ITC/USA 2006 Conference Proceedings / The Forty-Second Annual International Telemetering Conference and Technical Exhibition / October 23-26, 2006 / Town and Country Resort & Convention Center, San Diego, California / OFDM is a preferred physical layer for an increasing number of telemetry and LAN applications. However, joint estimation of the multipath channel and frequency offset in OFDM remains a challenging problem. The Unscented Kalman Filter (UKF) is presented to solve the offset/channel tracking problem. The advantages of the UKF are that it is less susceptible to divergence than the EKF, and does not require computation of a Jacobian matrix. A hybrid analysis/simulation approach is developed to rapidly evaluate UKF performance in terms of symbol-error rate and channel/offset error for the 802.11a OFDM format.

ITC/USA 2005 Conference Proceedings / The Forty-First Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2005 / Riviera Hotel & Convention Center, Las Vegas, Nevada / Underwater acoustic (UWA) telemetry requires wideband waveforms for anti-multipath which are simultaneously easy to equalize and demodulate. The Walsh/m-sequence waveforms proposed here are robust to multipath and with appropriate time-guard bands do not require equalization. For example, in the UCSB prototype acoustic modem, a data rate of 133 bps is achieved using 8-ary Walsh signaling with an 11.2 msec. symbol duration. Demodulation is performed using noncoherent detection, and hence accurate phase tracking, which is difficult to achieve in the UWA channel, is not required. However, telemetry from unmanned underwater vehicles (UUVs) is more problematic due to large Doppler shifts resulting from platform motion. A new receiver algorithm based on Matching Pursuits is proposed which combines channel and Doppler shift estimation. Symbol-error rate (SER) simulation results are presented for the UWA modem under realistic Doppler/multipath conditions.

Master of Engineering by Research / As a multi-carrier modulation scheme, Orthogonal Frequency Division Multiplexing (OFDM) technique can achieve high data rate in frequency-selective fading channels by splitting a broadband signal into a number of narrowband signals over a number of subcarriers, where each subcarrier is more robust to multipath. The wireless communication system with multiple antennas at both the transmitter and receiver, known as multiple-input multiple-output (MIMO) system, achieves high capacity by transmitting independent information over different antennas simultaneously. The combination of OFDM with multiple antennas has been considered as one of most promising techniques for future wireless communication systems. The challenge in the detection of a space-time signal is to design a low-complexity detector, which can efficiently remove interference resulted from channel variations and approach the interference-free bound. The application of iterative parallel interference canceller (PIC) with joint detection and decoding has been a promising approach. However, the decision statistics of a linear PIC is biased toward the decision boundary after the first cancellation stage. In this thesis, we employ an iterative receiver with a decoder metric, which considerably reduces the bias effect in the second iteration, which is critical for the performance of the iterative algorithm. Channel state information is required in a MIMO-OFDM system signal detection at the receiver. Its accuracy directly affects the overall performance of MIMO-OFDM systems. In order to estimate the channel in high-delay-spread environments, pilot symbols should be inserted among subcarriers before transmission. To estimate the channel over all the subcarriers, various types of interpolators can be used. In this thesis, a linear interpolator and a trigonometric interpolator are compared. Then we propose a new interpolator called the multi-tap method, which has a much better system performance. In MIMO-OFDM systems, the time-varying fading channels can destroy the orthogonality of subcarriers. This causes serious intercarrier interference (ICI), thus leading to significant system performance degradation, which becomes more severe as the normalized Doppler frequency increases. In this thesis, we propose a low-complexity iterative receiver with joint frequency- domain ICI cancellation and pilot-assisted channel estimation to minimize the effect of time-varying fading channels. At the first stage of receiver, the interference between adjacent subcarriers is subtracted from received OFDM symbols. The parallel interference cancellation detection with decision statistics combining (DSC) is then performed to suppress the interference from other antennas. By restricting the interference to a limited number of neighboring subcarriers, the computational complexity of the proposed receiver can be significantly reduced. In order to construct the time variant channel matrix in the frequency domain, channel estimation is required. However, an accurate estimation requiring complete knowledge of channel time variations for each block, cannot be obtained. For time- varying frequency-selective fading channels, the placement of pilot tones also has a significant impact on the quality of the channel estimates. Under the assumption that channel variations can be approximated by a linear model, we can derive channel state information (CSI) in the frequency domain and estimate time-domain channel parameters. In this thesis, an iterative low-complexity channel estimation method is proposed to improve the system performance. Pilot symbols are inserted in the transmitted OFDM symbols to mitigate the effect of ICI and the channel estimates are used to update the results of both the frequency domain equalizer and the PICDSC detector in each iteration. The complexity of this algorithm can be reduced because the matrices are precalculated and stored in the receiver when the placement of pilots symbols is fixed in OFDM symbols before transmission. Finally, simulation results show that the proposed MIMO-OFDM iterative receiver can effectively mitigate the effect of ICI and approach the ICI-free performance over time-varying frequency-selective fading channels.

