Iterative receivers with joint channel and frequency offset estimation in time-variant fading channels

In this paper, a coded convolutional spreading codedivision multiaccess with cyclic prefix (CS-CDMA/CP) system in conjunction with iterative receivers is proposed for synchronous downlink transmission over frequency selective fading channels and its performance is compared with the uncoded CS-CDMA/CP employing maximum-likelihood sequence estimation (MLSE) receiver as well as with the conventional coded direct sequence CDMA (DS-CDMA) employing (maximal ratio combining-) MRC-RAKE. Contrary to the uncoded CSCDMA/ CP system which suffers from performance degradation at low signal-to-noise power ratios (SNRs), it is demonstrated that the proposed scheme can attain almost the full path diversity gain over all SNRs with single-user complexity. Compared with the coded DS-CDMA system with single-user receivers, the proposed system is free from multiuser interference (MUI) whenever the multipath delay of the channel does not exceed the designed maximum delay. It is also demonstrated, moreover, that the proposed system shows a robust performance even if the channel length exceed the designed maximum delay slightly. Because of the subblock structure of CS-CDMA/CP, the proposed system can utilize time-diversity effects, when the channel subjects fast fading, and this greatly improves the resultant performance. Finally, it is shown that the receiver complexity of the proposed system is compared quite favorably with the iterative multiuser receivers for coded DS-CDMA systems of comparable performance.

Channel interpolation for LTE uplink systems with high mobility using Slepian sequences

In this paper, we study the achievable rate of the training-based multi-input multi-output (MIMO) systems over time-varying flat fading channels modeled with the $L$-th order autoregressive, AR($L$), process. Using the Bayesian Cram\'{e}r-Rao lower bound (BCRB) to characterize the mean squared error of channel estimation, the achievable rate of the MIMO systems is investigated from the information-theoretical perspective. The optimum lengths for the training and the data blocks are determined to maximize the achievable rate. Besides, by modeling the time-varying wireless fading channel with a proper AR($L$) model for the specific normalized Doppler frequency, $f_dT_s$, the aforementioned results can be extended to characterize the achievable rate in a more realistic time-varying wireless fading channel.

In this paper, the performance of limited feedback precoded spatial multiplexing multiple-input multiple-output orthogonal frequency division multiplexing (MIMO - OFDM) systems is investigated in time varying fading channels. Most studies into limited feedback precoded (MIMO - OFDM) systems are based on the notion of time invariant channels throughout transmission. Therefore, the precoding matrix for each subcarrier can be designed at the receiver in terms of the current channel state, fed back to the transmitter, and used for the subsequent block of data symbols. However, in time varying channels, the feedback information becomes outdated, which results in significant system performance degradation. To mitigate this system performance degradation caused by outdated information due to a delay in the feedback channel, this paper considers a more practical system, where the channel varies from one block of symbols to another. A method is proposed based on modelling the channel as an autoregressive (AR) model and using a Kalman filter linear predictor at the receiver to predict the channels states, required to design the precoding matrices for the next OFDM symbol carriers whose indexes are fed back to the transmitter. The performance of this method is investigated using computer simulation, and the results obtained for the proposed channel prediction demonstrate improved bit error rate performance for time-varying Rayleigh fading channels, even in systems with high mobility.

For direct-sequence code-division multiple-access (DS-CDMA) time-varying channels with additive Gaussian noise, we propose a new receiver. Since channel tracking plays an essential role in practice in equalization of the receiver, a new and viable design approach, a modified interacting multiple-model (MIMM) algorithm, is proposed for tracking of multipath time-varying fading channels. We employ a set of second-order auto-regressive (AR2) multiple models associated with a Makov jump process to cover the range of channel dynamics. This setup leads to an AR2-based MIMM channel tracker which can automatically adjust channel model parameters to track time-varying fading channels for all times once some design parameters are initialized. We employ a Kalman filter as a symbol detector (KBSD). Simulation studies demonstrate that the performance of the AR2-MIMM channel tracker together with a conventional KBSD performs at least as well as that of the ideal AR2-based Kalman channel estimator having the exact knowledge of the Doppler rate of each channel in combination with the KBSD

