Unknown Frequency-selective Fading Channels Research Articles

MIMO-OFDM Modulation Classification Using Three-Dimensional Convolutional Network

Automatic modulation classification (AMC) plays a vital role in cognitive radio to improve spectrum utilization efficiency, however, most of the existing works have focused on single-carrier communications in single-input single-output systems. In this paper, we propose an efficient AMC method for multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) communication systems with the assumption of unknown frequency-selective fading channels and signal-to-noise ratio. At the receiver, the complex envelope samples of a burst signal acquired by multiple antennas are decomposed into in-phase and quadrature samples, which are then structured into a high-dimensional data array. To learn the modulation patterns from received signals, we develop a deep network, namely three-dimensional MIMO-OFDM convolutional neural network (MONet). With cuboidal convolution filters, the proposed MONet allows the network to capture underlying features as intra- and inter-antenna correlations at multi-scale signal representations. Relying on simulations, MONet achieves the classification accuracy of over 95% at 0 dB SNR under various channel impairments and shows the robustness with different MIMO antenna configurations.

Modulation Classification for MIMO-OFDM Signals via Approximate Bayesian Inference

The problem of modulation classification for a multiple-antenna (MIMO) system employing orthogonal frequency division multiplexing (OFDM) is investigated under the assumption of unknown frequency-selective fading channels and signal-to-noise ratio (SNR). The classification problem is formulated as a Bayesian inference task, and solutions are proposed based on Gibbs sampling and mean field variational inference. The proposed methods rely on a selection of the prior distributions that adopts a latent Dirichlet model for the modulation type and on the Bayesian network formalism. The Gibbs sampling method converges to the optimal Bayesian solution and, using numerical results, its accuracy is seen to improve for small sample sizes when switching to the mean field variational inference technique after a number of iterations. The speed of convergence is shown to improve via annealing and random restarts. While most of the literature on modulation classification assume that the channels are flat fading, that the number of receive antennas is no less than that of transmit antennas, and that a large number of observed data symbols are available, the proposed methods perform well under more general conditions. Finally, the proposed Bayesian methods are demonstrated to improve over existing non-Bayesian approaches based on independent component analysis and on prior Bayesian methods based on the `superconstellation' method.

RLS-Based Estimation and Tracking of Frequency Offset and Channel Coefficients in MIMO-OFDM Systems

In this paper, we investigate the problem of carrier frequency-offset (CFO) synchronization and channel estimation in multiple-input multiple-output orthogonal frequency-division multiplexing systems operating over unknown frequency-selective fading channels. We first propose a novel joint CFO and channel estimator, assuming time-domain training blocks are available. The proposed joint estimator consists of two recursive least-square (RLS) algorithms which iterate their estimated CFO and CIR values. We then derive a more precise pilot-aided RLS algorithm to estimate the residual frequency synchronization errors or track small CFO changes. With this, the accuracy of channel estimation is also enhanced. The analysis and simulation results show that, the proposed estimation and tracking scheme which is fully compatible with the existing standards is able to attain fast convergence, high stability, and ideal performances as compared with relevant Cramer---Rao bounds in all ranges of signal-to-noise ratio. Moreover, it can work well for wide tracking range up to ±0.5 of the subcarrier spacing.

Joint maximum-likelihood estimation of frequency offset and channel coefficients in multiple-input multiple-output orthogonal frequency-division multiplexing systems with timing ambiguity

In this study, the authors consider a multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing system operating over unknown frequency-selective fading channels. Based on two different signal models, two maximum-likelihood schemes for joint carrier frequency offset (CFO) and MIMO channel estimation under timing ambiguity have been derived. The first estimator jointly estimates the timing offset, CFO and channel coefficients, but the complexity is high owing to the need of two-dimensional searches. The second estimator has a reduced complexity, but its performance slightly degrades compared with the first one. The performance of proposed estimators was benchmarked with Cramer–Rao bounds (CRB), and investigated by computer simulations. The simulation results show that the proposed estimators achieve almost ideal performances compared with the CRB.

Iterative Receiver Design with Joint Carrier-Frequency Offset and Channel Estimation for LDPC-Coded MIMO-OFDM Systems

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.

