Optimal periodic training signal for frequency offset estimation in frequency-selective fading channels

This paper addresses an optimal periodic training signal design for frequency offset estimation in frequency-selective multipath Rayleigh fading channels. For a fixed transmitted training signal energy within a fixed-length block, the optimal periodic training signal structure (the optimal locations of identical training subblocks) and the optimal training subblock signal are presented. The optimality is based on the minimum Cramer-Rao bound (CRB) criterion. Based on the CRB for joint estimation of frequency offset and channel, the optimal periodic training structure (optimality only in frequency offset estimation, not necessarily in joint frequency offset and channel estimation) is derived. The optimal training subblock signal is obtained by using the average CRB (averaged over the channel fading) and the received training signal statistics. A robust training structure design is also presented in order to reduce the occurrence of outliers at low signal-to-noise ratio values. The proposed training structures and subblock signals achieve substantial performance improvement.     

频率选择性衰落MIMO信道的GBDB模型及其性能分析

针对频率选择性MIMO信道建立GBDB模型。综合考虑了无线衰落信道收发两端的多普勒扩展、非均匀角度扩展以及平均发射与到达方向,综合考虑了收发端天线阵的配置,推导出频率选择性MIMO信道的联合空时频相关函数,给出该模型的时延扩展的概率密度函数、时延谱与角度谱,并且与实测数据进行对比分析,验证了该模型的准确性。     

A pre-BLAST-DFE technique for the downlink of frequency-selective fading MIMO channels

In this paper, we propose a pre-Bell Laboratories layered space-time (BLAST)-decision-feedback equalization technique for the downlink of frequency-selective fading multiple-input multiple-output (MIMO) channels to combat multiple-access interference (MAI) and intersymbol interference (ISI). In our technique, we perform MIMO pre-equalization and prelayered space-time processing at the transmitter or base station, with a simplified receiver at the mobile station that requires only limited signal processing. An important application is in the downlink, so that a simplified mobile station can be constructed. An expression for the signal-to-noise ratio (SNR) and error probability based on the Gaussian approximation of the output noise term is derived. Performance is investigated by analysis and simulation results. In particular, it is demonstrated that the diversity order of this technique is higher than that of the MIMO orthogonal frequency-division multiplexing (OFDM) with vertical (V)-BLAST and MIMO OFDM with linear transmit preprocessing. It is also noticed that this technique performs better at high SNR values.     

Optimal placement of training for frequency-selective block-fading channels

The problem of placing training symbols optimally for orthogonal frequency-division multiplexing (OFDM) and single-carrier systems is considered. The channel is assumed to be quasi-static with a finite impulse response of length (L + 1) samples. Under the assumptions that neither the transmitter nor the receiver knows the channel, and that the receiver forms a minimum mean square error (MMSE) channel estimate based on training symbols only, training is optimized by maximizing a tight lower bound on the ergodic training-based independent and identically distributed (i.i.d.) capacity. For OFDM systems, it is shown that the lower bound is maximized by placing the known symbols periodically in frequency. For single-carrier systems, under the assumption that the training symbols are placed in clusters of length /spl alpha/ /spl ges/ (2L + 1), it is shown that the lower bound is maximized by a family of placement schemes called QPP-/spl alpha/, where QPP stands for quasi-periodic placement. These placement schemes are formed by grouping the known symbols into as many clusters as possible and then placing these clusters periodically in the packet. For both OFDM and single-carrier systems, the optimum energy tradeoff between training and data is also obtained.     

Achievable information rates and coding for MIMO systems over ISI channels and frequency-selective fading channels

We propose a simulation-based method to compute the achievable information rates for general multiple-input multiple-output (MIMO) intersymbol interference (ISI) channels with inputs chosen from a finite alphabet. This method is applicable to both deterministic and stochastic channels. As an example of the stochastic MIMO ISI channels, we consider the multiantenna systems over frequency-selective fading channels, and quantify the improvement in the achievable information rates provided by the additional frequency diversity (for both ergodic and nonergodic cases). In addition, we consider the multiaccess multiantenna system and present some results on the achievable information-rate region. As for the deterministic MIMO ISI channels, we use the binary-input multitrack magnetic recording system as an example, which employs multiple write and read heads for data storage. Our results show that the multitrack recording channels have significant advantages over the single-track channels, in terms of the achievable information rates when the intertrack interference is considered. We further consider practical coding schemes over both stochastic and deterministic MIMO ISI channels, and compare their performance with the information-theoretical limits. Specifically, we demonstrate that the performance of the turbo coding/decoding scheme is only about 1.0 dB away from the information-theoretical limits at a bit-error rate of 10/sup -5/ for large interleaver lengths.     

