Layered MAP algorithm for MIMO ISI channels

The layered maximum a posteriori （L-MAP） algorithm has been proposed to detect signals under frequency selective fading multiple input multiple output （MIMO） channels. Compared to the optimum MAP detector, the L-MAP algorithm can efficiently identify signal bits, and the complexity grows linearly with the number of input antennas. The basic idea of L-MAP is to operate on each input sub-stream with an optimum MAP sequential detector separately by assuming the other streams are Gaussian noise. The soft output can also be forwarded to outer channel decoder for iterative decoding. Simulation results show that the proposed method can converge with a small number of iterations under different channel conditions and outperforms other sub-optimum detectors for rank-deficient channels.     

BEM-based SISO detection of orthogonal space-time block codes over frequency flat-fading channels

The expectation-maximization algorithm for maximum a posteriori (MAP) estimation of a random vector is applied to the problem of detection of orthogonal space-time block codes over time-selective Rayleigh fading channels. This results in a soft-in soft-out detection algorithm suitable for iterative detection/decoding schemes. Simulation results show that the error performance of the proposed detection algorithm is very close to that of a MAP detector endowed with an ideal knowledge of the channel state if the fading rate is not too fast.     

Joint MAP equalization and channel estimation forfrequency-selective and frequency-flat fast-fading channels

This paper presents a new fractionally-spaced maximum a posteriori (MAP) equalizer for data transmission over frequency-selective fading channels. The technique is applicable to any standard modulation technique. The MAP equalizer uses an expanded hypothesis trellis for the purpose of joint channel estimation and equalization. The fading channel is estimated by coupling minimum mean square error techniques with the (fixed size) expanded trellis. The new MAP equalizer is also presented in an iterative (turbo) receiver structure. Both uncoded and conventionally coded systems (including iterative processing) are studied. Even on frequency-flat fading channels, the proposed receiver outperforms conventional techniques. Simulations demonstrate the performance of the proposed equalizer     

Single Carrier Frequency Domain Equalization Space–Time Block-Spread CDMA with Multiuser Interference-Free Detection

In this paper, we study a single carrier space–time block-spread (STBS) with frequency domain equalization combined with direct-spread code division multiple access (CDMA) which we term, SCFDE-STBS-CDMA. We propose a novel SCFDE space–time scheme for CDMA that achieves multiuser-interference free reception and performs well in both slow and fast fading frequency selective channel. The orthogonality among the users is preserved at the receiver allowing a multiuser-free MUI-free detection in slow fading channel. In fast fading channel, we proposed a MMSE detector that exploits the time diversity of the fast fading channels. In the conventional counterpart scheme proposed in the literature, the length of the spreading factor affect negatively the performance of the system when the channel is fast fading while in the proposed scheme, the spreading factor is an additional degree of freedom that do not degrade the system performance. Since the maximum number of users supported depends on the spreading factor, the proposed scheme can then maintain more users than the conventional one in fast fading channels. The bit-error rate (BER) performance of the proposed scheme is analyzed and compared with the conventional approach in the literature.     

Blind equalization of dispersive fast fading Ricean channels via the EMV algorithm

A blind maximum likelihood equalization method is proposed for frequency selective fast fading Ricean channels. This method employs the expectation-maximization Viterbi algorithm (EMVA) developed in for blind channel estimation and signal detection. Since the Viterbi algorithm (VA) is used to execute the E-phase of an expectation-maximization (EM) iteration, it requires that the observed sequence can be modelled as a finite-state hidden Markov process. We develop a hidden Markov model for frequency selective fast fading Ricean channels, so that the observed process can be viewed as the noisy output of a finite state machine (FSM), to which the VA is applicable. The EMVA is then employed to obtain a blind maximum likelihood estimate of the specular part of the channel and, for one special case, of a noise parameter measuring the total power of the additive and multiplicative channel noise components. Simulation results are presented which show that the EMVA achieves an accurate estimate of the channel specular part and has an error rate performance close to that of the maximum likelihood detector based on true parameters for the given FSM model.     

Performance of parallel and serial concatenated codes on fading channels

The performance of parallel and serial concatenated codes on frequency-nonselective fading channels is considered. The analytical average upper bounds of the code performance over Rician channels with independent fading are derived. Furthermore, the log-likelihood ratios and extrinsic information for maximum a posteriori (MAP) probability and soft-output Viterbi algorithm (SOVA) decoding methods on fading channels are developed. The derived upper bounds are evaluated and compared to the simulated bit-error rates over independent fading channels. The performance of parallel and serial codes with MAP and SOVA iterative decoding methods, with and without channel state information, is evaluated by simulation over independent and correlated fading channels. It is shown that, on correlated fading channels, the serial concatenated codes perform better than parallel concatenated codes. Furthermore, it has been demonstrated that the SOVA decoder has almost the same performance as the MAP decoder if ideal channel state information is used on correlated Rayleigh fading channels.     

