Orthogonal frequency division multiplexing (OFDM) has been widely adopted in modern wireless communication systems due to its robustness against the frequency selectivity of wireless channels. For coherent detection, channel estimation is essential for receiver design. Channel estimation is also necessary for diversity combining or interference suppression where there are multiple receive antennas. In this paper, we will present a survey on channel estimation for OFDM. This survey will first review traditional channel estimation approaches based on channel frequency response (CFR). Parametric model (PM)-based channel estimation, which is particularly suitable for sparse channels, will be also investigated in this survey. Following the success of turbo codes and low-density parity check (LDPC) codes, iterative processing has been widely adopted in the design of receivers, and iterative channel estimation has received a lot of attention since that time. Iterative channel estimation will be emphasized in this survey as the emerging iterative receiver improves system performance significantly. The combination of multiple-input multiple-output (MIMO) and OFDM has been widely accepted in modern communication systems, and channel estimation in MIMO-OFDM systems will also be addressed in this survey. Open issues and future work are discussed at the end of this paper.

Channel Estimation for OFDM

Cellular networks are currently experiencing a tremendous growth of data traffic. To cope with this demand, a close cooperation between academic researchers and industry/standardization experts is necessary, which hardly exists in practice. In this paper, we try to bridge this gap between researchers and engineers by providing a review of current standard-related research efforts in wireless communication systems. Furthermore, we give an overview about our attempt in facilitating the exchange of information and results between researchers and engineers, via a common simulation platform for 3GPP long term evolution (LTE) and a corresponding webforum for discussion. Often, especially in signal processing, reproducing results of other researcher is a tedious task, because assumptions and parameters are not clearly specified, which hamper the consideration of the state-of-the-art research in the standardization process. Also, practical constraints, impairments imposed by technological restrictions and well-known physical phenomena, e.g., signaling overhead, synchronization issues, channel fading, are often disregarded by researchers, because of simplicity and mathematical tractability. Hence, evaluating the relevance of research results under practical conditions is often difficult. To circumvent these problems, we developed a standard-compliant opensource simulation platform for LTE that enables reproducible research in a well-defined environment. We demonstrate that innovative research under the confined framework of a real-world standard is possible, sometimes even encouraged. With examples of our research work, we investigate on the potential of several important research areas under typical practical conditions, and highlight consistencies as well as differences between theory and practice.

Pushing the Limits of LTE: A Survey on Research Enhancing the Standard

The number of transmit and receive antennas in multi-input multi-output (MIMO) systems is increasing rapidly to enhance the throughput and reliability of next-generation wireless systems. Benefits of large size MIMO systems, however, can be realized only when the quality of estimated channels is ensured at the transmitter and receiver side alike. In this paper, we introduce a new decision-directed channel estimation technique dealing with pilot shortage in the MIMO-OFDM systems. The proposed channel estimator uses soft symbol decisions obtained by iterative detection and decoding (IDD) scheme to enhance the quality of channel estimate. Using the soft information from the decoders, the proposed channel estimator selects reliable data tones, subtracts interstream interferences, and performs re-estimation of the channels. We analyze the optimal data tone selection criterion, which accounts for the reliability of symbol decisions and correlation of channels between the data tones and pilot tones. From numerical simulations, we show that the proposed channel estimator achieves considerable improvement in system performance over the conventional channel estimators in realistic MIMO-OFDM scenarios.

Iterative Channel Estimation Using Virtual Pilot Signals for MIMO-OFDM Systems

A survey on OFDM channel estimation techniques based on denoising strategies

An OFDM communication system performs time domain channel estimation responsive to received symbols before the symbols are processed by a fast Fourier transform. The communication system generates virtual pilots from actual pilots to improve the stability and quality of channel estimation. The system generates a reference signal from the actual and virtual pilots and correlates the resulting reference signal with a signal responsive to the received symbol to generate an initial channel impulse response (CIR) and to determine statistics about the channel. In some circumstances, the resulting reference signal is correlated with a modified symbol in which the actual and virtual pilot locations are emphasized and the data locations are deemphasized. Time domain channel estimation iteratively improves on the initial CIR. The system determines channel estimates for data only symbols through averaging such as interpolation.

