Dieter Van Welden

Frequency-Domain Data-Aided Channel Estimation for KSP-OFDM

In this paper, we propose a new low-complexity data-aided channel estimation algorithm for known symbol padding (KSP) OFDM. Besides the pilot symbols in the guard interval, additional pilots are put on some of the OFDM carriers. The received time-domain samples are first converted to the frequency domain, and the channel estimation is based on the observation of the pilot carriers only. The proposed estimator is compared to the subset estimator from [1]. Although performing slightly worse than the subset estimator at low SNR, the proposed estimator outperforms the subset estimator at high SNR, as the former does not suffer from an error floor in the MSE. The MSE resulting from the proposed estimator is inversely proportional to the number of pilot carriers and is independent of the FFT size, the pilot carrier positions and the used pilot sequence.

Time delay estimation for KSP-OFDM systems in multipath fading channels

In this paper we present a time delay estimation algorithm for known symbol padding (KSP) orthogonal frequency division multiplexing (OFDM) systems. The estimator exploits both the pilot symbols in the guard interval and on the pilot carriers, and takes the frequency selectivity of the fading channel into account. Our simulations indicate that the time delay estimator gives rise to only a small degradation of the bit error rate (BER) performance, as compared to a receiver with perfect synchronization.

PAPR Reduction by Symbol Nulling

As a multicarrier signal can exhibit large peaks in the time domain, the amplifier used to transmit the multicarrier signal must be highly linear, and thus expensive, to avoid non-linear signal distortion. To reduce the high peak-to-average power ratio, and hence to allow cheaper amplifiers, several techniques are described in the literature. However, the drawback of these techniques is that they cause non-linear in-band distortion and out-of-band radiation, reduce the system throughput or require side-information. To avoid these drawbacks, we propose a PAPR reduction technique that has none of the abovementioned disadvantages. In the proposed technique, we replace some of the transmitted data symbols by nulls, Le we introduce errors in the transmitted signal. To counteract the effect of the introduced symbol errors, the transmitted information is encoded. At the receiver, an iterative decoder is used to correct the transmitter and channel errors. The performance of the proposed technique is compared with the clipping technique. Although the clipping technique slightly outperforms the proposed technique with respect to the obtainable PAPR reduction and corresponding BER degradation, the proposed technique does not suffer from non-linear in-band distortion and out-of-band radiation.

Frequency offset estimation for KSP-OFDM

In this paper, we propose two ad hoc frequency offset (FO) estimation algorithms in a known symbol padding (KSP) orthogonal frequency-division multiplexing (OFDM) system, where the guard interval is filled with pilot symbols. Besides those time domain pilot symbols, some additional pilot symbols are transmitted on the pilot carriers. The FO is estimated without any channel knowledge. One algorithm operates in the time domain (TD), while the other one operates in the frequency domain (FD). The interference from the unknown data symbols is much smaller in the FD than in the TD, especially for small FOs. As a result, the FD initialization algorithm results in a lower mean squared error (MSE). Both estimation algorithms reach the BER performance of a receiver with perfect knowledge about the FO.

Narrowband AM interference cancellation for broadband multicarrier systems

We consider an overlay system where narrowband AM signals interfere with a broadband multicarrier system. To reduce the effect of the AM narrowband interference on the multicarrier system, we propose a low-complexity algorithm to estimate the AM narrowband interference. Analytical expressions for the performance of this estimator are derived and verified with simulations. The performance of this estimator, however, degrades when the number of interferers increases. To improve the algorithm, we adapt it such that the interferers are estimated in a successive way. The proposed estimators are able to produce accurate estimates of the frequencies, and track the time-varying amplitudes of the AM signals. The estimators can reduce the power of the AM signal to a level that is approximately 20 dB lower than the multicarrier power, independently of the AM signal power.