Adaptive MAPSD algorithms for symbol and timing recovery of mobileradio TDMA signals

Dual-mode adaptive algorithms with rapid convergence properties are presented for the equalization of frequency selective fading channels and the recovery of time-division multiple access (TDMA) mobile radio signals. The dual-mode structure consists of an auxiliary adaptive filter that estimates the channel during the training cycle. The converged filter weights are used to initialize a parallel bank of filters that are adapted blindly during the data cycle. When the symbol timing is known, this filter bank generates error residuals that are used to perform approximate maximum a posteriori symbol detection (MAPSD) and provide reliable decisions of the transmitted signal. For channels with timing jitter, joint estimation of the channel parameters and the symbol timing using an extended Kalman filter algorithm is proposed. Various methods are described to reduce the computational complexity of the MAP detector, usually at the cost of some performance degradation. Also, a blind MAPSD algorithm for combining signals from spatially diverse receivers is derived. This diversity MAPSD (DMAPSD) algorithm, which can be easily modified for the dual-mode TDMA application, maintains a global set of MAP metrics even while blindly tracking the individual spatial channels using local error estimates. The performance of these single-channel and diversity MAPSD dual-mode algorithms are studied via computer simulations for various channel models, including a mobile radio channel simulator for the IS-54 digital cellular TDMA standard     

Low-Complexity Map Channel Estimation for Mobile MIMO-OFDM Systems

This paper presents a reduced-complexity maximum a posteriori probability (MAP) channel estimator with iterative data detection for orthogonal frequency division multiplexing (OFDM) systems over mobile multiple-input multiple- output channels. The optimal MAP estimator needs to invert an NN_T x NN_T data-dependent matrix each in OFDM symbol interval, where N is the number of subcarriers and N_T is the number of transmit antennas. We derive an expectation maximization (EM) algorithm with low-rank approximation to avoid inverting large-size matrices, and thus drastically reduce the receiver complexity. In the iterative process, channel parameters are initially obtained by a least square (LS) estimator for temporary symbol decisions. Then, inter-carrier interference (ICI) due to fast fading is approximated and canceled. Finally, the temporary symbol decisions and the ICI-canceled received signals are processed by the EM-based MAP estimator to refine the channel state information for improved detection. The proposed scheme achieves about 2 dB gain over the LS scheme in channels with medium to high normalized Doppler shifts.     

Modeling and Estimation of Wireless OFDM Channels by Using Time-Frequency Analysis

Orthogonal frequency division multiplexing (OFDM) has become a very popular method for high data rate wireless communications because of its advantages over single carrier modulation schemes on multipath, frequency selective fading channels. However, intercarrier interference, due to Doppler frequency shifts, and multipath fading severely degrade the performance of OFDM systems. Estimation of channel parameters is required at the receiver. In this paper, we present a channel modeling and estimation method based on the time-frequency representation of the received signal. The discrete evolutionary transform provides a time-frequency procedure to obtain a complete characterization of the multipath, fading, and frequency selective channels. Simulations are used to illustrate the performance of the proposed procedure and to compare it with other time-varying channel estimation techniques.     

On channel estimation and sequence detection of interleaved codedsignals over frequency nonselective Rayleigh fading channels

Due to the receiver complexity introduced by interleaving, the implementation of maximum likelihood (IML) decoding of interleaved coded signals transmitted over frequency nonselective Rayleigh fading channels has been shown to be practically impossible. As an alternative, a two-stage receiver structure has been proposed, where the channel estimation and sequence decoding are done separately. The channel estimation issue in a two-stage receiver is examined in detail in this paper. It is shown that although an optimum (maximum a posteriori (MAP)) channel estimation is not possible in practice, it can be approached asymptotically by joint MAP estimation of the channel and the coded data sequence. The implementation of the joint MAP estimation is shown to be an ML sequence estimator followed by an minimum mean-square error (MMSE) channel estimator. Approximate fill sequence estimation using pilot symbol interpolation is also studied, and through computer simulations, its performance is compared to receivers using hit sequence estimation. The effect of decision delay (DD), prediction order, and pilot insertion rate (PIR) on the reduced complexity ML sequence estimation is investigated as well. Finally, a practical receiver is proposed that makes the best compromise among the error performance, receiver complexity, DD, and power (or bandwidth) expansion due to pilot insertion     