With the challenges of the unknown noise and time-varying channel, a new modulation recognition algorithm is proposed in this paper. Firstly, we propose a new dynamic state-space model to describe the sequential modulation recognition problem. And the time-variant fading channel is described by finite state Markov channel. Secondly, based on particle filter technology which can overcome the adverse effects of time-varying noise and sequential Bayesian inference method which can premeditate the dynamic transfer characteristics of the fading channel gain, a new algorithm is proposed to estimate the noise variance, channel state and modulation scheme jointly. The algorithm can raise modulation recognition performance with unknown noise variance in the time-varying channel by simulation.

In selective cooperative relaying only a single relay out of the set of available relays is activated, hence the available power and bandwidth resources are efficiently utilized. However, implementing selective cooperative relaying in time-varying channels may cause frequent relay switchings that deteriorate the overall performance. In this paper, we study the rate at which a relay switching occurs in selective cooperative relaying applications in time-varying fading channels. In particular, we derive closed-form expressions for the relay switching rate (measured in Hz) for opportunistic relaying (OR) and distributed switch and stay combining (DSSC). Additionally, expressions for the average relay activation time for both of the considered schemes are also provided, reflecting the average time that a selected relay remains active until a switching occurs. Numerical results manifest that DSSC yields considerably lower relay switching rates than OR, along with larger average relay activation times, rendering it a better candidate for implementation of relay selection in fast fading environments.

A communication system model for mutual information performance analysis of multiple-symbol differential M-phase shift keying over time-correlated, time-varying flat-fading communication channels is developed. This model is a finite-state Markov (FSM) equivalent channel representing the cascade of the differential encoder, FSM channel model and differential decoder. A state-space approach is used to model channel phase time correlations. The equivalent model falls in a class that facilitates the use of the forward–backward algorithm, enabling the important information theoretic results to be evaluated. Using such a model, one is able to calculate mutual information for differential detection over time-varying fading channels with an essentially finite time set of correlations, including the Clarke fading channel. Using the equivalent channel, it is proved and corroborated by simulations that multiple-symbol differential detection preserves the channel information capacity when the observation interval approaches infinity.

Instantaneous mutual information (IMI) is the amount of information that a time-varying channel can convey for the given time instant. In this paper, second-order statistics of IMI are studied in time-varying underwater acoustic particle velocity channels. First, the autocorrelation function, correlation coefficient, level crossing rate, and average outage duration of IMI are provided in a time-varying fading channel. Exact expressions are given in terms of the summation of special functions, which facilitate numerical calculations. Then, accurate approximations for the autocorrelation function and correlation coefficient are presented for low and high signal-to-noise ratios. Moreover, analytical and numerical results are provided for the correlation and level-crossing characteristics of IMI in underwater particle velocity channels. The results shed light on the dynamic behavior of mutual information in underwater acoustic particle velocity channels. [Work supported in part by the National Science Foundation (NSF), Grant CCF-0830190.]

Linear precoded OFDM systems with channel coding have already been demonstrated to efficiently exploit frequency and time diversities of the transmission channel. Iterative receivers which iteratively perform channel decoding and deprecoding provide very good performance. In the literature, these iterative receivers are based on maximum likelihood based functions for both linear deprecoding and channel decoding leading to a high complexity for large size of preceding matrices or high modulation order. In this paper, a simple linear operation instead of a maximum likelihood based one is carried out for deprecoding allowing the use of large preceding matrices and thus an optimal exploitation of the signal diversity.

In this paper, we study the design of expectation-maximization (EM)-based iterative receivers for low-density parity check -coded multiple-input multiple-output orthogonal frequency-division multiplexing systems with the presence of carrier-frequency offset (CFO). First, starting from the maximum-likelihood principle, we devise a novel EM-based pilot-aided scheme for joint estimation of CFO and channel coefficients. Then, this estimator is incorporated into the initialization step of the iterative receiver. Simulation results show the effectiveness of our receiver design in combating CFO over unknown frequency selective fading channels.