This dissertation deals with the channel estimation techniques for orthogonal frequency division multiplexing (OFDM) systems such as in IEEE 802.11. Although there has been a great amount of research in this area, characterization of typical wireless indoor environments and design of channel estimation schemes that are both robust and practical for such channel conditions have not been thoroughly investigated. It is well known that the minimum mean-square-error (MMSE) estimator provides the best mean-square-error (MSE) performance given a priori knowledge of channel statistics and operating signal-to-noise ratio (SNR). However, the channel statistics are usually unknown and the MMSE estimator has too much computational complexity to be realized in practical systems. In this work, we propose two simple channel estimation techniques: one that is based on modifying the channel correlation matrix from the MMSE estimator and the other one with averaging window based on the LS estimates. We also study the characteristics of several realistic indoor channel models that are of potential use for wireless local area networks (LANs). The first method, namely MMSE-exponential-Rhh, does not depend heavily on the channel statistics and yet offer performance improvement compared to that of the LS estimator. The simulation results also show that the second method, namely averaging window (AW) estimator, provides the best performance at moderate SNR range.

This dissertation deals with the channel estimation techniques for orthogonal frequency division multiplexing (OFDM) systems such as in IEEE 802.11. Although there has been a great amount of research in this area, characterization of typical wireless indoor environments and design of channel estimation schemes that are both robust and practical for such channel conditions have not been thoroughly investigated. It is well known that the minimum mean-square-error (MMSE) estimator provides the best mean-square-error (MSE) performance given a priori knowledge of channel statistics and operating signal-to-noise ratio (SNR). However, the channel statistics are usually unknown and the MMSE estimator has too much computational complexity to be realized in practical systems. In this work, we propose two simple channel estimation techniques: one that is based on modifying the channel correlation matrix from the MMSE estimator and the other one with averaging window based on the LS estimates. We also study the characteristics of several realistic indoor channel models that are of potential use for wireless local area networks (LANs). The first method, namely MMSE-exponential-Rhh, does not depend heavily on the channel statistics and yet offer performance improvement compared to that of the LS estimator. The simulation results also show that the second method, namely averaging window (AW) estimator, provides the best performance at moderate SNR range.

A complex array for constructing perfect sequences is presented in this paper. The row sequences and their discrete Fourier transform form two sets of perfect sequences. The column sequences are orthogonal to each other for any cyclic shift. In addition, any combination of the column sequences with complex weighting coefficients of equal amplitude is also a perfect sequence. In addition, a superimposed training scheme is also proposed for channel estimation in OFDM systems. The perfect sequence is adopted since it has a constant magnitude in both the time domain and the frequency domain. Although the derived channel estimator has a slightly worse performance since the unknown data contributes extra noise, the effective data throughput is substantially increased. In addition, the proposed scheme is shown to have a much better peak-to-average power ratio (PAPR) because the added perfect sequence has a constant magnitude in the time domain.