Nondata-aided channel estimation for OFDM systems with space-frequency transmit diversity

This paper proposes a computationally efficient nondata-aided maximum a posteriori (MAP) channel-estimation algorithm focusing on the space-frequency (SF) transmit diversity orthogonal frequency division multiplexing (OFDM) transmission through frequency-selective channels. The proposed algorithm properly averages out the data sequence and requires a convenient representation of the discrete multipath fading channel based on the Karhunen-Loeve (KL) orthogonal expansion and estimates the complex channel parameters of each subcarrier iteratively, using the expectation maximization (EM) method. To further reduce the computational complexity of the proposed MAP algorithm, the optimal truncation property of the KL expansion is exploited. The performance of the MAP channel estimator is studied based on the evaluation of the modified Cramer-Rao bound (CRB). Simulation results confirm the proposed theoretical analysis and illustrate that the proposed algorithm is capable of tracking fast fading and improving overall performance.     

Efficient LDPC‐Based,Threaded Layered Space‐Time‐Frequency System with Iterative Receiver

We present a low‐density parity‐check (LDPC)‐based, threaded layered space‐time‐frequency system with emphasis on the iterative receiver design. First, the unbiased minimum mean‐squared‐error iterative‐tree‐search (U‐MMSE‐ITS) detector, which is known to be one of the most efficient multi‐input multi‐output (MIMO) detectors available, is improved by augmentation of the partial‐length paths and by the addition of one‐bit complement sequences. Compared with the U‐MMSE‐ITS detector, the improved detector provides better detection performance with lower complexity. Furthermore, the improved detector is robust to arbitrary MIMO channels and to any antenna configurations. Second, based on the structure of the iterative receiver, we present a low‐complexity belief‐propagation (BP) decoding algorithm for LDPC‐codes. This BP decoder not only has low computing complexity but also converges very fast (5 iterations is sufficient). With the efficient receiver employing the improved detector and the low‐complexity BP decoder, the proposed system is a promising solution to high‐data‐rate transmission over selective‐fading channels.     

An iterative receiver for turbo-coded pilot-assisted modulation infading channels

We introduce an iterative joint channel and data estimation receiver that exploits both the power of pilot-symbol assisted modulation (PSAM) and turbo coding for fading channels. The key innovation is a low-complexity soft channel estimator which divides a processing block into overlapped cells and performs maximum a posteriori (MAP) sequence estimation and MMSE filtering based on the received signal and extrinsic information delivered by the soft channel decoder. Simulation results show that for turbo-coded PSAM systems under time-variant fading the proposed receiver offers significant performance gains over a non-iterative receiver and two other cancellation schemes     

Performance analysis on an MAP fine timing algorithm in UWB multiband OFDM

In this paper we develop a fine synchronization algorithm for multiband OFDM transmission in the presence of frequency selective channels. This algorithm is based on maximum a posteriori (MAP) joint timing and channel estimation that incorporates channel statistical information, leading to considerable performance enhancement relative to existing maximum likelihood (ML) approaches. We carry out a thorough performance analysis of the fine timing algorithm, and link the diversity concept widely used in data communications to the timing performance. We show that the probability of the timing offset equal to or larger than Delta taps has a diversity order of N_B min(Delta, L) in Rayleigh fading channels, where N_B is the number of subbands and L is the number of channel taps. This result reveals that the timing estimate is very much concentrated around the true timing as the signal to noise ratio (SNR) increases. Our simulations confirm the theoretical analysis, and also demonstrate the robustness of the proposed timing algorithm against model mismatches in a realistic UWB indoor channel.     

Performance analysis of two-branch transmit diversity block-coded OFDM systems in time-varying multipath Rayleigh-fading channels

Based on Alamouti code, Lee and Williams proposed two-branch transmit diversity block-coded orthogonal frequency-division multiplexing (TDBC-OFDM) systems, namely, space-time block-coded OFDM (STBC-OFDM) and space-frequency block-coded OFDM (SFBC-OFDM). However, they employed the simple maximum-likelihood (SML) detector, which was designed under the assumption that the channel is static over the duration of a space-time/frequency codeword. Therefore, STBC-OFDM/SFBC-OFDM suffers from the high time/frequency selectivity of the wireless mobile fading channel. In this paper, besides the original SML detector, three detectors proposed by Vielmon et al. are applied to improve the two-branch TDBC-OFDM systems. Additionally, assuming sufficient cyclic prefix, the performances of all systems in spatially uncorrelated time-varying multipath Rayleigh-fading channels are evaluated by theoretical derivation and computer simulation, as well. According to the derived bit-error rate (BER), we further derive the bit-error outage (BEO) to provide a more object judgment on the transmission quality within a fading environment. Numerical results have revealed that significant performance improvement can be achieved even when the systems are operated in highly selective channels.     