EM-based turbo receiver design for low-density parity-check-coded MIMO-OFDM systems with carrier-frequency offset

The design of expectation-maximisation (EM)-based turbo receivers for low-density parity-check-coded multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems with the presence of carrier-frequency offset (CFO) is studied. First, starting from the maximum-likelihood principle, a novel EM-based CFO estimator for MIMO-OFDM systems is devised. This estimator iteratively provides the CFO estimate with the aid of pilot symbols. It is also capable of accommodating any space-time-coded-OFDM transmission. Then this CFO estimator is incorporated into the initialisation step of the turbo receiver. Simulation results show the effectiveness of the receiver design in combating CFO over unknown frequency-selective fading channels.

Single- and Multiple-Antenna Constellations for Communication Over Unknown Frequency-Selective Fading Channels

Data transmission through frequency-selective block fading channels is considered in the case where neither the transmitter nor the receiver has any knowledge of the channel coefficients. Standard code design approaches for this scenario take channel uncertainty at the receiver into account by splitting the available channel coherence time into a part dedicated to training symbols utilized for channel estimation and a second part using an error-control coding scheme that is designed without channel uncertainty in mind. In contrast, in this correspondence joint codes are designed that are optimized for communication over the unknown channel and operate over the full coherence time. Using an approximation of the union bound on codeword error probability as design criterion, codes based on general complex-valued symbols are obtained with a gradient search optimization technique. Numerical examples for both single antenna as well as multiple-antenna systems illustrate that significant improvement over training-based schemes can be obtained

Maximum-likelihood symbol synchronization for IEEE 802.11a WLANs in unknown frequency-selective fading channels

Based on the maximum-likelihood principle and the preamble structure of IEEE 802.11a wireless local area network (WLAN) standard, this paper proposes a new symbol synchronization algorithm for IEEE 802.11a WLANs over frequency-selective fading channels. In addition to the physical channel, the effects of filtering and unknown sampling phase offset are also considered. Loss in system performance due to synchronization error is used as a performance criterion. Computer simulations show that the proposed algorithm exhibits better performances than the simple correlation-based algorithms. When compared to the algorithm based on the generalized Akaike information criterion, the proposed algorithm presents comparable performance and exhibits reduced complexity.

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.

A space-time block-coded OFDM scheme for unknown frequency-selective fading channels

We introduce a space-time block-coded orthogonal frequency-division multiplexing (STBC-OFDM) selective fading channels which does not require channel knowledge either at the transmitter or at the receiver. The decoding algorithm is based on generalized maximum-likelihood sequence estimation. We investigate the performance of the proposed scheme over two-tap Rayleigh fading channels. Simulation results show the performance to be near optimum.

Bayesian Monte Carlo multiuser receiver for space-time coded multicarrier CDMA systems

We consider the design of optimal multiuser receivers for space-time block coded (STBC) multicarrier code-division multiple-access (MC-CDMA) systems in unknown frequency-selective fading channels. Under a Bayesian framework, the proposed multiuser receiver is based on the Gibbs sampler, a Markov chain Monte Carlo (MCMC) method for numerically computing the marginal a posteriori probabilities of different users' data symbols. By exploiting the orthogonality property of the STBC and the multicarrier modulation, the computational complexity of the receiver is significantly reduced. Furthermore, being a soft-input soft-output algorithm, the Bayesian Monte Carlo multiuser detector is capable of exchanging the so-called extrinsic information with the maximum a posteriori (MAP) outer channel code decoders of all users, and successively improving the overall receiver performance. Several practical issues, such as testing the convergence of the Gibbs sampler in fading channel applications, resolving the phase ambiguity as well as the antenna ambiguity, and adapting the proposed receiver to multirate MC-CDMA systems, are also discussed. Finally, the performance of the Bayesian Monte Carlo multiuser receiver is demonstrated through computer simulations.

A new blind receiver for downlink DS-CDMA communications

A linear receiver is proposed for downlink DS-CDMA communications over unknown frequency-selective fading channels. The new receiver exploits the fact that all synchronized downlink signals go through the same channel and recovers the desired signal with a constrained channel equalizer followed by a despreader. Such a scheme allows the receiver to operate blindly in a time varying environment for both periodic CDMA and aperiodic CDMA systems.