Ofdm receiver with time domain channel estimation

In this paper, an iterative channel estimation algorithm is considered in LTE systems. In order to take advantage of “null” sub-carriers (guard band) in LTE systems and make the algorithm simpler, an iterative compensated MMSE (IC-MMSE) channel estimation algorithm is proposed in frequency domain. Together with a simple “linear interpolation” in time domain, channel estimates are obtained in an iterative way with lower complexity. Theoretical analysis shows that the compensation process does not affect the accuracy of iterative MMSE channel estimation. Simulation results confirm that the proposed channel estimation has very robust performance and approaches the best achievable performance.

Iterative compensated MMSE channel estimation in LTE systems

A channel estimation treatment method and device for obtaining binary data conveyed in a signal. The method includes: obtaining a current vector of channel estimates, each element of the current vector corresponding to an estimate of a subchannel; detecting, inside the current vector, at least one pilot symbol; splitting the current vector in at least two subvectors, at least one first subvector including channel estimates related to data symbols and/or pilots symbols and at least one second subvector including channel estimates related to null symbols; decoding the at least one first subvector, delivering at least one first treated subvector; modifying the at least one second subvector by assuming presence of pilot symbols in the at least one second subvector, delivering at least one second treated subvector; and calculating a new vector of channel estimates with the at least one first treated subvector and the at least one second treated subvector.

Iterative channel estimation method with compensated mmse

In this paper, an iterative channel estimation algorithm is considered in LTE systems. A simplified expectation maximization (EM) based algorithm is proposed for channel estimation in the frequency domain. In order to deal with “null” sub-carriers in the guard band and make the algorithm simpler, the truncated singular value decomposition method is integrated to EM (TSVD-EM). Together with a simple linear interpolation in time domain, channel estimates are obtained in an iterative way with low complexity. The mean square error of the proposed algorithm is also analyzed, and, based on this analysis, an additional constant variance is proposed to be used in the detection process. Simulation results show that the proposed channel estimation and detection methods have very close performance to the perfect case.

Simplified EM channel estimation in LTE systems

A method and apparatus are provided for cancelling interferences of a received MIMO RF signal. The method includes: receiving a signal y; an initial step of obtaining, from the received signal y, at least one data representative of the received signal, called decoded data; computing the decoded data as a function of at least one predetermined criterion, delivering feedback data and a feedback decision; and, as a function of the feedback decision, at least one iteration of the following steps: constructing a set of feedback symbols from the feedback data; obtaining, from the set of feedback symbols, at least one data representative of a feedback decoded signal, called feedback decoded data; computing the at least one feedback decoded data as a function of the at least one predetermined criterion, delivering the feedback data.

Interference Cancellation Method with Multiple Data Layer MIMO Transmission

A channel estimating method is provided for a signal transmitted in an orthogonal frequency division multiplexing (OFDM) system, wherein an OFDM symbol of the signal has at least one null subcarrier set in its defined bandwidth. The method includes: obtaining at least one initial channel estimate over at least one OFDM symbol of a received signal; processing the at least one initial channel estimate for delivering at least one soft information in a form of a complete matrix; and updating the at least one initial channel estimate by performing a truncated singular value decomposition of a partial FFT matrix. The partial FFT matrix includes only the first L DP columns and the rows N DP of an FFT matrix of the complete matrix, the N DP rows corresponding to modulated subcarriers of received signal, including data and pilot symbols and excluding the at least one null subcarrier, delivering an improved channel estimate.

Yang Liu

Papers

Iterative compensated MMSE channel estimation in LTE systems

Iterative channel estimation method with compensated mmse

Simplified EM channel estimation in LTE systems

Interference Cancellation Method with Multiple Data Layer MIMO Transmission

Channel estimation method