Modulation diversity for frequency-selective fading channels

In this article, modulation diversity (MD) for frequency-selective fading channels is proposed. The achievable performance with MD is analyzed and a simple design criterion for MD codes for Rayleigh-fading channels is deduced from an upper bound on the pairwise error probability (PEP) for single-symbol transmission. This design rule is similar to the well-known design rule for MD codes for flat fading and does not depend on the power-delay profile of the fading channel. Several examples for MD codes with prescribed properties are given and compared. Besides the computationally costly optimum receiver, efficient low-complexity linear equalization (LE) and decision-feedback equalization (DFE) schemes for MD codes are also introduced. Simulations for the widely accepted COST fading models show that performance gains of several decibels can be achieved by MD combined with LE or DFE at bit-error rates (BERs) of practical interest. In addition, MD also enables the suppression of cochannel interference.     

Optimal decision strategies for acquisition of spread-spectrumsignals in frequency-selective fading channels

The focus of this paper is on the initial acquisition of a direct sequence (DS) spread-spectrum signal utilizing a purely parallel search strategy. A parallel search strategy is utilized because it reduces the acquisition time compared to either serial or partially parallel strategies. In particular, the purpose of this paper is to derive the optimal decision rule, based on the maximum-likelihood criterion, for frequency-selective fading channels. The performance of the conventional decision rule, optimized for additive white Gaussian noise and flat-fading channels, the optimal decision rule derived, and a suboptimal decision rule, also presented in this paper, are compared. It is shown that the optimal and suboptimal decision rules for Rayleigh-fading channels outperform the conventional decision rule. For Rician-fading channels, it is shown both that the optimal decision rule outperforms the conventional decision rule, and that the optimum decision rule for Rayleigh-fading channels, when implemented on a Rician-fading channel, yields approximately optimum performance     

Universal decoding for frequency-selective fading channels

We address the problem of universal decoding in unknown frequency-selective fading channels, using an orthogonal frequency-division multiplexing (OFDM) signaling scheme. A block-fading model is adopted, where the bands' fading coefficients are unknown yet assumed constant throughout the block. Given a codebook, we seek a decoder independent of the channel parameters whose worst case performance relative to a maximum-likelihood (ML) decoder that knows the channel is optimal. Specifically, the decoder is selected from a family of quadratic decoders, and the optimal decoder is referred to as a quadratic minimax (QMM) decoder for that family. As the QMM decoder is generally difficult to find, a suboptimal QMM decoder is derived instead. Despite its suboptimality, the proposed decoder is shown to outperform the generalized likelihood ratio test (GLRT), which is commonly used when the channel is unknown, while maintaining a comparable complexity. The QMM decoder is also derived for the practical case where the fading coefficients are not entirely independent but rather satisfy some general constraints. Simulations verify the superiority of the proposed QMM decoder over the GLRT and over the practically used training sequence approach.     

On the design of space-time and space-frequency codes for MIMO frequency-selective fading channels

The authors introduced an algebraic design framework for space-time coding in flat-fading channels . We extend this framework to design algebraic codes for multiple-input multiple-output (MIMO) frequency-selective fading channels. The proposed codes strive to optimally exploit both the spatial and frequency diversity available in the channel. We consider two design approaches: The first uses space-time coding and maximum likelihood decoding to exploit the multi-path nature of the channel at the expense of increased receiver complexity. Within this time domain framework, we also propose a serially concatenated coding construction which is shown to offer a performance gain with a reasonable complexity iterative receiver in some scenarios. The second approach utilizes the orthogonal frequency division multiplexing technique to transform the MIMO multipath channel into a MIMO flat block fading channel. The algebraic framework is then used to construct space-frequency codes (SFC) that optimally exploit the diversity available in the resulting flat block fading channel. Finally, the two approaches are compared in terms of decoder complexity, maximum achievable diversity advantage, and simulated frame error rate performance in certain representative scenarios.     

Sampling-based soft equalization for frequency-selective MIMO channels

We consider the problem of channel equalization in broadband wireless multiple-input multiple-output (MIMO) systems over frequency-selective fading channels, based on the sequential Monte Carlo (SMC) sampling techniques for Bayesian inference. Built on the technique of importance sampling, the stochastic sampler generates weighted random MIMO symbol samples and uses resampling to rejuvenate the sample streams; whereas the deterministic sampler, a heuristic modification of the stochastic counterpart, recursively performs exploration and selection steps in a greedy manner in both space and time domains. Such a space-time sampling scheme is very effective in combating both intersymbol interference and cochannel interference caused by frequency-selective channel and multiple transmit and receiver antennas. The proposed sampling-based MIMO equalizers significantly outperform the decision-feedback MIMO equalizers with comparable computational complexity. More importantly, being soft-input soft-output in nature, these sampling-based MIMO equalizers can be employed as the first-stage soft demodulator in a turbo receiver for coded broadband MIMO systems. Such a turbo receiver successively improves the receiver performance through iterative equalization, channel re-estimation, and channel decoding. Finally, computer simulation results are provided to demonstrate the performance of the proposed sampling-based soft MIMO equalizers in both uncoded and turbo coded systems.     

