Low-Complexity Banded Equalizers for OFDM Systems in Doppler Spread Channels

Recently, several approaches have been proposed for the equalization of orthogonal frequency-division multiplexing (OFDM) signals in challenging high-mobility scenarios. Among them, a minimum mean-squared error (MMSE) block linear equalizer (BLE), based on a band LDL factorization, is particularly attractive for its good tradeoff between performance and complexity. This paper extends this approach towards two directions. First, we boost the BER performance of the BLE by designing a receiver window specially tailored to the band LDL factorization. Second, we design an MMSE block decision-feedback equalizer (BDFE) that can be modified to support receiver windowing. All the proposed banded equalizers share a similar computational complexity, which is linear in the number of subcarriers. Simulation results show that the proposed receiver architectures are effective in reducing the BER performance degradation caused by the intercarrier interference (ICI) generated by time-varying channels. We also consider a basis expansion model (BEM) channel estimation approach, to establish its impact on the BER performance of the proposed banded equalizers.Electrical Engineering, Mathematics and Computer Scienc

Maximum-Likelihood Semiblind Equalization of Doubly Selective Channels Using the EM Algorithm

Maximum-likelihood semi-blind joint channel estimation and equalization for doubly selective channels and single-carrier systems is proposed. We model the doubly selective channel as an FIR filter where each filter tap is modeled as a linear combination of basis functions. This channel description is then integrated in an iterative scheme based on the expectation-maximization (EM) principle that converges to the channel description vector estimation. We discuss the selection of the basis functions and compare various functions sets. To alleviate the problem of convergence to a local maximum, we propose an initialization scheme to the EM iterations based on a small number of pilot symbols. We further derive a pilot positioning scheme targeted to reduce the probability of convergence to a local maximum. Our pilot positioning analysis reveals that for high Doppler rates it is better to spread the pilots evenly throughout the data block (and not to group them) even for frequency-selective channels. The resulting equalization algorithm is shown to be superior over previously proposed equalization schemes and to perform in many cases close to the maximum-likelihood equalizer with perfect channel knowledge. Our proposed method is also suitable for coded systems and as a building block for Turbo equalization algorithms

Estimation and Direct Equalization of Doubly Selective Channels

We propose channel estimation and direct equalization techniques for transmission over doubly selective channels. The doubly selective channel is approximated using the basis expansion model (BEM). Linear and decision feedback equalizers implemented by time-varying finite impulse response (FIR) filters may then be used to equalize the doubly selective channel, where the time-varying FIR filters are designed according to the BEM. In this sense, the equalizer BEM coefficients are obtained either based on channel estimation or directly. The proposed channel estimation and direct equalization techniques range from pilot-symbol-assisted-modulation- (PSAM-) based techniques to blind and semiblind techniques. In PSAM techniques, pilot symbols are utilized to estimate the channel or directly obtain the equalizer coefficients. The training overhead can be completely eliminated by using blind techniques or reduced by combining training-based techniques with blind techniques resulting in semiblind techniques. Numerical results are conducted to verify the different proposed channel estimation and direct equalization techniques.Electrical Engineering, Mathematics and Computer Scienc