¡@¡@In recent year, orthogonal frequency division multiplexing ¡]OFDM¡^ technology has been widely used in high-speed communication systems. One primary reason for the popularity of OFDM is its ability to provide good performance in multi-path channels than the other systems through the use of Guard interval(GI). By using the Guard interval, it can convert these inter-symbol interference (ISI) channels into ISI-free channels. But Guard interval without any information will caused inter-channel interference. In order to solve this problem, a guard interval using cyclic prefix (CP) is inserted to avoid inter-symbol interference from the adjacent symbols and inter-channel interference from other sub-channels. However, using long cyclic prefix will decrease the transmission rate, reduce the spectral efficiency, and increase the signal-to-noise power ratio¡]SNR¡^loss. If we choose a shorter one, the channel length may be longer than the cyclic prefix. The interference caused by insufficient cyclic prefix can seriously degrade the performance of OFDM systems. In order to solve this problem, a time domain equalizer¡]TEQ¡^is usually used in the receiver to shorten the channel length of OFDM transmission system, and therefore minimize the ISI and ICI. However, because of its high complexity, the optimum design of TEQ is hard to realize. ¡@¡@So we use an iterative channel estimation technique between time domain and frequency domain to mitigate the ISI and ICI which is caused by insufficient cyclic prefix. The iterative technique can remove ISI and hold the circular convolution property. By utilizing the iterative technique we can improve the channel estimation performance as the OFDM symbol used sufficient cyclic prefix. ¡@¡@In the computer simulations, we consider the worst case that the OFDM symbol is transmitted without guard interval. The results show that our proposed method can effectively suppress residual ISI. The comparison between our proposed method including both proposed channel estimation¡]PCE¡^and proposed data demodulation¡]PDD¡^, decision feedback channel estimation¡]DFCE¡^, avoid ISI preamble channel estimation¡]AISIP¡^, and residual ISI cancellation¡]RISIC¡^algorithm are made in this thesis. Finally, the performance improvement of the proposed algorithm under several channel conditions is considered and compared with other algorithms.

Traditionally in CDMA system, selective rake receiver is the popular method of detection. When used in DS-UWB system, the complex in door environment will increase the channel paths. As the channel paths increase, the more fingers which are part of Rake receiver will increase. It will be difficult for hardware implement when consider the operation of channel estimation and Rake receiver. And it is unfavorable for hardware design. In this thesis, we will use partial Rake receiver to replace selective Rake receiver. Channel estimation is implemented by template the receiver signals within 2 bit time window length. The performance is acceptable and the hardware complexity is reduced. When implement the channel estimation, we combine some blocks of acquisition and channel estimation for reducing hardware complexity.

This thesis looks at the problem of channel estimation and equalization in a multiple-input multiple-output (MIMO) dispersive fading environments. Two classes of MIMO receiver structure are proposed with integrated channel estimation and tracking. One is a symbol-by-symbol based receiver using a MIMO minimum mean square error (MMSE) decision feedback equalizer (DFE), and the other is a sequence-based receiver using a partitioned Viterbi algorithm (PVA) which approaches the performance of maximum likelihood sequence estimation (MLSE). A MIMO channel estimator capable of tracking the time and frequency selective channel impulse responses, known as the vector generalized recursive least squares (VGRLS) algorithm, is developed. It has comparable performance and a similar level of complexity as the optimum Kalman filter. However, it does not require any knowledge of the channel statistics to operate and as such it can be employed in a Rician fading channel readily. A reduced complexity form of the estimator, known as the vector generalized least mean squares (VGLMS) algorithm, is also developed. This is achieved by replacing the online recursive computation of the VGRLS algorithm's 'intermediate' Riccatti matrix with an offline pre-computed matrix. This reduces the complexity of the algorithm by an order of a magnitude, but at the expense of degraded performance. The estimators are integrated with the above-mentioned equalizers in a decision directed mode to form a receiver structure that can operate in continuously time-varying fading channels. Due to decision delays, the outputs from the equalizer are delayed and this then produces 'delayed' channel estimates. A simple polynomial-based channel prediction module is employed to provide up-to-date channel estimates required by the equalizers. However, simulation results show that the channel prediction module may be omitted for a very slowly fading channel where the channel responses do not vary much. In the case of the PVA- receiver, the zero-delay tentative decisions are used as feedback to the channel estimators with negligible loss.