An iterative detection and decoding (IDD) technique has recently received much attention due to its capacity approaching performance and manageable complexity for (parallel) turbo-coded systems. The existing IDD receivers process indiscriminately the a priori information of the systematic bits and the parity bits generated by the turbo decoder in the front-end detection. In this paper, we first show that the parity bits of the parallel turbo codes are inherently less protected than the systematic bits, which leads to suboptimality for the IDD receivers. Based on this observation, we then propose an unequal-error-correcting-capability-aware technique to mitigate the associated performance loss. As an illustrative example, the minimum-mean-square-error (MMSE) filtering and soft interference cancelation (MMSE-SIC)-aided iterative receiver for parallel-turbo-coded multiple-input-multiple-output (MIMO) systems is employed in this paper. Numerical results manifest that the MMSE-SIC-aided iterative receiver based on the proposed paradigm achieves noticeable performance gains over the conventional unequal-error-correcting-capability-agnostic one even with reduced computational complexity. The extension of the proposed principle to other iterative algorithms for parallel-turbo-coded data transmission is straightforward.

3GPP (3rd Generation Partnership Project) LTE (Long Term Evolution) Advanced standards are currently under way, where 4×4 MIMO (Multiple Input Multiple Output) scheme is the minimum structure. One of the best solutions to support the maximum data rate transmission is to adopt a MIMO scheme, especially spatial multiplexing mode, which means that each antenna port can transmit separate data. To realize this algorithm, the main issue is to cancel interferences added to each antenna port, and therefore, the algorithm at the receiver should have good performances. In the aspect of implementation, MMSE (Minimum Mean Square Error) detection algorithm is a reasonable method considering both complexity and performance. Furthermore, an iterative receiver (IR) algorithm can also be applied to this system. An IR algorithm has a tradeoff between complexity and performance. In this paper, we designed a reasonable and implementable MIMO receiver structure and showed performance for 3GPP LTE Advanced system, and verified that hard decoded bits, PIC-MMSE (Parallel Interference Cancellation - MMSE) and 1-iteration PIC are enough to meet the required SNR using the implemented test-bed system.

Highmobility is an important scenario for the 5G wireless communications. However, the high mobility results in serious time-varying fading, bringing challenges to the reliabilities of wireless transmission. Diversity technique is an essential method to overcome the effect of fading. It is noted that an LDPC (low-density parity-check) code is a concatenation of single parity-check codes (SPC) and repetition codes (REP) by a random interleaver, and a REP can be viewed as a typical example for achieving time/frequency diversity. Thus, it is appealing to jointly consider LDPC codes and diversity techniques. This paper presents parity-check coding transmit diversity (PCTD) schemes based on half-rate invertible LDPC codes, which are capable of achieving both diversity and coding gains from the time-varying fading channels. Besides, we investigate two types of PCTD schemes, and take into consideration two transmission modes, which are single-carrier (SC) and orthogonal frequency division multiplexing (OFDM) transmission modes. A chase combining based message passing algorithm (CC-MPA) is proposed for the proposed schemes, which can take full advantages of signal processing and coding gains. Furthermore, the Shannon limits of time-varying fading channels with BPSK signaling are deduced. Simulation results show that the proposed PCTD with CC-MPA algorithm can provide better BER performances than the classical time-domain diversity scheme in time-varying fading channels, which is appealing for the high mobility communications.

The multi-input multi-output channel model has been widely considered for next generation multimedia wireless communication systems. In this paper, we consider the problem of joint channel estimation and data detection for MIMO systems under quasi-static channels with known and unknown spatially correlated noise. We propose two computationally efficient iterative receivers based on space-alternating generalized expectation-maximization (SAGE) algorithms. Bit error rate (BER) performance of the Maximum likelihood (ML) receivers with perfect channel state information (CSI) is simulated and compared with the BER performance of the proposed iterative receivers. The results show that the proposed receivers exhibit near ML performance with a few iterations