerinde is presented and is adopted for an indoor channel. Most of the system blocks and parameters used in the testbed are the same as those used in [1] in order to easily compare the results obtained by simulation and those obtained by implementation. The system bandwidth required for the project was too high for the processor chosen for the testbed. A qualitative evaluation of the practicality of Dr Oyerinde’s channel estimation algorithms was performed instead. From this evaluation it was derived that Dr Oyerinde’s non-iterative decision directed channel estimation algorithm was more suitable for real time non-iterative decision directed channel estimation communication systems than for iterative versions. Apart from processing demands that couldn’t be met, the other aspects of the project were implemented successfully

Doctor of Philosophy

dissertationThis dissertation addresses several key challenges in multiple-antenna communications, including information-theoretical analysis of channel capacity, capacity-achieving signaling design, and practical statistical detection algorithms. The first part of the thesis studies the capacity limits of multiple-input multiple-output (MIMO) multiple access channel (MAC) via virtual representation (VR) model. The VR model captures the physical scattering environment via channel gains in the angular domain, and hence is a realistic MIMO channel model that includes many existing channel models as special cases. This study provides analytical characterization of the optimal input distribution that achieves the sum-capacity of MAC-VR. It also investigates the optimality of beamforming, which is a simple scalar coding strategy desirable in practice. For temporally correlated channels, beamforming codebook designs are proposed that can efficiently exploit channel correlation. The second part of the thesis focuses on statistical detection for time-varying frequency-selective channels. The proposed statistical detectors are developed based on Markov Chain Monte Carlo (MCMC) techniques. The complexity of such detectors grows linearly in system dimensions, which renders them applicable to inter-symbol-interference (ISI) channels with long delay spread, for which the traditional trellis-based detectors fail due to prohibitive complexity. The proposed MCMC detectors provide substantial gain over the de facto turbo minimum-mean square-error (MMSE) detector for both synthetic channel and underwater acoustic (UWA) channels. The effectiveness of the proposed MCMC detectors is successfully validated through experimental data collected from naval at-sea experiments