Equalization of linearly frequency-selective fading channels

A simple technique for removing intersymbol interference (ISI) introduced by “linearly frequency-selective” fading channels is presented. The technique involves the optimization of the overall impulse response of the transmit and receive filters and effectively reduces the channel to one which is flat fading. Computer simulation results show that this equalization method works for channels with small delay spreads     

Effective capacity channel model for frequency-selective fading channels

To efficiently support quality of service (QoS) in future wireless networks, it is important to model a wireless channel in terms of connection-level QoS metrics such as data rate, delay and delay-violation probability. To achieve this, in [7], we proposed and developed a link-layer channel model termed effective capacity (EC) for flat fading channels. In this paper, we apply the effective capacity technique to modeling frequency selective fading channels. Specifically, we utilize the duality between the distribution of a queue with superposition of N i.i.d. sources, and the distribution of a queue with a frequency-selective fading channel that consists of N i.i.d. sub-channels, to model a frequency selective fading channel. In the proposed model, a frequency selective fading channel is modeled by three EC functions; we also propose a simple and efficient algorithm to estimate these EC functions. Simulation results show that the actual QoS metric is closely approximated by the QoS metric predicted by the proposed EC channel model. The accuracy of the prediction using our model can translate into efficiency in admission control and resource reservation. Dapeng Wu received B.E. in Electrical Engineering from Huazhong University of Science and Technology, Wuhan, China, in 1990, M.E. in Electrical Engineering from Beijing University of Posts and Telecommunications, Beijing, China, in 1997, and Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University, Pittsburgh, PA, in 2003. From July 1997 to December 1999, he conducted graduate research at Polytechnic University, Brooklyn, New York. During the summers of 1998, 1999 and 2000, he conducted research at Fujitsu Laboratories of America, Sunnyvale, California, on architectures and traffic management algorithms in the Internet and wireless networks for multimedia applications. Since August 2003, he has been with Electrical and Computer Engineering Department at University of Florida, Gainesville, FL, as an Assistant Professor. His research interests are in the areas of networking, communications, multimedia, signal processing, and information and network security. He received the IEEE Circuits and Systems for Video Technology (CSVT) Transactions Best Paper Award for Year 2001. Currently, he is an Associate Editor for the IEEE Transactions on Vehicular Technology and Associate Editor for International Journal of Ad Hoc and Ubiquitous Computing. He served as Program Chair for IEEE/ACM First International Workshop on Broadband Wireless Services and Applications (BroadWISE 2004); and as TPC member of over 30 conferences. He is Vice Chair of Mobile and wireless multimedia Interest Group (MobIG), Technical Committee on Multimedia Communications, IEEE Communications Society. He is a member of the Best Paper Award Committee, Technical Committee on Multimedia Communications, IEEE Communications Society. He is also Director of Communications, IEEE Gainesville Section. Rohit Negi received the B.Tech. degree in Electrical Engineering from the Indian Institute of Technology, Bombay, India in 1995. He received the M.S. and Ph.D. degrees from Stanford University, CA, USA, in 1996 and 2000 respectively, both in Electrical Engineering. He has received the President of India Gold medal in 1995. Since 2000, he has been with the Electrical and Computer Engineering department at Carnegie Mellon University, Pittsburgh, PA, USA, where he is an Associate Professor. His research interests include signal processing, coding for communications systems, information theory, networking, cross-layer optimization and sensor networks.     

Space-time-frequency coded OFDM over frequency-selective fading channels

This paper proposes novel space-time-frequency (STF) coding for multi-antenna orthogonal frequency-division multiplexing (OFDM) transmissions over frequency-selective Rayleigh fading channels. Incorporating subchannel grouping and choosing appropriate system parameters, we first convert our system into a set of group STF (GSTF) systems. This enables simplification of STF coding within each GSTF system. We derive design criteria for STF coding and exploit existing ST coding techniques to construct both STF block and trellis codes. The resulting codes are shown to be capable of achieving maximum diversity and coding gains, while affording low-complexity decoding. The performance merits of our design are confirmed by corroborating simulations and compared with existing alternatives.     