Master of Engineering by Research / As a multi-carrier modulation scheme, Orthogonal Frequency Division Multiplexing (OFDM) technique can achieve high data rate in frequency-selective fading channels by splitting a broadband signal into a number of narrowband signals over a number of subcarriers, where each subcarrier is more robust to multipath. The wireless communication system with multiple antennas at both the transmitter and receiver, known as multiple-input multiple-output (MIMO) system, achieves high capacity by transmitting independent information over different antennas simultaneously. The combination of OFDM with multiple antennas has been considered as one of most promising techniques for future wireless communication systems. The challenge in the detection of a space-time signal is to design a low-complexity detector, which can efficiently remove interference resulted from channel variations and approach the interference-free bound. The application of iterative parallel interference canceller (PIC) with joint detection and decoding has been a promising approach. However, the decision statistics of a linear PIC is biased toward the decision boundary after the first cancellation stage. In this thesis, we employ an iterative receiver with a decoder metric, which considerably reduces the bias effect in the second iteration, which is critical for the performance of the iterative algorithm. Channel state information is required in a MIMO-OFDM system signal detection at the receiver. Its accuracy directly affects the overall performance of MIMO-OFDM systems. In order to estimate the channel in high-delay-spread environments, pilot symbols should be inserted among subcarriers before transmission. To estimate the channel over all the subcarriers, various types of interpolators can be used. In this thesis, a linear interpolator and a trigonometric interpolator are compared. Then we propose a new interpolator called the multi-tap method, which has a much better system performance. In MIMO-OFDM systems, the time-varying fading channels can destroy the orthogonality of subcarriers. This causes serious intercarrier interference (ICI), thus leading to significant system performance degradation, which becomes more severe as the normalized Doppler frequency increases. In this thesis, we propose a low-complexity iterative receiver with joint frequency- domain ICI cancellation and pilot-assisted channel estimation to minimize the effect of time-varying fading channels. At the first stage of receiver, the interference between adjacent subcarriers is subtracted from received OFDM symbols. The parallel interference cancellation detection with decision statistics combining (DSC) is then performed to suppress the interference from other antennas. By restricting the interference to a limited number of neighboring subcarriers, the computational complexity of the proposed receiver can be significantly reduced. In order to construct the time variant channel matrix in the frequency domain, channel estimation is required. However, an accurate estimation requiring complete knowledge of channel time variations for each block, cannot be obtained. For time- varying frequency-selective fading channels, the placement of pilot tones also has a significant impact on the quality of the channel estimates. Under the assumption that channel variations can be approximated by a linear model, we can derive channel state information (CSI) in the frequency domain and estimate time-domain channel parameters. In this thesis, an iterative low-complexity channel estimation method is proposed to improve the system performance. Pilot symbols are inserted in the transmitted OFDM symbols to mitigate the effect of ICI and the channel estimates are used to update the results of both the frequency domain equalizer and the PICDSC detector in each iteration. The complexity of this algorithm can be reduced because the matrices are precalculated and stored in the receiver when the placement of pilots symbols is fixed in OFDM symbols before transmission. Finally, simulation results show that the proposed MIMO-OFDM iterative receiver can effectively mitigate the effect of ICI and approach the ICI-free performance over time-varying frequency-selective fading channels.