Decision-Feedback Receiver for Quasi-Orthogonal Space-Time Coded OFDM Using Correlative Coding Over Fast Fading Channels

Orthogonal frequency division multiplexing (OFDM) is robust against frequency selective fading, but it is very vulnerable to time selective fading. In quasi-orthogonal space-time coded OFDM (ST-OFDM) systems, channel variations cause not only inter-carrier interference among different subcarriers in one OFDM block, but also inter-transmit-antenna interference (ITAI). When applied in fast fading channels, common ST-ODFM receivers usually suffer from an irreducible error floor. In this letter, we apply frequency-domain correlative coding combined with a modified decision-feedback detection scheme to effectively suppress the error floor of quasi-orthogonal ST-OFDM over fast fading channels. The effectiveness of the proposed scheme in mitigating the effects of channel time selectivity is demonstrated through comparison with existing schemes such as zero-forcing, two-stage zero-forcing, and sequential decision feedback estimation     

Iterative vector channel estimation/MAP/PIC for CDMA systems in time-selective correlated multipath fading channels

Recently, Gao et al. proposed the expectation-maximization (EM) vector channel estimation for single-user direct-sequence code-division multiple-access (DS-CDMA) systems to estimate the correlated fading channel coefficients of the paths of a user. They also used one D-lag decision-feedback maximum a posteriori (MAP) detector to detect the information bits. A straightforward extension (noniterative) to multiuser synchronous CDMA cases, i.e., adding the parallel interference cancellation (PIC) multiuser detector into their scheme, results in poor performance. Therefore, we propose an iterative scheme which combines vector channel estimation, decision-feedback MAP detection, and PIC. The partial PIC is applied in the sequence hypothesis stage of MAP in each iteration before the final MAP decision. The proposed scheme has twice the decision delay of the previous scheme for single-user cases. The performance of the proposed system in the time-selective, correlated multipath fading channel environment is investigated. Simulation results show that the proposed scheme significantly outperforms the noniterative scheme. Simulation results also show that the proposed scheme performs better than its scalar channel-estimation version.     

Turbo equalization of doubly selective channels

In this paper, turbo equalization for transmission over doubly selective channels is proposed. The maximum a posteriori probability (MAP) algorithm is used for channel detection as well as for channel decoding. The detection/decoding constituents can exchange soft information in an iterative manner resulting in the so‐called turbo equalization. The time‐varying multi‐path fading channel is modeled using the basis expansion model (BEM). In this BEM, the time‐varying channel is viewed as a bank of time‐invariant finite impulse response filters, and the time variation is captured by means of time‐varying complex exponential basis functions. Therefore, the time‐varying transition tables that characterize the time‐varying channel can also follow a similar BEM. The complexity of the MAP channel detector is rather prohibitive for practical applications. This motivates the search for lower‐complexity soft‐output channel detectors. For this purpose, soft‐output linear minimum‐mean square error (LMMSE)‐based channel detectors are proposed for single carrier as well as for multi‐carrier systems. With the use of Gaussian approximation, expressions for the a posteriori and extrinsic log‐likelihood ratios have been derived. The performance of the proposed turbo equalization schemes are evaluated using numerical simulations. Copyright © 2012 John Wiley & Sons, Ltd.     

Joint Semi-Blind Channel Estimation and Data Sequence Detection of OFDM Systems

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BLIND CHANNEL ESTIMATION IN DELAY DIVERSITY FOR FREQUENCY SELECTIVE CHANNELS1

Delay diversity is an effective transmit diversity technique to combat adverse effects of fading. Thus far, previous work in delay diversity assumed that perfect estimates of current channel fading conditions are available at the receiver and training symbols are required to estimate the channel from the transmitter to the receiver. However, increasing the number of the antennas increases the required training interval and reduces the available time with in whichdata may be transmitted. Learning the channel coefficients becomes increasingly difficult for the frequency selective channels. In this paper, with the subspace method and the delay character of delay diversity, a channel estimation method is proposed, which does not use training symbols. It addresses the transmit diversity for a frequency selective channel from a single carrier perspective in the form of a simple equivalent flat fading model. Monte Carlo simulations give the performance of channel estimation and the performance comparison of our channel-estimation-based detector with decision feedback equalization, which uses the perfect channel information.