MIMO capacity convergence in frequency-selective channels

The dependence of multi-antenna capacity on bandwidth is characterized empirically for narrowband, wideband and ultrawideband indoor channels using spatial and polar arrays. It is shown that both the mean and the outage MIMO capacity increase with bandwidth, whilst the capacity coefficient of variation asymptotically vanishes.     

Trellis coded GMSK in frequency-selective fading channels

The BER performance of a spectrally efficient trellis coded modulation (TCM) scheme, which combines convolutional coding and GMSK, in frequency-selective fading channels, is presented. Computer simulated results show that a significant improvement in the BERs is achievable with the TCM scheme. The TCM scheme also shows less sensitivity to carrier phase errors than the uncoded scheme     

Differential space-time-frequency modulation over frequency-selective fading channels

We present a differential space-time-frequency (DSTF) modulation scheme for systems with two transmit antennas over frequency-selective fading channels. The proposed DSTF scheme employs a concatenation of a spectral encoder and a differential encoder/mapper, which are designed to yield the maximum spatio-spectral diversity and significant coding gain. To reduce the decoding complexity, the differential encoder is designed with a unitary structure that decouples the maximum likelihood (ML) detection in space and time; meanwhile, the spectral encoder utilizes a linear constellation decimation (LCD) coding scheme that encodes across a minimally required set of subchannels for full diversity and, hence, incurs the least decoding complexity among all full-diversity codes.     

Adaptive Bayesian and EM-based detectors for frequency-selective fading channels

The problems of adaptive maximum a posteriori (MAP) symbol detection for uncoded transmission and of adaptive soft-input soft-output (SISO) demodulation for coded transmission of data symbols over time-varying frequency-selective channels are explored within the framework of the expectation-maximization (EM) algorithm. In particular, several recursive forms of the classical Baum-Welch (BW) algorithm and its Bayesian counterpart (often referred to a Bayesian EM algorithm) are derived in an unified way. In contrast to earlier developments of the BW and BEM algorithms, these formulations lead to computationally attractive algorithms which avoid matrix inversions while using sequential processing over the time and trellis branch indices. Moreover, it is shown how these recursive versions of the BW and BEM algorithms can be integrated with the well-known forward-backward processing SISO algorithms resulting in adaptive SISOs with embedded soft decision directed (SDD) channel estimators. An application of the proposed algorithms to iterative "turbo-processing" receivers illustrates how these SDD channel estimators can efficiently exploit the extrinsic information obtained as feedback from the SISO decoder in order to enhance their estimation accuracy.     

Multiuser adaptive transmission technique for time-varying frequency-selective fading channels

This paper proposes an efficient multiuser adaptive modulation and coding (AMC) scheme that considers inevitable feedback delay by employing short-term and long-term channel state information (CSI) in time-varying frequency-selective fading channels. By taking the statistic of the true signal-to-noise ratio (SNR) at a given predicted SNR value into account, the required transmit power to meet the target packet-error-rate (PER) can be obtained and used for user selection, power allocation, and modulation and coding set (MCS) selection. In addition, a simple and useful approximation method of obtaining the required transmit power is proposed. The performance of the proposed scheme is shown to be much better than that of conventional schemes without considering the feedback delay or the prediction error. The proposed scheme can also reduce the feedback resource while maintaining the system throughput by allocating different feedback resources to different users according to their prediction error variances.     

Reduced-rank multistage receivers for DS-CDMA in frequency-selective fading channels

Multistage (MS) implementation of the minimum mean-square error (MMSE), minimum output energy (MOE), best linear unbiased estimation (BLUE), and maximum-likelihood (ML) filter banks (FBs) is developed based on the concept of the MS Wiener filtering (MSWF) introduced by Goldstein et al. These FBs are shown to share a common MS structure for interference suppression, modulo a distinctive scaling matrix at each filter's output. Based on this finding, a framework is proposed for joint channel estimation and multiuser detection (MUD) in frequency-selective fading channels. Adaptive reduced-rank equal gain combining (EGC) schemes for this family of FBs (MMSE, MOE, BLUE, and ML) are proposed for noncoherent blind MUD of direct-sequence code-division multiple-access systems, and contrasted with the maximal ratio combining counterparts that are also formed with the proposed common structure under the assumption of known channel-state information. The bit-error rate, steady-state output signal-to-interference plus noise ratio (SINR), and convergence of the output SINRs are investigated via computer simulation. Simulation results indicate that the output SINRs attain full-rank performance with much lower rank for a highly loaded system, and that the adaptive reduced-rank EGC BLUE/ML FBs outperform the EGC MMSE/MOE FBs, due to the unbiased nature of the implicit BLUE channel estimators employed in the EGC BLUE/ML schemes.